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Capacity Planning Tools and Techniques for Efficient Resource Management

March 15, 2024 by Maria Garcia

business intelligence for capacity planning

In the ever-evolving landscape of business and technology, efficient resource management stands as a crucial pillar for organizational success. Capacity planning, the process of determining the resources required to meet future workload demands, is essential in ensuring that resources are utilized effectively, minimizing waste, and optimizing performance. This blog post delves into the various tools and techniques used in capacity planning to facilitate informed decision-making and robust resource management.

Understanding Capacity Planning

Capacity planning is a strategic process that involves predicting future resource requirements to prevent resource shortages or excesses. It balances the act between under-utilization and over-utilization of resources, ensuring that the right amount of resources is available at the right time. This process is vital for managing IT infrastructure, workforce, production capabilities, and more.

Key Techniques in Capacity Planning

1. trend analysis.

Trend analysis involves examining historical data to predict future resource needs. By analyzing past usage patterns, businesses can forecast future demands and plan accordingly. Tools like time-series analysis, regression models, and moving averages are commonly used to identify trends and predict future requirements.

2. Scenario Planning

Scenario planning considers various future possibilities and creates plans for different scenarios. This technique helps organizations prepare for uncertain futures by considering a range of potential events and their impacts on resource needs. It’s particularly useful in dynamic environments where external factors can significantly influence demand.

3. Demand Forecasting

Demand forecasting uses statistical tools and models to predict future demand for products or services. This method helps in aligning the resources such as manpower, materials, and production capacity to meet the anticipated demand, ensuring efficient resource utilization.

4. Resource Allocation Models

Resource allocation models help in optimally distributing resources across various departments, projects, or processes. Techniques like linear programming, simulation models, and optimization algorithms are used to allocate resources effectively, considering constraints and objectives.

Popular Tools for Capacity Planning

1. project management software.

Tools like Microsoft Project, JIRA, and Asana offer features for resource planning and tracking, helping managers allocate resources effectively and monitor their utilization.

2. Simulation Software

Simulation tools, such as SimPy or Arena, allow businesses to model and analyze how different resource allocations will affect output and performance, providing insights into the optimal allocation of resources.

3. Capacity Planning Software

Dedicated capacity planning software, like CA Capacity Manager or HPE OneView, provides comprehensive solutions for monitoring, analyzing, and predicting resource requirements, enabling proactive management of IT infrastructure and other resources.

4. Business Intelligence Tools

Business intelligence (BI) tools, such as Tableau and Power BI, are crucial for analyzing data and providing actionable insights into resource utilization, trends, and forecasting.

Best Practices in Capacity Planning

  • Regular Monitoring and Review : Continuous monitoring of resource utilization and performance helps in timely adjustments and ensures resources are aligned with current demands.
  • Integrating Capacity Planning with Strategic Planning : Aligning capacity planning with business objectives and strategic plans ensures that resources are allocated in line with long-term goals.
  • Flexibility and Scalability : Plans should be flexible and scalable to adapt to changing demands and circumstances, preventing resource shortages or excesses.

Effective capacity planning is indispensable for optimizing resource utilization, enhancing operational efficiency, and supporting strategic business growth. By leveraging the right tools and techniques, organizations can anticipate future demands, make informed decisions, and maintain a competitive edge in their respective markets. In an era where resources are precious, capacity planning shines as a beacon of efficient and sustainable management.

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Understanding the Power of AI in Capacity Planning

Capacity Planning in IT

Introduction

In the dynamic realm of IT operations, the capacity planning process has become a cornerstone for ensuring that organizations can meet actual demand efficiently. With the rise of artificial intelligence, there's a transformative shift in how strategic capacity planning is approached.

AI not only streamlines the capacity planning process but also introduces predictive capabilities , allowing for more effective resource planning to fulfill demand.

This article delves deep into the following:

  • intricacies of capacity planning
  • limitations of traditional capacity planning
  • capacity planning strategies that organizations can employ
  • benefits of integrating AI in resource capacity planning
  • future of AI in capacity planning

From understanding the nuances of production capacity planning to exploring the tools available, we'll provide a comprehensive guide on navigating the challenges of resource management and meeting the anticipated demand.

Whether you're looking to optimize your current capacity , understand the types of capacity planning , or explore the benefits of capacity planning software , this article serves as a holistic resource. As customer demand grows, it's imperative for organizations to prioritize projects , allocate resources aptly , and ensure they have enough resources to match their capacity strategy.

Let's embark on this journey to understand the power of AI in capacity planning and how it's reshaping the landscape of operations management.

What is Capacity Planning in IT?

Capacity planning in IT is a strategic process that ensures an organization's IT resources , such as hardware , software , and network capacities , are sufficient to meet future operational demands .

It involves forecasting the organization's future IT requirements based on current operations, growth rate, and industry trends.

The goals of capacity planning are:

business intelligence for capacity planning

Maintain Optimal Performance

Organizations can ensure their IT resources are adequately provisioned through meticulous capacity planning strategies. This proactive approach to resource planning ensures that the performance of IT services remains at optimal levels, catering to the ever-evolving customer demand and adapting to market trends. By understanding the capacity requirements and aligning them with the capacity plan, businesses can consistently deliver high-quality services.

Avoid Service Disruptions

Capacity planning is not just about meeting the current needs but also about anticipating future resource requirements. Capacity planning can effectively prevent service disruptions by meticulously analyzing past data, understanding current market trends, and predicting future shifts. Such disruptions often arise due to resource shortages, especially during peak demand periods. A well-executed capacity planning strategy ensures that organizations are always a step ahead, ready to tackle challenges and meet customer expectations.

Prevent Unnecessary Expenditures

Financial prudence is at the heart of effective capacity management. By accurately predicting resource needs through strategic planning, capacity planning helps organizations streamline their expenditures. This means businesses can allocate their budget more efficiently, ensuring they invest in IT resources that offer the most value. By avoiding over-provisioning or under-provisioning, organizations can prevent unnecessary expenditures, ensuring that every dollar spent contributes to achieving their overarching objectives.

The Limitations of Traditional Capacity Planning

Let's start with a capacity planning example:

Imagine a retail company with many team members that has been in operation for over two decades. Their resource capacity planning for the holiday season is based on sales data from previous years. The IT team asks themselves, " How much capacity do we need? " and manually reviews this data, considering factors like past sales , inventory levels , and anticipated market trends in order to make a plan that fulfills demand.

Based on their capacity planning strategy, they allocate sufficient resources for their online store's server capacity. This is done with the expectation of meeting a similar customer demand pattern as in previous years. Their goal is to ensure that the available resources are optimized to meet demand, achieve their capacity plan objectives, and hit those key performance indicators, all while ensuring they don't run into issues of excess capacity or poor capacity planning.

However , this year, a sudden surge in the popularity of a particular product, coupled with a viral marketing campaign, led to an unprecedented spike in online traffic. The company's website, unprepared for this surge due to its reliance on historical data, crashes during peak shopping hours and cannot satisfy customer demand. This team capacity planning strategy results in lost sales, a tarnished brand image, and dissatisfied customers.

" Wouldn't it be easy if we had resource planning software? " asked one of the project managers.

Had the company employed a more proactive approach and created a better production capacity plan by leveraging artificial intelligence and modern capacity planning tools, they could have matched the production capacity required, anticipated potential spikes in demand, and scaled their resources accordingly. This real-world scenario underscores the limitations of traditional capacity planning methods and the need for more adaptive, forward-thinking strategies.

Traditional capacity planning vs modern capacity planning is something that will often come up to debate. The traditional methods often rely on manual processes and historical data, while modern methods rely on advanced technologies, real-time analytics, and AI-driven predictive models.

While these methods have their merits, they also come with several limitations:

Time-consuming.

The process of manual capacity planning is not just a simple task that can be completed in a few minutes. It's a meticulous and detailed procedure that demands a lot of attention and dedication. IT team members often find themselves investing a considerable amount of time, sometimes spanning days or even weeks, to ensure that everything is accounted for. This extensive time commitment can divert valuable resources and manpower from other critical tasks, potentially slowing down other operations within the organization.

Error-Prone

The reliance on historical data and manual calculations isn't foolproof. While historical data provides a foundation, it doesn't always paint the full picture of future needs. Moreover, no matter how careful the individual is, manual calculations are susceptible to human error. A simple oversight or miscalculation can lead to insufficient capacity. Such errors can have significant consequences, ranging from system downtimes to potential revenue losses, and can also affect the overall user experience.

Lack of Responsiveness

Traditional capacity planning methods often operate on set parameters based on past experiences. However, the digital landscape is ever-evolving, and sudden spikes in demand or unforeseen circumstances can arise. These methods might not be agile enough to adapt quickly to such changes. Furthermore, the intricate web of interdependencies between different components of an IT infrastructure can be complex. Traditional methods might not always account for these nuances, potentially leading to bottlenecks or system inefficiencies.

Artificial Intelligence: A Game-Changer for Capacity Planning

With its ability to analyze vast amounts of data and identify patterns, AI brings a new level of sophistication to the capacity planning equation. By leveraging machine learning(ML) algorithms, artificial intelligence can monitor actual demand and predict future resource needs with remarkable accuracy, taking into account factors such as historical usage trends , seasonal variations , and business growth projections and automatically adjusting capacity requirements. As the habit is to present three capacity planning strategies, we decided to provide six and even make a capacity planning video in the future.

Strategies for Effective Capacity Planning Process

Strategies for Effective Capacity Planning Process

Leverage AI and Capacity Planning Tools

Use AI-powered capacity planning tools to create a capacity strategy plan, automate the resource planning process, and improve accuracy on the projected demand estimates. These tools can analyze large amounts of data and identify how many available resources we have or current capacity, how many resources we need or maximum capacity, or capacity requirements based on seasonal variations, and with this, it will help team members make informed decisions.

Regular Monitoring

In the realm of capacity planning, it's crucial to regularly monitor available resources. By keeping a close eye on your current capacity and how it's being utilized, you can understand usage patterns. This proactive approach allows organizations to identify potential issues before they escalate.

Scalability Planning

As businesses grow and evolve, so do their IT needs. Scalability planning ensures your IT infrastructure is prepared to handle increased demand without compromising performance. For example, an e-commerce platform might anticipate demand spikes during holiday sales. By planning for scalability, they can ensure their production capacity meets the actual demand, preventing website crashes or slow load times.

Involve Stakeholders

The capacity planning process is not a solitary endeavor. It's essential to involve all relevant stakeholders. This includes IT teams, project managers, and even end-users. By gathering insights from these team members, organizations can gain a holistic view of current issues and future needs. For instance, management might provide insights into new projects on the horizon, while end-users can highlight performance issues they're facing.

Continuous Improvement

Capacity planning isn't a one-and-done task. It's an ongoing process that requires continuous refinement. As business needs change, it's essential to review and update your capacity plan regularly. This ensures that you have enough resources to fulfill demand efficiently. For instance, if a company launches a new product line, it might need to adjust its resource planning focuses to accommodate the anticipated demand for this product.

Benefits of AI in the Capacity Planning Process

Benefits of AI in the Capacity Planning Process

At its core, effective capacity planning ensures that organizations can meet their objectives efficiently. This includes meeting customer demand, effective resource management, and ensuring that there's no excess capacity, which can lead to wasted resources and increased costs.

The benefits of capacity planning are as follows:

Predictive Analytics

AI-driven predictive analytics offers a transformative approach to capacity planning, allowing organizations to anticipate future needs based on real-time trends and intricate data analyses. Instead of relying on historical patterns or manual estimations, it analyzes current market dynamics, the supply chain, and production capacity to provide actionable insights. This proactive approach, powered by advanced resource management tools, ensures that businesses can automatically adjust their capacity plans, optimizing performance and preventing potential pitfalls. Whether efficiently allocating team members in project management, understanding the nuances of product capacity planning, or navigating the critical path of complex projects, AI stands as a beacon, guiding organizations to make informed, forward-looking decisions in their capacity planning process.

Cost Optimization

AI's precision in predicting resource requirements ensures organizations strike the right balance, avoiding the pitfalls of over-provisioning, which can lead to wasteful spending, or under-provisioning, which can disrupt operations.

By harnessing AI's predictive analytics, businesses can tailor their resource management strategies, ensuring they only invest in what's necessary. This not only streamlines operations but also translates to substantial cost savings. Whether it's adjusting production capacity, efficiently allocating team members, or making informed decisions in the supply chain, AI's role in cost optimization is undeniable, offering a smarter approach to resource allocation and financial planning.

Improved Efficiency

By leveraging AI, the entire capacity planning process becomes automated, ensuring that plans are not only developed faster but are also more accurate. This automation means that IT teams can automatically adjust capacity plans without the need for manual intervention.

With AI-driven tool capacity planning, organizations can navigate the critical path of projects more efficiently, ensuring that delivery capacity is always optimized. Furthermore, the integration of AI allows for a deeper understanding of the various types of capacity planning, from workforce capacity planning to product capacity planning. This holistic approach ensures that every facet of an organization's operations, from project management to product delivery, benefits from enhanced efficiency.

In essence, AI doesn't just improve the capacity planning process; it revolutionizes it, setting the stage for a future where capacity planning vs. traditional methods becomes a topic of the past.

Risk Mitigation

By using AI, organizations can delve into various types of capacity planning, ensuring they're equipped to handle diverse operational needs. For instance, when considering workforce capacity planning, AI tools can predict when teams might be overburdened, allowing for timely interventions. Moreover, organizations can glean insights into patterns and potential pitfalls by studying capacity planning examples from the past and analyzing them with AI. These examples serve as valuable lessons, enabling businesses to anticipate issues before they impact service delivery. In essence, AI doesn't just enhance the capacity planning process; it acts as a safeguard, ensuring that organizations are always prepared and risks are mitigated effectively.

Looking Ahead: The Future of AI in Capacity Planning

business intelligence for capacity planning

As we journey further into the digital realm, AI is not just a buzzword; it's revolutionizing when it comes to capacity planning.

AI's role in capacity management and resource capacity is becoming paramount with the latest advancements in tech, especially in machine learning. Imagine it as a futuristic tool, like a crystal ball, but instead of magic, it's powered by heaps of data, helping in project management and strategic planning.

Companies are catching on to this trend, understanding the importance of AI and using it to create a well-defined capacity plan. They realize that to meet customer demand, they need to integrate AI-driven resource management tools. This is why AI tools for capacity planning are gaining traction.

In simpler words, think of AI as the ultimate team member in your project planning squad. It's got the knack for predicting things, like increasing production capacity or understanding the supply chain's nuances. As we progress, it's evident that AI will be the cornerstone in helping businesses plan capacity, ensuring they make the right moves in the ever-evolving business landscape.

Power of AI in Capacity Planning

So, we've been chatting about how AI is shaking things up in the world of IT, especially when it comes to capacity planning to meet demand. Remember how we talked about the old-school ways of doing things and how they had hiccups? AI is here to make things smoother, smarter, and way more efficient.

In this deep dive, we've covered everything from the nitty-gritty of capacity planning to the cool tools that can help. We've also touched on why it's super important for businesses to get their planning right, especially with the digital world moving at lightning speed. And let's not forget those real-life examples that showed us how things can go sideways if we're not on top of our game.

The big takeaway?

AI is like the cool new kid on the block everyone wants on their team. It's helping businesses and project management leaders predict what they'll need in the future, making sure they're always ready to meet customer demands without breaking a sweat. And as we keep moving forward, it's clear that AI is going to be the MVP in helping businesses stay ahead of the curve.

In a nutshell, as we keep diving deeper into the digital age, AI isn't just a fancy buzzword; it's the game-changer in capacity planning. So, for anyone in IT or project management, it's time to embrace AI and see the magic unfold!

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8 Best Capacity Planning Tools: Comprehensive Comparison and Analysis

Calculating, planning and analyzing capacity is a task that requires comprehensive knowledge and lots of experience. Fortunately, there are capacity planning tools that can strengthen both these qualities and make the entire process much easier. But which tools are really worth being looked into? We analyzed the most popular softwares for capacity planning - see our comparison below!

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Arkadiusz Terpiłowski

Best capacity planning tools: 2022 ranking

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What are capacity planning tools?

Capacity planning software is a tool capable of calculating and managing employees’ maximum hourly output while taking into account all of his previous, current and future engagements, including absences, public holidays and other projects. 

Just judging by the length of the definition above it is easy to see that this process is quite troublesome and time-consuming. In fact, we agree with that evaluation of the process; in our article on how to plan and manage capacity , we explored all the possibilities and scenarios a project manager needs to cover to create an exact capacity plan. 

In short, capacity planning tools simplify the process of resource planning and make it much more bearable. 

What should a capacity planning tool have? 

Capacity planning software combines resource management with time tracking, time offs, public holidays and advanced, real-time reporting - only with all this data can they accurately calculate the capacity. 

To do that, a perfect capacity planning software should have: 

  • a flexible calendar with availability heat map, information about people allocations and their utilization level, people / project perspective, drag & drop function for quick reallocations,
  • a database of public holidays for different countries to choose from, 
  • dynamic utilization, availability and timesheets reports, 
  • time-tracking module or integration with time tracking tools (such as Jira time tracking plugins ),
  • detailed work description, including billable and non-billable hours,
  • time offs and absences (leave management),
  • information about people skills - in the best scenario CVs with experience and project history,
  • notifications for unexpected events, such as overbooking,
  • type and history of contracts with information about capacity engagement (number of hours available). 

Best capacity planning tools: ranking

We already know what a perfect capacity planning software should have - it’s time to find the one that really has it all.

Primetric offers a comprehensive approach to capacity planning, with numerous additional features at hand. However, what really makes this tool stand out is its ability to solve even the most complex problems with as much automation as physically possible. 

But let’s start with a more general picture of this capacity planning tool - how do all of these features work together, and how do they appeal to the users? 

Let’s get this straight: Primetric’s main focus, apart from the number and quality of features, is its UX. It does not matter what modules you look for; a transparent and intuitive interface with numerous guides and instructions will definitely help you find them. Additionally, should you have any doubts, Primetric’s support, as well as help center, will always welcome any inquiries. 

Well-designed interface in Primetric is accompanied by a variety of features. Those looking for an advanced capacity planning tool will be happy to hear that the software has modules for: 

  • custom public holidays, working days and time-off categories, 
  • automated calendar with public holidays for numerous regions to choose from, 
  • leave tracker with leave approval window, 
  • contract management with terms and wages, 
  • employment and contract history, 
  • comprehensive time tracking with allocations. 

Thanks to the variety of available solutions, Primetric can reflect all types of projects and billings while remaining accurate - an advantage any manager would like to have at his side. 

This list is, however, just a tip of the iceberg. That’s because Primetrics also has a number of accompanying features that, when combined with capacity planning, offer a wide range of possibilities. That includes: 

  • resource planning and skill management, 
  • project portfolio management, 
  • business intelligence, 
  • project accounting, 
  • time tracking.

As far as the integrations go, Primetric also has many virtues a potential customer can look forward to. At the moment, the system can be combined with tools such as: JIRA, Redmine, Tempo Timesheets, Teamwork, Calamari, and more. It also offers an open API for those who want to try to make their own integrations. 

All things considered, Primetric has everything a manager might need in his work - and these are not just empty words. Primetric has an average rating of 4.9/5 on both G2.com and Capterra, making it one of the best tools in his category. 

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Monday.com is one of the most popular project management tools on the market, but did you know that it has also a capacity planning feature?

The tool is undoubtedly very flexible. According to its creators, it is capable of reflecting any environment a manager can wish for by picking modules and integrations tailoring the tools to their expectations. 

However, while Monday.com can offer quite comprehensive services, they are all a part of a very chaotic environment. For a new user, it is hard to find the features one looks for, and it's even harder to arrange them in a logical manner - and customers’ opinions on the Internet confirm that. 

As far as the features for capacity planning are concerned, Monday also misses the mark. Right now, it offers features such as:

  • task management, 
  • project accounting ,
  • Gantt chart with calendar, 
  • time tracking .

However, while it is praised for its task management, Monday’s focus on a particular, short-term operation is troublesome for capacity calculations. That’s because, according to Monday’s guide, capacity management is based on estimated duration of the project and not on the availability of an employee. As a result, a resource management plan created in Monday may not reflect the real availability of resources! What is more, the actual capacity is not shown anywhere - even the official guide to the feature states that the allocations are based on manager’s assumptions. 

Apart from the features typical for capacity planning tools, Monday also offers a wide variety of resource management. However, while they are definitely useful for short-term planning, they do not provide project managers with an overview of operations. The tool is also no good for those taking pride in their analytical approach - there are no reports capable of summarizing the work in the long run. 

However, on the bright side, Monday.com definitely can be proud of its integrations. Right now, it can be connected with numerous different tools, including Outlook, Microsoft Teams, Slack, Zoom, Google Calendar, Google Drive, Zapier, Jira, and more.

Overall, Monday’s capabilities earned an average 4.6/5 grade on Capterra, and a 4.7/5 grade on G2. However, it is worth noting that the majority of these reviews come from small companies - major businesses may have to look elsewhere for their preferred capacity planning solutions. 

Mavenlink is another popular choice for managers interested in capacity planning tools. However, while it managed to get over 1400 reviews on G2, its features were barely enough to guarantee it a rating of 4.1/5. Then what is that Mavenlink lacks? 

Let’s start off with the UX. While on the first sight it may look welcoming, some customers report interface problems in some of the modules offered in the tool. Additionally, many users were bothered with its lack of flexibility - according to the online reviews, there were companies that simply could not reflect their structure properly. 

As for the capacity planning features, Mavenlink does not look any better. Its approach to capacity-related options focuses almost exclusively on reports, and not on using the data to improve resource management plans . 

For example, Mavenlink gives its users an option to check allocations by week for particular employees or the entire staff, as well as the availability and timeline with staffed and unstaffed projects. However, you cannot edit the actual data from the reports, as they are not displayed in the calendar. In other words, every change that may result from the data has to be made manually in a separate tab. 

On a bit more bright side, Mavenlink does offer a number of other tools that go well with the capacity planning software it includes. Still, project monitoring, resource management and project management available in the tool are all separated from capacity planning, making it hard to make changes. Additionally, this capacity planning tool is said to have some troubles with instant automatic updates for the data and can provide incorrect results during real-time operations!

Mavenlink is also no stranger to integrations. This capacity planning tool can be connected with popular programs, such as Slack, Jira, Asana, and more. 

However, numerous integrations were not enough to impress the users. Despite Mavenlink’s popularity, it has only achieved a 4.1 rating on both G2 and Capterra, showing that its popularity did not solve its obvious flaws. 

Wrike is a project scheduling software that added capacity management to its offer. However, is that addition enough to effectively manage executives’ problems? 

At first glance, Wrike looks like a user-friendly tool with a welcoming interface. Still, this first impression is, in this case, misleading. That’s because the multitude of options this capacity planning software has to offer makes it difficult to find necessary features. As a result, the learning curve for this tool was described as steep by numerous users who left their reviews online. 

As far as the capacity planning features are concerned, Wrike has quite a few options to offer. The tool includes: 

  • Gantt charts with employees’ workload, 
  • resource allocation system with time tracking,
  • overviews and reports for capacity and availability, 
  • team calendar. 

Still, even these quite promising features have their limitations. Users claim to have encountered some problems with allocations and project creations, making it difficult to quickly manage capacity-related processes. 

However, the biggest challenge posed by Wrike is its calendar. According to the guides to this capacity planning software, it has to be created separately for each team (even though the settings can then be used as a template). To add to that, a manager also needs to add all the holidays to the calendar manually, too, which is a big problem for planning capacity. 

Apart from strictly capacity planning tools, Wrike also offers other features a manager may find useful. That includes project portfolio management, time tracking, analytics, invoicing and to-do lists. However, many users mention that, despite having all of these features in the system, they have difficulties finding them. 

To add to that, Wrike offers a multitude of different integrations. It can be connected to JIRA, GitHub and Azure, just to name a few. However, they do not make up for the problems with accessibility we mentioned before. 

All in all, according to users, Wrike only deserves a 4.2 rating on G2 and 4.3 rating on Capterra. In other words, if you want to focus on capacity planning, it may not be the choice for you. 

Asana is well-known for its task management features. Still, can it also be used as a capacity planning tool? 

Looking at Asana for the first time, it is easy to notice that its interface tries to be user-friendly while incorporating as many features as physically possible. This goal is achieved fairly well - at least as long as the user is using this capacity planning tool on a slightly larger screen. 

Still, despite its best efforts, Asana may seem discouraging for new users. Just like in the case of Wrike, the tool tries to be a jack of all trades and fails at organizing its content in a manner accessible to an average new customer. 

UX is, naturally, not all Asana has to offer. As far as its capacity planning tools go, the software has a few features that naturally attracts people interested in the field. Those include: 

  • capacity analysis by project and specialist, 
  • drag-and-drop allocations, 
  • extended timeline. 

However, just by looking at the short list you can certainly see that Asana’s approach to capacity planning tools is unorthodox to say the least. 

Asana, as a typical task management tool, focuses on a more short-term approach instead of long-term allocations. That is why the tool puts a stress on capacity management in tasks and short allocations. Additionally, this point of view also resulted in very limited analytical features that present little to no value for the managers. 

To add to that, Asana also struggles with its Calendar view, which is critical for capacity management. Just like in Wrike, the calendars have to be created manually for each team or project, and they cannot serve as a single source of truth for the entire company. They also do not contain holidays, as they need to be added manually by the managers. As a result, this capacity planning tool is prone to human error. 

Other features do not make Asana look any better. Just like in the case of capacity planning, Asana mainly focuses on tasks and short-term planning - an offer that can surely be tempting for a small company, but not for a blooming business. While the software has time-tracking capabilities, it does not offer contract management, leave tracker, or even advanced analytics. 

Some may argue that all of the missing features can be replaced with integrations - there’s no denying Asana has plenty of them. However, these integrations may be the cause of additional costs that many businesses would like to avoid. 

To sum up, Asana may be a good choice for those looking for a task tracker, but it would disappoint managers willing to purchase a capacity planning tool. This is confirmed by more than just our opinion. Asana’s users rated the software at 4.2 on G2 and 4.3 on Capterra, leaving much to be desired for its prospective customers. 

Resource Guru

In its description on the website, Resource Guru claims to be a mixture of all the features required for quick and efficient resource management. It is, however, a different story when it comes to capacity planning. 

At first glance, Resource Guru looks simple and pleasant to use. The interface is definitely not confusing or misleading, but, compared to other tools in this ranking, it also seems empty. That is because Resource Guru focuses on resource management with little additional features, which naturally resulted in its UX being more straightforward. 

However, its specialization should make Resource Guru a master of capacity planning - at least in theory. Unfortunately, its actual features may be disappointing for those looking for a comprehensive approach. 

Right now, Resource Guru offers capacity planning tools such as: 

  • workload planning, 
  • capacity reports, 
  • Gantt charts with allocations.

Still, while the list of capacity planning tools included in Resource Guru may look somewhat promising, it quickly turns out that the software is lacking in the field. Users claim the option to add a public holiday to the calendar is very limited (which is critical information for accurate capacity planning!), 

Other features Resource Guru has are not perfect either. Apart from the capacity planning tools, the software also includes leave, project and resource management. However, some options simply weren't yet added to the system. For example, customers report that there is no bulk scheduling, repetitive tasks or visualizations that are expected from a resource management system just like this one. 

Resource Guru’s focus on resource management helped it get fairly good ratings, with 4.7 stars on G2 and 4.6 stars on Capterra. However, it is easy to notice that these opinions mostly focus on resource-related features. That is, in fact, a very telling description of Resource Guru as a capacity planning tool - while its focus on planning may seem attractive, it has only a few things to offer for those wanting to perfect the capacity processes in their business. 

Float combines resource management with task management, offering its customers a detailed perspective on short-term allocations. Still, this approach may not be a good choice for those looking for capacity planning tools. 

Let’s start with the UX. Float’s interface is not much different from other tools available on the market. What really makes it stand out from the competition is its minimalistic menu bar. However, this more modern approach to UX did not bore fruits - many users claim to have problems with finding the features they are looking for. Additionally, some users even report the stability issues that cause the software to freeze on a regular basis. 

When it comes to capacity planning, Float also has some problems. Right now, the tool offers features such as: 

  • time offs and custom working hours, 
  • real-time reporting, 
  • calendar with an option to import public holidays, 
  • team workload status.

However, despite being a quite promising set of options, these features lose quite a lot on closer acquaintances. The main issues they have include navigation - zooming in and out or changing the view from month to week was described as cumbersome for many users. 

To add to that, Float does not include many options customers expect it to have. Repetitive tasks, contract management or bulk scheduling is missing from the tool, making capacity planning much more difficult. 

However, these features on their own would still be a welcome addition to any resource management tool. However, they do not mix well with other features present that include resource scheduling and project planning. This is caused by a lack of in-depth analytics and skill management modules that are necessary for successful allocations. 

All these problems seem to be remedied by a variety of integrations Float does have. Still, as you probably know at this point, every of these integrations comes at additional cost for features you would expect to find in a single tool. 

Float’s virtues and flaws are reflected in its score on G2 and Capterra. With a rating of 4.2 and 4.5 stars, Float definitely should get some attention, but not from those looking for a capacity planning tool - in that field it requires significant improvement. 

Teamdeck describes itself as a comprehensive resource management tool that combines timesheets with project planning and budgeting. But was there a room for some capacity planning tools, too? 

In the case of Teamdeck, answering this question is not easy. That is because the system, however pleasant to the eye, is lacking stability. Loading times for the majority of sections discourages the user from analyzing the content of the tool. Repetitive pop-ups only add to this annoyance, and constant freezes fuel the irritation even more. 

Still, UX is not everything a manager looks for in a capacity planning tool. So, are the capacity planning features better? The answer is: unfortunately no. 

Teamdeck contains the following features for capacity management: 

  • time tracking, 
  • leave management, 
  • resource and project scheduling, 
  • resource utilization and workload management. 

As good as this list may look, these features still require lots of development from Teamdeck’s team. That is because they are simply cumbersome to use and sometimes generate unnecessary records that confuse many of the users that have decided to leave their review online. The same issues are also visible in other modules of the tool, including time tracking and leave management. 

However, the worst side of Teamdeck is its analytics. According to opinions of some users on Capterra and G2, the reports provided by this tool have problems with real-time updates, resulting in incorrect numbers being presented in the tables. For managers, it proved to be a challenge that’s simply impossible to overcome. 

All in all, Teamdeck is lacking as a capacity planning tool - and customers have noticed it, leaving the software with 4.3 and 4.4 starts on G2 and Capterra respectively. 

Want to know more about capacity planning tools? 

We are always here to help you! 

Feel free to read our other articles on resource and capacity planning: 

  • learn about JIRA resource management , 
  • tools for Jira timesheets ,
  • check our guide to creating a resource management plan , 
  • implement a perfect resource planning process in your organization, 
  • read more about resource management software and how it can help you, 
  • see why resource planning in project management matters, 
  • calculate the utilization rate with our guide. 

Or test our tool right away! 

Start a trial or book a demo to see what Primetric can do for you.

Arkadiusz is Head of Growth and Co-founder at Primetric. Prior to that, Arkadiusz was at the helm of his own software development company where he oversaw operations. A great enthusiast of process improvements, his personal mission is to make software companies more profitable and efficient on their path to growth.

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How AI-Powered Capacity Planning is Changing The Manufacturing Landscape – a ThroughPut Perspective

business intelligence for capacity planning

The consumer demand scene is constantly changing and when you suddenly land in a situation where your product is in great demand, it can turn into a missed opportunity if you’re not prepared.

So, how do you prepare for such an unprecedented situation? How would you determine how many resources you would need to deploy to get the order delivered? How would you allocate your resources to get the maximum output and ROI? The answer to all these questions is capacity planning.

Capacity planning helps you determine resources as a manufacturer in proportion to the output you need to generate to meet the demand.

With proper capacity planning strategies , you can determine how much raw materials, labor, equipment, and investment in facilities you’ll need over a period of time to meet future demand.

But is there a way to make capacity planning more efficient? Of course, there is! With emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML), manufacturers and businesses can mitigate various risks and impacts on the supply chain and build resilience for the future.

An effective AI-powered capacity planning tool can help you in various ways:

  • It can help you plan your manufacturing resources better and optimize your limited resources in the best possible way.
  • You can maintain a healthy balance of demand and supply in your supply chain by assessing actual capacity against realized demand.
  • It can help you optimize your production schedules by detecting and eliminating bottlenecks as they arise.
  • It allows you to revisit historical data on demand, initial inventory levels, supply-demand behavior patterns and use the knowledge of asset performance capabilities to this data.

Think you can Manage your Supply Chain Without Capacity Planning? Think again!

AI-powered capacity planning helps you achieve the right balance of demand and supply in the chain. Wondering how? Let us explain.

Customer demands today include low cost, superior quality, and instant availability of products. Advanced AI-powered tools can help you meet all the criterions through automation and augmentation.

Tools like ThroughPut’s ELI help you analyze capacity utilization by allowing you to track the capacity utilization against the actual, suggested, and available capacity for each resource category.

They help you with solutions that can boost your asset performance by providing updates about average machine performance, stable and unstable processes, current and potential operational constraints, and more.

To create a proper capacity plan in manufacturing, you will need information about how many hours in a day/week/month you’ll require these resources for production.

With a carefully designed capacity plan, you can ensure that the right people work on your project at the right time using the right equipment and deliver quality work on time.

Not just resources, AI helps you keep track of your inventory levels at all times so that you can deal with market fluctuations without breaking a sweat. With AI-powered capacity planning, you can:

  • Track, measure, and trace inventory with recommendations on when and where reallocation is possible
  • Balance demand and supply with deep insights on a mid-term and near-term range
  • Manage and match inventory availability and market demand to make smarter business decisions

Making Strides into Capacity Planning with Artificial Intelligence 

There are many reasons why traditional capacity planning methods fall apart in the current digital world. Traditional methods are manually intensive, inaccurate, and based on assumptions, and most importantly, they’re costly.

To make smarter capacity planning decisions, enterprises need accurate data that isn’t based on assumptions. 

Artificial Intelligence (AI) and advanced analytics play an important role in providing huge continuous improvements over traditional, legacy processes.

AI-driven capacity planning solutions help you decrypt relevant information to obtain appropriate insights by applying predictive analytics, data analysis, forecasting, and optimization models. 

These insights are based on legitimate data and regulated through Machine Learning (ML) algorithms. They can help enterprises make appropriate decisions on time by forecasting and putting necessary network changes in action to stay ahead of the demand curve.

AI-powered Capacity Planning – the key to a Resilient and Agile Supply Chain

AI-powered capacity planning strategies take into account all the relevant aspects of production including workforce, facilities, production schedules, budgets,  and supplies.

With these strategies, manufacturers can improve productivity and can keep a close eye on all production costs especially during periods of growth and recession.

If you think that capacity planning is only relevant to large enterprises, you may want to reconsider your opinion. Small and medium businesses also need effective capacity planning.

By automating capacity planning through AI, decision-makers can view their capacity at different operational levels and maintain a balance in the supply chain. 

Automated capacity planning offers a flexible approach and provides both local and holistic views of capacity to the enterprises.

As your capacity planning solution forecasts demand, capacity planning acts as the input for other production functions which includes demand management, aggregate planning, scheduling, and shop floor control.

Top AI Influencer & Industry Analyst, Ronald Van Loon shares key insights about “2021 AI & Supply Chain Trends and Market Insights.

Digitally Transform Capacity Planning and Always be Ready for the Unexpected

What used to be an involved process that solely relied on guesswork and assumptions earlier is now transforming into optimal manufacturing models based on standardized data and insights.

With the advent of AI, the Internet of Things (IoT), the Cloud, and other digital technologies, manufacturing capacity planning and that of the entire supply chain management has undergone tremendous change.

  • From making short-term decisions about staffing to making long-term capital decisions, digital technologies have made production more efficient.
  • The key to optimizing the capacity planning supply chain is to ensure that the crucial aspects of growth are taken into account. This includes keeping track of every stage of your product from raw material to the delivered product. 
  • Sometimes, production may need more equipment or more workforce or your customer service may need additional staff to resolve issues, purchasing may have to renegotiate existing contracts and find a new supplier, or maybe shipping would need demand forecasts. All of these factors will have to be considered while creating a capacity plan and with advanced insights, this work becomes a lot easier.
  • You can also make changes to planned production or available capacity using rough-cut capacity planning (RCCP) analysis. 
  • Monitoring production progress
  • Re-allocating resources to address bottlenecks
  • Checking task status

ThroughPut makes it easy

If you’re ready to get started on the road to manufacturing capacity planning with Artificial Intelligence, ThroughPut’s ELI is the right way to go. 

ELI gives you a detailed view of your critical resources. It helps you achieve your capacity utilization goals and minimize losses by maximizing the demand closer to real-time with the need to offset by production lead time. Here’s how ELI helps.

  • It provides you with a resource view and products view to help you keep track of your resources and product against the actual, suggested, and available capacities and quantities respectively.
  • It provides a bird’s eye view to your capacity planners, operations managers , and chief supply chain officers across the capacity levels so they can estimate the capacity of your asset load accurately, plan scheduled or unscheduled maintenance, get multi-site and multi-plant visibility for work orders, and more.
  • It also keeps you updated about inventory levels by tracking and tracing the products across the chain and assessing the change in market demand.
  • ELI works to cut your losses by maximizing the real-time demand, keeping the resource utilization under the set capacity limit.

Get the most out of your investment in AI-driven capacity planning software – ELI. Ask for a demo today and get started on the path of profits. 

AI-driven supply chain optimization software for the manufacturing industry. Schedule A Demo Now

What is Resource Capacity Planning? An Ultimate Guide for Every Project Manager

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Businesses are facing a highly competitive and volatile market demand across the globe. Since resource costs are among the most expensive entries in any organization’s balance sheet, businesses must utilize their scarce resources most efficiently for higher ROI.

Many organizations do not have a dedicated resource capacity planning tool . They have been carrying out the resource allocation and capacity planning process using their legacy systems, such as Excel spreadsheets/other home-grown applications. There are many resources, and no mechanism exists to link their work together to get enterprise-wide visibility for resources.

The Excel spreadsheets and half-baked home-grown capacity planning solutions are incredibly limiting, time-consuming, and hard to maintain. In fact, “88% of spreadsheets are difficult to maintain.” It cannot meet new business challenges.

Businesses are in desperate need of an enterprise-level futuristic resource capacity planning solution. This guide has been designed for businesses to understand enterprise resource demand and capacity planning in project management. In addition, it will help any company to establish the right processes with the tool.

But before delving into the details, let’s first understand the capacity planning definition.

What is resource capacity planning?

Resource capacity planning predicts the gap between future demand and workforce capacity to identify the shortfall/excesses of resources. Accordingly, one can develop a resource capacity plan to bridge the gap proactively for successful project delivery while ensuring every resource is optimally utilized. Thus, it becomes an essential step before resource allocation, providing all available resources before the project’s onset.

The resource capacity planning process requires centralizing information from various systems. These systems are human resources, skills, current projects, future pipeline projects, resource demand/ allocation, vacations, and non-project activities. It helps you build a single real-time system as a single source of truth.

Guide to Resource Capacity Planning

Role of resource capacity planning in project management

The resource capacity planning model plays a vital role in project management . It helps align sales and delivery by planning and forecasting pipeline opportunities. Once a pipeline project reaches a certain probability stage, the manager estimates the resource requirements and initiates the requisition process.

The corresponding resource manager then starts planning for fulfillment. But first, they need to analyze if there are sufficient resources to start the project.

The resource manager compares the existing resource capacity against the project demand from multiple perspectives such as role, department, team, skills, etc.

It helps to identify the shortages or excesses ahead of time. Accordingly, managers can apply appropriate resourcing strategies, such as hiring a permanent or contingent workforce, to bridge this gap.

Allowing sufficient lead time helps avoid last-minute hiring/firing costs and ensures that the right resources are available for projects at the right time and cost. Simultaneously, capacity resource planning helps minimize bench time proactively by facilitating on-the-job training, adjusting timelines, or selling excess capacity.

In a nutshell, resource or workforce capacity-based planning helps build an optimized project team, reduces project costs , and future-proofs the workforce against market volatilities and economic uncertainties.

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What are the key elements of resource capacity planning?

Resource capacity planning involves determining and managing the availability and capacity of resources required for project execution. It ensures appropriate resources are allocated to tasks and projects based on availability and workload capacity. The key elements of resource capacity planning include:

Identifying and categorizing resources

Managers must have complete data on the available resources in the workplace. For this, they should first establish specific categorization criteria, such as role, skills, expertise, availability, cost, etc. Following that, they can then use these criteria to group their available talent pool into different resource categories required for various project activities. This category-based grouping provides an overview of the resources at the organization’s disposal, helps assess the resource capacity, determine bottlenecks, and evaluate gaps.

Estimating resource demand

Organizations must accurately forecast and estimate the resource demand to ensure successful completion of projects. To achieve this, they must evaluate project plans, scope, and timelines to determine the specific resources required for each project activity.These resources include skills and expertise, materials, equipment, etc. In addition, they must also identify the total resources or capacity required to complete the project on time. By thoroughly assessing these factors, organizations can align their resource allocation strategies effectively and optimize the utilization of available resources.

Assessing the resource capacity

Assessing resource capacity is a critical element of resource capacity planning, which involves evaluating the organization’s ability to meet demands and requirements for resources within a specified period. Here, once project managers determine the resource demand, managers analyze the existing workforce using availability or capacity vs. Demand reports. This step helps understand whether the organization has the right number of resources with the desired skills to meet ongoing and future demands.

Capacity vs. demand gap analysis

A capacity vs demand gap analysis is key to identifying the gaps between the resources needed for future projects and the ones available within an organization. This step is vital as it helps managers check for any imbalances in capacity and demand. It involves comparing the future resource demand with the available capacity to identify shortfalls or excesses. If there are any potential gaps, managers can take corrective measures to bridge them to ensure uninterrupted project execution and improve overall billability.

Now that we know the various components, let’s understand the importance of capacity planning for firms.

Read More: Beat Market Volatility With Efficient Resource Capacity Planning

What are the business benefits of resource capacity planning?

Resource capacity planning helps businesses plan pipeline projects and futureproof the workforce against ongoing market volatility. Here are some of the advantages of resource capacity planning for your business:

Reduces project resource costs across the enterprise

Capacity planning helps forecast the skill demand precisely and arrange the requisite personnel. It:

  • Reduces last-minute expensive hiring measures to fulfill sudden demands
  • Helps avoid unnecessary overhead costs and frequent hiring/firing cycles.
  • Allows for the allocation of resources to tasks based on the available capacity, preventing double booking, burnout, and unplanned attrition.
  • Eliminates under/over-skilled resources on projects
  • Utilizes cost-effective global resources without compromising quality
  • Minimizes hiring/firing cycles by aligning project workload with workforce capacity
  • Avoids double booking of resources and minimize burn rate
  • Controls unplanned attrition of resources

Read More: Reduce Resourcing Cost by 10-30% with Modern Resource Management Solution

Maximizes productive utilization of every resource

Billable resource utilization is a critical KPI for a professional service business to ensure profitability and sustainability. Capacity planning helps balance the availability of resources with the project demand to prevent under/overallocation to minimize idle time, billing losses, and work overload.

Additionally, it allows for forecasting billable and strategic utilization of the workforce ahead of time. Based on that, managers can mobilize employees from non-billable or low-priority work to billable or high-priority projects to tap into their maximum potential and enhance profitability.

Ensures competent resource allocation for successful project execution

Having the right-skilled employees available at the right costs is crucial for a project to finish within the budgeted time and cost. Capacity planning enables resource planning and management to identify and allocate competent resources to each project based on their skills, experience, qualifications, location, team, resource cost rate, and other defined criteria.

It, thus, helps implement the “best-visible-best-fit” instead of the “first-visible-first-fit” approach to distribute tasks evenly based on resources’ ability and capacity. It, therefore, prevents work overload, schedule overruns, and contributes to timely project completion.

Forecasts and bridges the skills gap

Capacity planning helps identify skill shortages or excess ahead of time and take several corrective actions to eliminate them. For example, managers can:

  • Readjust project start and end dates to align with the available capacity.
  • Hire a contingent workforce for short-term requirements
  • Retrain and upskill employees to prepare them for future projects.
  • Bring forward some initiatives to meet strategic goals in case resources are in excess to optimize bench size.
  • Mobilize resources across several departments to maximize utilization and increase profitability.

Aligns sales and delivery by forecasting pipeline opportunities

Capacity planning helps consider the forecasted and actual deals a company wins to estimate the resources ahead of time. It also allows the delivery team to coordinate with the sales team to evaluate and determine the feasibility of the sales pipeline opportunities based on the project’s resource requirements and the client’s expectations.

Accordingly, the delivery team can forward-plan and ensure the right resources are available at the right time to finish the project. It also helps prevent the ‘overcommit and underdeliver’ trap often arising from sales-delivery misalignment to ensure timely project initiation and enhance client satisfaction.

Once the benefits of resource capacity planning are clear, let’s move on to learn some of the best methods of resource capacity planning.

Best practices of resource capacity planning

Resource capacity planning in project management is becoming increasingly critical for a business to reduce resourcing costs and become responsive to the market. As a result, resource capacity planning has gone beyond the basics of measuring workforce demand against capacity.

Here are some key strategies to implement capacity planning efficiently in your firm

Forecast capacity vs. demand and form a project resource plan in advance

A business must forecast capacity vs. demand from multiple dimensions, i.e., by role, department, team, location, skills, etc. It helps identify short- or long-term shortages/excess of resources. This enables the managers to implement the right resourcing treatments to bridge the gap.

For instance, in case of shortages, organizations can facilitate re-training/upskilling resources, or hiring a permanent/contingent workforce to avoid last-minute hiring/firing costs. Conversely, when the resources are in excess, managers can either bring forward project timeline or sell extra capacity to optimize resource utilization and ensure successful project delivery.

Track and analyze the competency matrix in real-time

Tracking and keeping up-to-date information about the workforce competencies and skills is critical. It allows the right resource with skill, experience, qualifications, individual preferences, etc., to be allocated to the proper work.

It helps plan a new project that may need a niche skill that is difficult to get from the market. If such a capability is available within the organization, the resource can be outrotated with a suitable backfill candidate. It, thus, helps initiate the new high-priority project on time without disrupting the ongoing one.

Manage project pipeline efficiently

The system should keep track of future potential projects in the pipeline and forecast estimated resource demand. It will ensure the resource pool is optimally balanced, skilled, and ready to meet the demands of new projects.

Managers can decide whether to re-skill, hire, or have contingency resources to do the work. They can also assess the pipeline project demands to determine whether they are one-off or recurring to create an optimal mix of permanent and contingent resources and overcome budget constraints.

Read More: Project Resource Management: An Ultimate Guide on How to Master it

Predict and improve overall resource utilization

The system should provide short- or long-term billable, strategic, and overall utilization forecasting. If resources are underutilized, managers can bring forward some project timelines or sell excess capacity to optimize their utilization.

If resources are overutilized, they can adjust projects’ timelines to match the future availability, pull in additional team members, or initiate a planned or project-specific hiring as required. This way, managers can take proactive measures to ensure optimal utilization levels of the workforce.

Foresee project vacancies and people on the bench

Failure to find the right resources for the right project can cause you to lose an opportunity. Therefore, the system should give you foresight into future resource needs and people who will end up on the bench.

It helps resource managers mix and match available people against project vacancies to avoid increased idle time and billing losses as repercussions. Not just that, robust capacity planning measures also help ensure all the projects are staffed with the right-skilled resources and ensure their successful execution.

Streamline resource requisition to deliver projects on time

Conventionally, resource requisition and allocations are done through email or phone requests that cause chaos. The reason is that it leads to silos of information regarding resource requests and allocations across various projects. Therefore, a resource may be booked for multiple projects beyond their capacity.

It can cause not only burnout but also power conflicts among project managers for similar-skilled resources. Therefore, streamlining the process using workflow is critical to ensure resources are allocated with appropriate approvals and notifications. In addition, one must avoid unnecessary emails/telephone calls as they cannot be easily reconciled, documented, and analyzed later.

Read More: Resource Forecasting Guide for Project Managers

These are some effective strategies businesses can adopt for resource capacity planning. Let’s look into the effect of resource capacity planning on utilization.

How does resource capacity planning affect utilization?

Achieving high utilization rates relies on the efficient movement of team members across tasks and projects, minimizing unnecessary downtime. Successful resource capacity planning is vital in aligning resources, their skills, and project demands. By implementing effective resource capacity planning, companies can experience increased utilization rates that remain strong over time.

Additionally, it is also crucial to continually implement capacity planning strategies, learn from past projects, and build a comprehensive catalog of employee skills. This continuous improvement approach enhances planning and resource allocation, resulting in a positive impact on utilization rates. Ultimately, the goal is to reach a utilization percentage that maintains profitability while avoiding employee burnout.

Knowing how resource capacity planning impacts utilization, let’s understand how to select the right solution for effective capacity planning.

How to choose the right solution for efficient resource capacity planning?

Capacity and resource planning is a crucial part of the performance improvement of modern business. It is critical to look for a solution beyond the current spreadsheet functionalities. A business should ensure that they have robust capacity planning software that can provide the following:

The system should be scalable, configurable, and expandable

Every business is different, and so are its workforce capacity planning needs. Therefore, a business must select a scalable and configurable capacity planning tool to meet current needs and expandable to meet future business requirements. In addition, system performance must not degrade with more users using the device across the organization.

It should forecast profitability and productivity

Resource capacity planning methodology should help your business to do multi-dimensional forecasting. It will provide real-time business intelligence to improve business performance, profitability, and productivity.

It must solve the complexities of matrix organization

It must align with the matrix organization structure. Nowadays, most businesses have established a matrix organization structure to best utilize their resources. So, companies must have a capacity planning tool that aligns with matrix organization structure and associated complexities.

The solution must provide real-time BI analytics

Project demand in a real-life business environment changes every minute. So, it is crucial for resource management and capacity planning techniques to get real-time business intelligence , i.e., reports, analytics, and dashboards.

It should integrate with other applications

Most businesses have already invested in enterprise-level systems. They hold a lot of data required by a capacity planning solution, i.e., resource profile, competencies, project detail, etc. So, the resource management system must integrate seamlessly with existing applications.

Read More: How to Select the Best Resource Management Solution for your Business

In this way, organizations can choose the right capacity planning solution. So now, let’s know some ways to do resource capacity planning.

Checklist for resource capacity planning for a specific period

Here are some critical capacity planning strategies you must consider while managing capacity and demand for projects.

Forecast & calculate workforce capacity

  • Take an inventory of your organization’s full-time, part-time, contractor, or freelance resources.
  • Include resources who will be joining or leaving during this period
  • Assign calendar (Workweek and Holiday list) to your resources if they are working at different locations
  • Track the skills and competencies of the selected resources

Establish project portfolio

  • List all the current and future projects
  • List all the potential opportunities which are in the pipeline
  • Account for non-project activities like BAU, Support Maintenance, Administrative Work, Training, etc.
  • Categorize the projects into Billable, Strategic, and Non-Billable Projects
  • Prioritize your projects for a better Capacity Planning process

Read More: A Quick Guide to Product Portfolio Management

Forecast resource demand

  • Get foresight into the resource requirements of the pipeline projects
  • Identify the competent resources and their availability during the same timeline
  • Prioritize the demand as per the criticality of each project and their subsequent tasks

Compare resource demand against capacity

  • Analyze Resource Capacity versus Demand
  • Identify the Gap between Resource Capacity and Demand
  • Identify skill shortages or excesses, if any.
  • Plan on how to bridge the gap of shortfall of resources ahead of time

Allocate resources to the appropriate projects

  • Assign the right resources to the right Project. Avoid allocating over-skilled or under-skilled resources
  • Allocate generic resources or placeholders on future Projects
  • Create estimates using placeholders for your Opportunities
  • Record resources unavailable time, i.e., People going on Leave, training, etc.
  • Implement the right resource optimization technique to avoid employee burnout

These are a few techniques to be considered for managing project capacity and demand.

Resource capacity planning is a crucial aspect of project resource management. By leveraging the functionalities of advanced capacity planning tools, businesses can use their resources more effectively. In addition, it also helps in reducing resourcing costs, eliminating reactive hiring, and futureproofing their workforce against market volatility.

Get Futuristic Resource Management Software

Read More: Glossary of Resource Workforce Planning, Scheduling and Management

The SAVIOM Solution

SAVIOM is the market leader in providing an Enterprise Resource Capacity Planning solution. With over 20 years of experience leading the market, Saviom is actively used by over 15 highly esteemed global companies worldwide. The tools within the suite include project portfolio management, professional service automation, and workforce planning software . Re-engineer operational efficiency with a system shaped around your business!

The Ultimate Guide to an Efficient Resource Management

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Home › Data Engineering › AI Capacity Planning: Optimizing Performance and Scalability 

AI Capacity Planning: Optimizing Performance and Scalability 

Written by: Sudeshna Ghosh

In today’s dynamic manufacturing environment, leveraging Artificial Intelligence (AI) and Machine Learning (ML) for capacity planning is becoming increasingly pivotal for manufacturers. This innovative approach allows enterprises to comprehensively assess their operations, encompassing vital elements like schedules, workforce management, raw materials, and budgets. By integrating AI capacity planning into their strategies, manufacturers can optimize productivity, effectively manage production costs, and ensure resilience, particularly in the face of economic fluctuations.

This discourse delves into the transformative impact of AI on traditional manufacturing paradigms. It illuminates how AI equips manufacturers with predictive capabilities, streamlining processes, and a competitive edge, thereby cementing its status as an indispensable component in today’s ever-evolving market. Additionally, AI-driven capacity planning or production capacity planning fosters strategic foresight, enabling manufacturers to align their operations with consumer demand and navigate the intricacies of the supply chain seamlessly. This integration of statistical and machine learning algorithms into the capacity planning process not only enhances resource management but also fortifies IT operations and enterprise infrastructure. Through intuitive UI portals, manufacturers can harness the power of AI to make informed decisions and drive efficiency across their manufacturing resources, ushering in a new era of agile and adaptive manufacturing.

Book a demo to experience the meaningful insights we derive from data through our ai capacity planning analytical tools and platform capabilities. Schedule a demo today! 

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Importance of scaling AI in manufacturing Operations 

The significance of scaling Artificial Intelligence (AI) within manufacturing operations cannot be overstated in today’s rapidly evolving landscape. As consumer demand continues to fluctuate, manufacturers face the challenge of optimizing their production processes while effectively managing resources such as raw materials and costs. In this context, leveraging AI and Machine Learning (ML) becomes paramount for strategic capacity planning, resource management, and supply chain optimization. This introduction will delve into the critical role of scaling AI in manufacturing operations, exploring how it enhances predictive capabilities, resilience, and overall efficiency within the supply chain and enterprise infrastructure. By embracing AI-driven solutions, manufacturers can effectively navigate complexities, streamline operations, and gain a competitive edge in the market. Additionally, the integration of statistical algorithms and machine learning algorithms into IT operations and capacity planning processes further strengthens manufacturers’ capabilities to adapt to changing market dynamics and optimize their manufacturing resources. Through intuitive UI portals, manufacturers can harness the power of AI to make informed decisions and drive efficiency across their manufacturing resources, ushering in a new era of agile and adaptive manufacturing.

ai capacity planning

1. Leveraging AI for Predictive and Efficient Production Planning

The integration of AI into production planning represents a pivotal advancement in manufacturing. Leveraging historical data and external market influences, AI tools alongside machine learning algorithms facilitate precise predictions of future demand. Such foresight plays a critical role in enabling manufacturers to fine-tune inventory levels, minimize holding costs, and adeptly respond to customer demands. This innovative approach transcends traditional methodologies, empowering enterprises to optimize manufacturing resources and enhance their enterprise infrastructure. Through strategic capacity planning guided by AI-driven insights, businesses can efficiently allocate resources, streamline IT operations, and bolster IT management practices. Additionally, UI portals tailored to accommodate statistical algorithms provide user-friendly interfaces for seamless data analysis and decision-making processes. In essence, AI’s integration revolutionizes resource management in manufacturing, paving the way for heightened operational efficiency and sustainable growth.

2. Optimization and Streamlining with AI-Generated Plans

AI-generated prebuilt capacity and production plans leverage advanced statistical and machine learning algorithms to optimize manufacturing resources efficiently. By integrating with enterprise infrastructure and IT management systems, these plans offer seamless integration into existing workflows, enhancing operational efficiency across the board.

UI portals provide intuitive interfaces for stakeholders to interact with data, facilitating informed decision-making and real-time adjustments. Statistical algorithms analyze historical data and market trends to forecast demand accurately, while machine learning algorithms refine these predictions over time, adapting to changing market conditions.

Capacity planning, coupled with resource management, enables organizations to allocate resources effectively, ensuring that production meets demand without overstretching resources or causing bottlenecks. Strategic capacity planning takes into account long-term business goals and market projections, aligning production capabilities with future growth opportunities.

Overall, AI-driven capacity planning empowers businesses to optimize their manufacturing processes, streamline IT operations, and maintain a competitive edge in today’s fast-paced market landscape.

3. Proactive Disruption Management

AI brings transformative benefits to manufacturing by proactively identifying and mitigating potential disruptions. Predictive analytics, a key feature of AI, can anticipate equipment failures, allowing for timely preventive maintenance and avoiding costly downtime. This predictive approach extends the asset lifecycle, reduces maintenance costs, and bolsters operational efficiency.

In a nutshell, the imperative of scaling Artificial Intelligence (AI) in manufacturing operations is undeniable, given its transformative potential in enhancing efficiency, resilience, and competitiveness. By leveraging AI and Machine Learning (ML), manufacturers can effectively navigate the complexities of fluctuating consumer demand and optimize their production processes and resources, including raw materials and workforce management. Strategic capacity planning, empowered by AI-driven predictive capabilities and statistical algorithms, enables manufacturers to adapt swiftly to evolving market dynamics while ensuring cost-effectiveness and operational agility. Furthermore, the integration of AI into IT operations and enterprise infrastructure, facilitated by intuitive UI portals, fosters a seamless and adaptive manufacturing environment. As manufacturers embrace AI-driven solutions, they position themselves to thrive in an increasingly competitive landscape, driving innovation and sustainable growth in the manufacturing industry.

Experience the advantages firsthand by testing a customized complimentary pilot designed to address your specific capacity planning requirements. Pilot studies are non-committal in nature. 

Challenges in Manufacturing Without AI Capacity Planning

Manufacturing without AI capacity planning poses formidable challenges across various fronts, including forecasting, optimization, resource allocation, demand management, and integration of the Internet of Things (IoT). Traditional methods struggle to predict demand accurately, leading to overproduction or missed opportunities. Without AI-driven optimization models, efficiency remains suboptimal, hindering adaptation to market dynamics. Inefficient resource allocation and lack of legitimate data exacerbate these issues, while IoT integration remains underutilized. Aggregate planning also suffers, impacting production schedules and resource utilization. Output variability further complicates matters, necessitating flexible strategies. Embracing AI capacity planning is essential for manufacturers aiming to navigate modern complexities and achieve sustainable growth.

1. Navigating Demand Prediction Complexities and Market Shifts

Even with AI assistance, predicting future demand remains a complex task, susceptible to unpredictable market shifts. This unpredictability can render forecasts less accurate, leading to challenges in aligning production with fluctuating demand. Without a robust AI system, manufacturers may face issues like overstocking or underutilization of resources, impacting cost efficiency and market responsiveness.

2. The Need for Robust Data Management and Real-Time Adaptation

Accurate integration of historical data with market variables demands a strong data collection and management system, often necessitating significant investments. Generating contingency plans and adapting to complex production dynamics require a deep understanding of manufacturing processes and real-time operational adjustments.

3. Human Oversight in AI-Driven Capacity Management

While AI and automation enhance efficiency, human intervention remains essential for contextual understanding and nuanced decision-making. Human oversight in validating AI-generated recommendations ensures a balanced approach, considering factors beyond data, such as market trends and strategic considerations. This synergy between AI’s predictive capabilities and human judgment minimizes costly errors and optimizes capacity planning.

Get started with your complimentary trial today and delve into our platform without any obligations. Explore our wide range of customized, consumption driven analytical solutions services built across the analytical maturity levels. 

In conclusion, the integration of AI capacity planning is not just advantageous but imperative for modern manufacturing. With the dynamic nature of consumer demands and market fluctuations, traditional methods fall short in providing accurate demand forecasts and efficient resource allocation. By leveraging optimization models driven by AI algorithms, manufacturers can streamline operations, minimize waste, and maximize output. Additionally, the utilization of legitimate data and IoT integration enables real-time insights and informed decision-making, essential for staying competitive in the industry.

Moreover, the challenges extend beyond the factory floor. From purchasing and shipping to production lead time and multi-site visibility, effective capacity planning impacts every aspect of the supply chain. Advanced tools like rough-cut capacity planning (RCCP) analysis and set capacity limits facilitate efficient resource management and scheduling, ensuring smooth operations across workstations and plants.

Furthermore, embracing technologies such as Cloud, DevOps, and Algorithmic analysis offers unprecedented scalability and agility. With features like compute instances, virtual networks, and management APIs, manufacturers can optimize infrastructure utilization and enhance operational efficiency. Leveraging reserved instance discounts and avoiding overprovisioned storage ensures cost-effectiveness without compromising performance.

In the face of unforeseen challenges, such as forensic incident analysis, capacity planners armed with AI-driven tools can swiftly adapt and mitigate disruptions. The synergy between advanced analytics and human expertise enables proactive decision-making and continuous improvement.

In essence, the future of manufacturing lies in the convergence of AI-driven technologies and human ingenuity. By embracing AI and harnessing the power of data-driven insights, manufacturers can navigate complexities, drive innovation, and achieve sustainable growth in an ever-evolving landscape.

Key Benefits of AI Capacity Planning in Manufacturing

In today’s dynamic manufacturing landscape, the integration of Artificial Intelligence (AI) capacity planning stands as a pivotal strategy for optimizing operational efficiency and ensuring competitiveness. This introduction explores the key benefits of AI capacity planning in manufacturing, shedding light on how it revolutionizes traditional approaches by harnessing predictive capabilities, statistical algorithms, and strategic foresight. By leveraging AI-driven solutions, manufacturers can effectively manage fluctuating consumer demand, streamline resource allocation, and enhance resilience within their supply chain and enterprise infrastructure. This discourse will delve into the transformative impact of AI capacity planning, elucidating its role in driving innovation, cost-effectiveness, and sustainable growth in the manufacturing sector.

Transformative Advantages of AI-Driven Strategies

In today’s rapidly evolving technological landscape, the integration of Artificial Intelligence (AI) driven strategies stands as a pivotal force driving transformative advantages across various sectors. This introduction explores the profound impact of AI-driven strategies, leveraging a comprehensive set of terms ranging from telemetry data to strategic capacity planning. Through the utilization of machine learning algorithms and statistical-probabilistic techniques, organizations are equipped with predictive capabilities that enable them to anticipate and adapt to dynamic market demands. Furthermore, AI-driven strategies facilitate efficient IT operations and capacity planning processes, optimizing resource allocation and enhancing overall performance. From root-cause analysis to the creation of insightful data visualizations, these strategies empower decision-makers to gain valuable insights into their operations, enabling proactive decision-making and fostering innovation. As organizations embark on their journey towards digital transformation, the adoption of AI-driven strategies emerges as a cornerstone for achieving sustainable growth and competitive advantage in today’s data-driven world. AI Capacity Planning is revolutionizing the manufacturing industry by offering three core benefits:

  • Automated Demand Prediction : AI’s sophisticated data analysis capabilities enable manufacturers to accurately forecast demand. This automation minimizes overproduction and shortages, aligning production more closely with market needs.
  • Reduction in Material Waste : By fine-tuning production based on precise demand forecasts, AI significantly reduces material waste. This not only optimizes asset load and work orders but also contributes to sustainability initiatives.
  • Optimal Portfolio Management : AI-generated optimal portfolio plans align production capacities with market demand. This ensures operational efficiency, reduces downtime, and supports a lean manufacturing approach.

Consistent and Continuous Production Lines

Integrating AI in resource capacity planning is vital for a retail company to effectively manage fluctuating sales demands. By analyzing customer demand patterns and employing AI algorithms, the company can optimize server capacity and compute environments according to changing demand trends. This proactive approach transcends the limitations of traditional capacity planning by facilitating swift capacity adjustments based on application performance and evolving instance types.

A well-defined capacity strategy driven by AI ensures that expenditures are optimized through financial prudence. By aligning production levels with demand forecasts, the company can minimize unnecessary costs while maintaining high application performance. This approach not only enhances operational efficiency but also improves overall resource planning.

In conclusion, the integration of AI in resource capacity planning empowers organizations to adapt swiftly to changing market dynamics while maximizing efficiency and reducing costs.

ai capacity planning

The Transformative Impact of AI Capacity Planning in Manufacturing

The integration of Artificial Intelligence (AI) capacity planning represents a monumental shift in the manufacturing sector, ushering in a new era of efficiency and adaptability. This introduction will explore the transformative impact of AI capacity planning on manufacturing processes, highlighting its ability to leverage advanced technologies and predictive capabilities to revolutionize traditional methods. By harnessing a combination of Machine Learning (ML) algorithms, statistical-probabilistic algorithms, and simulation algorithms, AI capacity planning enables manufacturers to analyze telemetry data from their physical IT infrastructure and compute environments. Through strategic predictive capabilities, organizations can optimize resource allocation, identify capacity requirements, and proactively address potential security intrusions and performance issues. Additionally, AI facilitates the creation of data visualization dashboards, providing insights into baseline norms and capacity adjustments across hybrid environments. As manufacturers embrace AI-driven solutions, they gain a competitive edge in managing underutilized resources, optimizing cloud object stores, and leveraging high-performance computing for enhanced operational efficiency. With the support of AI Ops vendors and infrastructure management software, manufacturers can streamline their IT operations, ensuring agile responses to market demands and driving continuous improvement in the manufacturing landscape. Key aspects of this transformation include:

Alignment with Market Needs: Automated demand prediction allows manufacturers to produce in line with actual market requirements, reducing the likelihood of overproduction and shortages. This not only enhances brand image by demonstrating responsiveness to customer demands but also fosters stronger relationships with stakeholders.

Sustainability and Resource Optimization: The reduction of material waste through AI’s precision not only conserves resources but also aligns manufacturing practices with sustainability goals. By leveraging resource planning software and modern capacity planning techniques, manufacturers can mitigate environmental impact while maintaining operational efficiency.

Enhanced Operational Productivity: AI-driven optimal portfolio plans ensure that manufacturing processes are both efficient and responsive, reducing downtime and enhancing productivity. This eliminates the time-consuming and error-prone nature of manual capacity planning, enabling quicker project planning and greater adaptability to changing demands. Additionally, it addresses the lack of responsiveness inherent in traditional methods, ensuring that production capacity plans are aligned with market needs.

In unison, these advantages culminate in streamlined, cost-effective, and environmentally conscious manufacturing operations. AI Capacity Planning empowers manufacturers to navigate the ever-changing global market landscape confidently, leveraging predictive insights to inform strategic decision-making and achieve operational excellence. By integrating Artificial Intelligence (AI) and Machine Learning (ML) algorithms, manufacturers can optimize processes, ensuring that production aligns precisely with consumer demand and minimizes missed opportunities. Additionally, AI-driven capacity planning enables manufacturers to identify and mitigate bottlenecks within the supply chain, enhancing resilience and adaptability to market fluctuations. Through accurate data analysis and advanced analytics, manufacturers can optimize resource utilization, improve inventory availability, and meet market demand efficiently. This proactive approach not only enhances Return on Investment (ROI) but also fosters a proactive and sustainable approach to manufacturing, ensuring the long-term success of enterprises across various industries and operational levels.

Conclusion:

In conclusion, AI capacity planning emerges as an indispensable strategy for manufacturers seeking to optimize performance and scalability in the ever-evolving business landscape. By integrating Artificial Intelligence (AI) and Machine Learning (ML) algorithms, manufacturers can strategically align their production capacities with the dynamic fluctuations of consumer demand, thereby minimizing missed opportunities and maximizing Return on Investment (ROI). This proactive approach, supported by accurate data analysis and advanced analytics, enables manufacturers to anticipate market fluctuations, optimize production schedules, and identify bottlenecks within the supply chain. Through strategic resource management, manufacturers can enhance resilience and adaptability, ensuring optimal utilization of manufacturing resources and minimizing service disruptions. Moreover, the integration of AI-powered capacity planning tools facilitates continuous improvement and scalability planning, empowering decision-makers to navigate the complexities of the digital world and drive efficiency across operational levels. As the future of AI in capacity planning unfolds, it promises to revolutionize traditional approaches, offering innovative solutions to the intricacies of production capacity planning and resource allocation. With AI-driven predictive models and monitoring capabilities, manufacturers can make informed decisions, enhance performance, and thrive in a competitive business landscape, thereby ensuring the success and sustainability of their enterprises.

What is AI Capacity Planning?

Why is capacity planning important in ai projects, what factors should be considered in ai capacity planning, how do i estimate the computing resources needed for an ai project, are there any tools or frameworks available for ai capacity planning, how can i optimize resource allocation in ai capacity planning, recent posts.

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AI-Driven Capacity Planning Software

Scope potential projects in your pipeline, connect those projects to required resources and leverage AI staffing suggestions.

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Only hire when you need to

Save hiring costs by anticipating future resourcing needs. Scope out the resources you’ll need to deliver a project, and view the team’s capacity in one place to avoid over-hiring or double-booking.

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Bring predictability into resource planning

Get a more realistic estimation of your future resource needs by leveraging a project’s win probability, based on data in your CRM, in the capacity overview.

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Streamline your planning process

Eliminate manual work and ditch the spreadsheets with an all-in-one solution. Scope out the resources you’ll need to deliver a project with placeholders. Tentatively book or request resources for a project and get staffing recommendations from our built-in AI. 

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Win clients with confidence

Set your team up for success by understanding what you can actually deliver and when. Appropriately set expectations with clients, and ensure successful delivery of your projects by knowing you have the people to make them happen. 

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Retrieve utilization reports on-demand

Run reports to get a birds-eye view of the entire portfolio and make top-level strategic decisions with ease. Easily see overall work utilization and billability in order to drive efficiency.

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Putting the power of AI to work for you

Our advance AI technology enables intelligent recommendations so you can be more proactive.

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Predictable execution, financial control, integrate your tech stack.

The AI-driven platform that brings all your data together to streamline projects, resources and financials.

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"Forecast has combined a lot of formerly disparate processes in one single platform. Schedule & Timesheets in total have saved us 15-20% admin time per week."

business intelligence for capacity planning

Using Forecast my team has become far more profitable

Capacity Planning for Business Intelligence Applications: Approaches and Methodologies

An ibm red books publication.

Note: This is publication is now archived. For reference only.

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Published on 15 November 2000 , updated 13 December 2000

  • .PDF (2.4 MB)

ISBN-10: 0738418994 ISBN-13: 9780738418995 IBM Form #: SG24-5689-00

Authors: Seungrahn Hahn, M.H. Ann Jackson, Bruce Kabath, Ashraf Kamel, Caryn Meyers, Ana Rivera Matias, Merrilee Osterhoudt and Gary Robinson

Businesses of all sizes are recognizing the powerful effect that data analysis can have on decision-making, resulting in the increasing deployment of Business Intelligence (BI) applications and solutions. This IBM Redbooks publication contains approaches and methodologies that help you do capacity planning for the system resources that support BI applications accessing DB2 on OS/390.

Written for S/390 capacity planners, it includes the following:

A discussion of the fundamental concepts of BI environments

A structured methodology for doing a capacity plan for the S/390 BI hardware and software infrastructure

A detailed description of how experienced capacity planners can modify traditional S/390 capacity planning techniques to address the unique characteristics of BI environments

A set of worksheets to help you and your team members develop a S/390 BI infrastructure capacity plan

This book addresses capacity planning for the S/390 Business Intelligence infrastructure, which includes processors, memory, I/O subsystems and DASD; it does not address capacity planning of network or non-S/390 hardware platforms.

Table of Contents

Chapter 1. Introduction to capacity planning

Chapter 2. Resource usage attributes of a query workload

Chapter 3. Data maintenance

Chapter 4. Characterization of existing workloads

Chapter 5. Establishing current system usage

Chapter 6. Growing existing workloads

Chapter 7. Sizing methodologies for new applications

Chapter 8. Estimating model size for IBM DB2 OLAP Server

Chapter 9. Sizing IM for Data for performance

Appendix A. Sample worksheets

Appendix B. Data models

Appendix C. Data Propagator Relational( DPropR)

Appendix D. Capture ratios

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How to create a capacity planning model

Carla Vianna

Your attraction can’t afford to guess when it comes to knowing the right amount of staff and equipment to invest in.

Capacity planning removes the “guessing” out of one of the most important areas of running your business: determining the resources you need to meet your current guest demand. In this case, resources are your tour guides, activity equipment, and venue.

For example, a kayaking tour company needs to know how many kayaks and tour guides it needs to run its tours smoothly. To figure this out, the company needs to find out if it has the right amount of equipment and staff to run its tours.

During this process, the company will also be able to predict how these needs might change in the future.

In this guide, you’ll learn how to create a capacity planning model to ensure you always have the right amount of resources to meet customer demand — even as it fluctuates.

  • What is a capacity planning model?
  • Long term vs. short-term capacity planning
  • What goes into a capacity planning model?

How often should you do capacity planning?

5 best practices for building capacity planning models, 1. analyze your existing capacity, 2. understand overall demand, 3. forecast capacity needs, 4. prioritize areas to allocate resources, 5. identify bottlenecks, what is a capacity planning model .

A capacity planning model is used to determine and predict your future staffing and equipment needs. This involves predicting the fluctuations in booking volume, such as an influx of guests during the busy summer months.

When your company has insufficient capacity, you won’t be able to meet customer demand. This means guests might need to add their name to a waitlist or come back to try and visit another day when you have enough staff and equipment to accommodate them. This can clearly result in lost business and revenue for your attraction.

At the other end of the spectrum, if your attraction hires too many employees without enough booking volume to sustain them, then you’ll have extra fixed costs.

Most companies use one of three capacity planning models to avoid either one of these scenarios.

1. Lag Strategy: Many businesses like to stay on the safe side when it comes to capacity planning. With the lag model, a company only increases capacity when there’s an actual demand for it.

Rather than anticipate a rise in booking volume over time, an attraction would continue operating at or near 100% capacity — as in, its equipment and staff are all booked — until it can no longer meet guest demand.

Pros: The lag strategy cuts down the risk of hiring extra staff you don’t need.

Cons: When you’re operating at or near 100% capacity, you run the risk of overworking your staff. 

2. Lead Strategy: Other companies take a much more aggressive approach. The lead capacity planning model involves an upfront investment in more equipment or staff. This is based on the assumption that booking volume is going to increase.

Pros: Your company will have the resources needed to cover an influx of bookings and tours. 

Cons: If your booking volume remains the same, you’ll have an excess of labor or equipment that isn’t used to its full capacity. You may need to do layoffs or sell excess equipment at a steep discount.

3. Match Strategy: The match model adds capacity in small amounts based on real-time demand. Under this strategy, a tour operator would closely monitor its resources and hire a new guide when its current workforce becomes overwhelmed.

Pros: It is less risk-averse and gives attractions room to grow.

Cons: This strategy can be more difficult to accomplish than others.

Long term vs. short-term capacity planning 

Capacity planning involves both short-term and long-term considerations. 

Short-term capacity planning focuses on the seasonal and irregular fluctuations you might see in guest demand. It involves scheduling, employee shifts, and balancing resource capacities on a daily or weekly basis. Sometimes, short-term planning can extend as far out as six months.

This involves tracking capacity in real-time and adjusting your resource pool accordingly. For example, a food tour company decides to hire a few freelance tour guides once the busy summer season starts.

Long-term capacity planning, on the other hand, is the process through which a company prepares for future growth and expansion. This requires forecasting, which will allow you to define new capacity requirements. 

Understanding your current resource pool and utilization will give you a better understanding of what needs to be done before adding new tours or expanding to new markets.

What goes into a capacity planning model? 

Here’s a step-by-step guide for approaching your capacity planning process the right way.

  • Identify the key resources that need to be measured. If you’re an escape game operator, your company’s ability to meet guest demand will depend on the number of escape rooms and staff you have available. A walking tour company, on the other hand, would focus on tour guide schedules to ensure there are enough working hours to match its tour volume.
  • Measure the performance and utilization of your current resources. For the escape room, this would involve looking at the capacity utilization of its rooms. Once the company finds out how often its rooms are being used compared to how often they’re available, it’ll have a better idea if its current space is meeting guest demand. If the company’s escape rooms are under 100% capacity, then it still has room to grow.
  • Forecast anticipated demand and determine your new capacity requirements. At this point, you’ll have a solid understanding of where your company stands in terms of capacity and resource utilization. But do you know if your current staff, equipment, and/or space will be able to meet future guest demand? Statistical analysis can help you predict fluctuations in booking volume. 
  • Plan how to align capacity with anticipated demand. Now you can plan for the additional capacity that would be required to accommodate more guests. If you’re following the lead strategy, you’d start investing in new resources today to accommodate an expected rise in demand. Under the lag model, however, you’d continue running your business with your current capacity until you have no choice but to invest in more resources or lose bookings.

Most companies have typically performed a formal capacity planning exercise once a year . Yet the level of uncertainty and fluctuations in demand in today’s market has transformed it into an ongoing planning process, especially since the pandemic. 

Since capacity planning provides your company with data that helps you determine how and when to hire staff, companies that continuously track their resource capabilities can be more proactive to changes in demand.

Business owners and top stakeholders conduct capacity planning to ensure that the company has enough resources to fulfill its main objectives. Meanwhile, resource managers focus on having the right staffing and equipment resources for day-to-day operations.

Before you start building your capacity planning model, consider the following tips.

Is your current team and equipment meeting guest demand? Analyzing your existing capacity is key to the capacity planning process. How many hours are your tour guides actually able to dedicate to your tours? When you’re calculating this, consider the administrative work or transactional activities like checking email or attending meetings they have to do. You want to get a realistic view of your teams’ capacity.

Take a deep dive into your company data to learn more about guest demand. Pay attention to fluctuations in booking volume and when they happen. Business intelligence tools can help you make sense of this data by highlighting booking trends and overall demand over time. Your guest demand will inherently impact your capacity needs, so it’s important to get a good handle on your current numbers.

Predictive analytics can look at historic data to help you forecast long-term guest demand. This will help you determine if you need to hire more staff, keep things as-is, or decline your capacity. This will help you avoid overspending on resources you don’t need.

It helps to think about the areas you want to focus on before making hiring decisions. Does your company want to expand its tour offerings or focus on its marketing strategy? Depending on your answer, you’d make different staffing decisions.

Where do delays occur? You can identify bottlenecks by closely monitoring your resource utilization. Perhaps an employee is forgetting to complete a key part of their role as a tour guide. This is causing friction for the rest of the tours happening that day. After further investigation, you find that this employee is overloaded with work. You then know that you might need to adjust guide schedules or increase your capacity.

Don’t make your resource planning a guessing game: Use the strategies in this guide to build a capacity planning model for your attraction.

Writer Carla Vianna

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business intelligence for capacity planning

How to Create a Business Intelligence Plan

boy-with-glasses-thumb-up.jpg

Business intelligence boils down to one thing: squeezing your data sources for actionable insights. This is a real challenge today. Enterprises have more data at their fingertips than ever before. You can track, monitor, and visualize just about anything—from financial figures to web traffic—and this glut of information has actually made it harder, not easier, to make good business decisions.

Deciding what data to track and how to use it can be daunting, and without a good BI plan you can end up spinning your wheels and wasting a lot of time. Here are a few tips on how to make a coherent plan.

Assess the Business Intelligence Tools You Have.

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Before building a plan from scratch, think about the BI you have in place. What data are you tracking and why are you tracking it? Which indicators will give you the greatest understanding of your organization’s health and trends that will impact the future? Which useful indicators are you not tracking right now? Considering where your BI plan is today will help you to see how far you have to go.

C-Suite Should Spearhead the Plan, Not IT.

This may come as a shock to some people, but putting a business intelligence plan together is a task that belongs at the C-level, not IT.

Even though setup and management of data sources is a technical process, and IT will likely handle the implementation, the planning and development phase should be managed by an executive who has a big picture understanding of organizational objectives and which insights will help you succeed. Once the BI plan is deployed, this person should also help other stakeholders learn how to get what they need from the data.

Limit Your KPIs

Key performance indicators (KPIs) are "key" because they are exceptional. You can track a lot of indicators, but KPIs are the VIPs - the important pieces of data people need to do their jobs better.

You may already have an idea of what your KPIs are, but if you don't, take a look at your corporate mission, strategy, and objectives, and determine which metrics are most critical to measuring performance. Just remember to limit your KPIs to only the most important items on the list. If you get too granular with your focus, you risk diluting the valuable story they tell. That will make it harder to get the insights you are looking for.

Use a Data Visualization Tool Like Microsoft Power BI 

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Implementing the right business intelligence software can make your overall strategy more effective and easier to manage. Microsoft Power BI is a premium cloud-based business analytics suite that collects raw data from multiple sources and turns it into easy-to-read, highly actionable visualizations.

Power BI offers several advantages over other enterprise analytics solutions:

Integration With Office 365

Part of Microsoft’s ever-growing Office 365 suite, Power BI is integrated with software your employees are likely already using, like Excel.

Affordable Pricing

Microsoft currently offers two versions of Power BI, the basic free software and the paid pro version . The differences between the two include greater capacity and more frequent data refreshes in the pro version, and if your needs exceed the free version, you will find a paid subscription pretty reasonable at $12 per month/user. 

Sharing and Governance

One of the most powerful features of Power BI is the control over how information is shared. Of course you can access and share reports on any device, but you can also segment the users based on information you want them to see. For instance, you might want to share only certain metrics within a report to vendors and other outside entities. Power BI allows you to set permissions on what data can be accessed by whom.

Like most aspects of a dynamic business today, managing a business intelligence plan is a process that never ends. The best way to begin is to start small and scale your strategy as the company evolves. And by using tools that allow you to instantly understand and act on trends the data conveys, you can finally stop going blind on spreadsheets and get some real work done. 

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How To Do Capacity Planning For Your Agency In 4 Steps

Post Author - Jitesh Patil

Resource capacity planning is the process of determining the amount of a resource you need to meet demand. 

For agency and consultancy owners, this means balancing your team’s capacity with the amount of work you expect to come in. 

In this article, you’ll learn how to do capacity planning for your agency to deliver projects on time without overworking your team.

Why is capacity planning important for agencies?

By doing resource capacity planning, you can avoid overbooking your team, missing deadlines, and losing clients. It’s similar to resource planning but at the agency level.

Avoid overbooking your team 

When you don’t have enough capacity to handle your work, you risk missing deadlines and disappointing clients. This can damage your agency’s reputation and make it difficult to win new business.

Optimize resource spend

By understanding how much work your team can handle, you can avoid hiring too many people or overpaying for resources that you don’t need. This can free up your budget to invest in other business areas, such as marketing or product development.

Make better hiring and firing decisions 

By understanding the actual demand, you can make better decisions about when to hire new team members. Similarly, you can let go of employees who are no longer needed. This can help you keep your costs down and ensure you have the right people in the right roles.

Improve customer service

You can set realistic client expectations when you know how much work your team can handle. This can help to avoid surprises and keep your clients happy.

How to do capacity planning

There are four steps to capacity planning:

  • Identify available capacity. This includes your team members, their skills, availability, and other resources, such as software licenses, hardware, and office space.
  • Estimate demand. Estimating demand includes the number of projects you expect to take on, the amount of work involved in each project, and the deadlines for each project.
  • Match resources to demand. This involves ensuring you have enough available resources to meet your services’ demand.
  • Monitor capacity and make adjustments. This means regularly reviewing your capacity plan and making changes as your business grows or needs change.

Step 1: Identify available capacity

The first step in capacity planning is to identify your resource capacity. 

What are resources?

Resources include your team members, their skills, and availability. In addition, you also want to consider other resources, such as software licenses, hardware, and office space.

To identify your team’s capacity, you can create a resource planning spreadsheet that lists their names, skills, and availability. But spreadsheets are not ideal for capacity planning. They’re error-prone and lack collaborative features.

So what’s the solution?

Consider using a resource management tool to track your team’s workload and availability.

Team timelines in Toggl Plan make it easy to see a team member’s availability and workload. 

business intelligence for capacity planning

If you’re a large agency, you can create multiple Team timelines to organize your team members by skill. For example, a web design agency could create Team timelines for designers, writers, developers, etc.

In addition, you can also mark your team’s time off to know their true availability.

For other resources, simply list software licenses, hardware, and other tools necessary to deliver your services. 

Step 2: Estimate demand

The next step in capacity planning is to estimate work demand. 

This includes the number of projects you expect to take on, the amount of work involved in each project, and the deadlines for each project.

How do you look into the future?

Talk to your clients and prospects to understand their needs.

Then, to estimate customer demand, you can look at your past projects and use that information to project future demand. 

Toggl Track’s summary reports give you an overview of your team’s tracked time. You see the time your team tracks over the last 90 days, 12 months, or year. 

Summary Report in Toggl Track

Looking at this past data can help you forecast demand for the near future. 

Once you estimate your demand, you can match available resources to your demand.

Step 3: Match resources to the demand

The third step in capacity planning is to match available resources to the estimated demand.

There are three types of capacity planning strategies to meet the demand for your services.

How to implement a capacity strategy?

A capacity planning tool can help you track available team members, estimate demand, and ensure you have enough people to meet the forecasted demand.

Toggl Plan’s Availability Overview panel shows each team member’s availability during a specific period.

( Note that the Availability Overview feature is currently being developed and coming soon.)

Visualize your team's availability using Toggl Plan's team timelines and availability panel

This makes identifying available resources, allocating projects, and assigning tasks a breeze. 

Top tips to enlarge those brains

If adding new capacity is a challenge, look at your underutilized team members. Then, identify opportunities to upskill and re-skill them to fulfill the demand.

Step 4: Monitor capacity and make adjustments

The fourth and final step in capacity planning is to monitor your team’s capacity and adjust as needed. 

This involves regularly reviewing your agency’s capacity utilization rate and deciding to hire more people or increase demand.

How do you do that?

The Availability Overview panel in the Team timeline of Toggl Plan makes it simple to see a team member’s workload in a week, month, quarter, or a custom start and end date range.

(Note that the Availability Overview feature is being developed and is coming soon. )

Monitor your team's workload and adjust your capacity plans accordingly

If your employees are consistently overworked, you may need to hire more people or outsource some of your work. 

On the other hand, if they consistently have free capacity, you may need to find ways to increase your demand, such as marketing your services more aggressively or expanding into new markets.

It is important to remember that capacity planning is an ongoing process. As your business grows and capacity requirements change, you must revisit your capacity plan and adjust as needed.

Capacity planning challenges

Agencies face several challenges when it comes to capacity planning. The biggest ones include:

Manual process

Many agencies still use manual processes or spreadsheets for capacity planning. 

Why is this a problem?

These Excel sheets are rarely updated in real time. As a result, your capacity planning process can be time-consuming and error-prone.

Lack of visibility into resource planning

Agencies often don’t have a clear overview of their resources’ use. This can make it difficult to identify bottlenecks and ensure efficient use of resources.

Inaccurate demand forecasting

Agencies struggle to forecast demand for their services. 

Why does this happen?

Sometimes it’s because of a lack of experience. But mostly, it’s because agencies don’t track their past work. 

Inaccurate forecasts result in either overbooking or underbooking. Both can have negative consequences, i.e., burnt-out employees or lost margins.

Lack of buy-in

Capacity management often gets the lowest priority among all agency business processes. 

Why’s that? 

That’s because it’s seen as an administrative rather than a strategic task. As a result, it’s difficult to get buy-in from stakeholders whose decisions are critical to ensure efficient resource planning.

Capacity planning tips for agency owners and managers

Use capacity planning tools.

Capacity planning tools help you calculate, manage and monitor resource capacity requirements accurately and efficiently. Alternatively, you could do this manually or use Excel. But this can be time-consuming and error-prone.

Talk to your team members

Get input from your team members before creating your capacity plan. 

Your team members are the ones who do the actual work. So often, they have valuable insights into how much capacity they have and what tools and other resources they need.

Keep your capacity plans flexible

Be flexible and willing to make changes to your plan as needed. 

Things change. The sales team does exceedingly well. Old clients come up with new and urgent work. A team member becomes unavailable. 

So it is important to be able to adapt your capacity plan as needed.

Communicate the capacity plan

Communicate your capacity plan to your team members and clients. 

Your team members know what’s coming next. With clients, you set realistic expectations and avoid last-minute surprises.

Implement effective capacity management in your agency

Effective capacity planning is a critical business process for agencies. 

By doing capacity planning, you avoid overbooking your team, missing delivery deadlines, and turning-off clients.

In addition, you can optimize your resources, save money, make better decisions about hiring and firing, and improve your customer service .

If you are not already doing capacity planning, the next best time to start is today. It is a simple process that can greatly impact your business.

Capacity Planning: A Complete Guide For Agencies

Jitesh is an SEO and content specialist. He manages content projects at Toggl and loves sharing actionable tips to deliver projects profitably.

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CIO Influence

  • Business Intelligence

Why Capacity Planning Is the Next Hurdle for CIOs to Tackle in 2023

Why Capacity Planning Is the Next Hurdle for CIOs to Tackle in 2023

Companies are faced with a new set of business variables as 2023 ramps up. Most notably, organizations across industries have undergone major structural changes. Headcounts have fallen and layoffs have unfortunately been in headlines since the end of 2022.

The Bureau of Labor Statistics reports that among those that are currently unemployed, the number of people who have permanently lost their job rose by 127,000, totaling 1.4 million people in the U.S. in November 2022. It’s worth noting, for some, the opposite is also true, and scaling their businesses is the major focus.

In either set of conditions – both positive and negative – enterprise leaders need to be sure they are well attuned to all facets of their organizations, including their teams and those team members’ responsibilities. Leaders can use a well-connected enterprise architecture (EA) enabled by the right tools to better understand weaknesses, strengths and gaps in their teams, and more agilely navigate downsizing or growth.

Actionability Is the Name of the Game

One of the most valuable insights that EA can provide for the C-suite is capacity planning, which allows leadership and management to examine the availability of resources to meet the demands of the enterprise, and in this case processes and responsibilities of team members to ensure that tasks are appropriately performed or administered.

When applied to recent layoff trends, capacity planning can play a large role in keeping the downsizing responsible, respectful and tied to business strategy.

Rather than recklessly letting go entire teams or a certain percentage of headcount, capacity planning offers leadership teams visibility into individuals’ roles and responsibilities, the competencies required to perform those roles, and the capacity of the role to meet demand so they’re able to make better informed decisions. Put differently, if leadership needs to execute a layoff, they should be doing so with the most valuable information on hand so that business is not interrupted and impact is minimized.

Armed with these insights, leaders can back up their choices with vetted, data-based facts that are directly tied to strategy and business continuity or resilience. The value of capacity planning is further underscored by recent news of global companies cutting entire teams, jeopardizing the stability and compliance of the business without considering the consequences.

A well-designed EA enabled by the right tooling will show where business-critical information flows from individual to individual, preventing loss of data or knowledge when downsizing happens.

Well-designed EA also plays an important role in risk management. Risks can be avoided or mitigated by having better visualizations of key personnel and their roles. In essence, risk teams can’t protect their enterprises if they aren’t able to see the architecture of their organization. The immediate benefits of capacity planning are clear, but there are other ways that EA can help enterprises up-level the flow between employees and up to the C-suite, too.

Building Interconnectivity Between Leadership and Their Company

EA breaks down the siloed structures between leadership, employees and departments and makes everyone more operationally aware of the way their individual responsibilities drive business forward.

Capacity planning for the C-suite allows for making better decisions, but it also provides qualitative color to the respective roles that comprise an organization, the competencies needed to perform those roles as well as gap analysis to assist in the resourcing strategy. Leadership can have a “bird’s eye view” of who owns, manages and performs what processes, applications or other assets, an insight that would otherwise be impossible for those seated at the top of the enterprise. This real-time awareness can prevent tone deafness to burnout and other conditions facing staff.

Moreover, it’s critical that in the event of downsizing, the C-level is prioritizing fair workloads for their staff that remain, preventing the likelihood of teammates being overburdened and succumbing to burnout thus resulting in unplanned key personnel exodus.

From the employee perspective, capacity planning allows for better cross-organizational collaboration and employee autonomy. Team members can feel empowered in their responsibilities while having a clear vision on what projects, activities or assets others in the company are owning. EA provides team members with the ability to independently connect with others who manage resources, applications or solutions they need assistance with, improving overall communication across the organization.

Two Feet on the Ground, but Looking Ahead

Capacity planning might seem like it involves leaders poring over their screens, tracking the granular details of their workforce, but in reality, it has larger, future-facing implications for growth, too. Better enterprise responsibility mapping can point out weaknesses and gaps in infrastructure. By making use of effective tooling, leaders will have ultimate visibility into the people and processes that comprise a business, allowing for course corrections if problems arise, in both the short and long terms.

As it relates to the long-term growth of business, capacity planning can also become critical for the ability to forecast .

Leadership, once aware of gaps or weaknesses in their organization, can use that same tool as a reason to expand their bench of abilities. For example, the movement to the cloud has swept up most digital business, but if a company has no employees with cloud competencies, that jump towards progress can be difficult to land. With EA, the C-suite can model their staffing decisions before making changes, allowing for proactive planning and appropriate responses to shrinking teams, or other variables, before they happen. Capacity planning can be the bridge between strategy and execution for leaders.

While capacity planning might seem like an especially critical ability during layoffs, there is also a case to be made for its value in more positive markets. Leaders can ensure that their current teams are set up for the highest chance of success, without being overburdened and disconnected. It gives leaders the power to ask: “What is it that we truly need to achieve on our goals?” and from envisioning those objectives, initiatives are sure to follow.

[To share your insights with us, please write to [email protected]]

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11 Top Capacity Planning Software for Agency Project Managers

Margarita Aranza

June 21, 2023

If you’re starting a new project, the first question you should be asking yourself is: Do I have the adequate capacity to do this?

Capacity planning plays a key role in ensuring the smooth functioning of agencies by optimizing resource allocation, managing workloads, and maintaining productivity levels. In today’s fast-paced business environment, it can be hard to implement the right capacity planning strategy due to a number of reasons. Adopting tools and technologies has become crucial for any organization that wants to grow. Whether it’s a project management tool, a resource capacity planning tool or an all-in-one tool, there are many options to choose from and assessing your agency’s needs will help you pick the right one.

What Is Capacity Planning Software for Agencies?

We’ve already mentioned some benefits of capacity planning, but that in itself is no easy feat. That’s exactly where capacity planning solutions come into play. Capacity planning software for agencies is a solution designed to assist businesses in effectively managing and optimizing their resources. That sounds pretty straightforward, so you might wonder why you’d even want a tool like that in the first place? Effective resource capacity planning requires a lot more than just scheduling resources on projects. Resource planning tools allow agencies to forecast resource requirements, allocate work efficiently, monitor progress, and ensure that projects are completed within the specified time frame. By using such software, agencies can improve productivity, reduce bottlenecks, and achieve their business goals. In this article, we’ll explore the significance of capacity management tools for agencies and provide an overview of eleven popular tools that can help agencies streamline their operations.  

  • Hub Planner

1. Productive – One of The Best Capacity Planning Tools for Agencies

Productive is an all-in-one agency management tool that’ll help you run a profitable agency. It offers a wide variety of features that help with workforce capacity planning, meeting business demands, achieving optimal resource utilization and gaining 360-degree visibility of your agency operations. Productive is a tool meant for the entire team, from an agency CEO to designers and developers.  It’s meant to make everyone’s job easier.

With the Resource Planning feature you can make sure work is equally distributed amongst your project teams. You’ll be able to align your capacity with demand to ensure adequate capacity and achieve optimal utilization rates. You’ll be able to forecast capacity for any future projects you might have and be sure you’ll meet the capacity requirements. Learn more about capacity requirement planning (CRP) and long term capacity planning . You can also see who’s on vacation or sick leave so you’ll be able to plan accordingly.

Achieve optimal utilization with productive

The Project Management feature is able to handle complex projects, from start to finish. You can have an unlimited number of projects active and they can be broken down into tasks and to-dos that are then assigned to people that need to do them. Delivering client projects on time is of essence to any agency, so being able to track progress step-by-step is helpful.

track complex projects from start to finish with productive

Time tracking in Productive was made to be easy. There’s a built-in timer that you can start once you get to work on a specific task and it will track your time automatically. You can also do your time sheets manually at the end of the day. From a resource scheduling perspective, you can book people on specific projects for a period of time so you know who’s available and when.

Budgeting and Reporting

With Budgeting you can be sure you’re on top of your project financials. You can keep track of project budgets individually, or get a broader picture of your agency’s financial indicators.

gain valuable data with reports

Reporting let’s you create insightful reports from already available templates, but you can also customize your own reports that suit your agency’s needs. With real-time data you’ll be able to make data-driven decisions that can improve your business development.

With Productive , you can separate billable and non-billable work which makes it easier to invoice clients. You can generate invoices by tracking time on billable services and those billable hours will then be transferred to the corresponding invoice. Additional features include Docs and Sales. Productive also has active integrations with Xero, QuickBooks, Jira, Slack, Hubspot, and many more.

  • Plans start with the Essential plan at $9 per user per month, which includes essential features such as budgeting, project & task management, docs, time tracking, expense management, reporting, and time off management.
  • The Professional plan includes custom fields, recurring budgets, advanced reports, billable time approvals, and many more for $24 per user per month.
  • The Ultimate plan has everything that the Essential plan and Professional plan offer, along with the HubSpot integration, advanced forecasting, advanced custom fields, overhead calculations, and more for a custom price.
  • You can also check out the Enterprise Plan with custom pricing for companies that would include more than 50 active users per month.

You can go for a free 14-day free trial before you decide to check out a paid plan.

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2. Smartsheet – A Collaborative Capacity Planner Platform

Smartsheet is a collaborative work management platform that offers features for resource planning, task tracking, and project management. Key Features:

  • Resource allocation and forecasting
  • Gantt charts and project timelines
  • Real-time collaboration and communication
  • Reporting and analytics

SOurce: smartsheet

Smartsheet provides a user-friendly interface and allows for easy collaboration among team members. The advanced features in Smartsheet come at a higher cost, which may not be suitable for smaller agencies or agencies with limited budgets.

3. ClickUp – A Good Choice for Agencies Looking for a Resource Capacity Planning Tool

ClickUp is a project management platform that offers capacity planning features along with task management, collaboration, and automation capabilities. Key Features:

  • Resource capacity tracking and allocation
  • Customizable dashboards and workflows
  • Collaboration and communication tools
  • Time tracking and reporting

Source: clickup

ClickUp provides a wide range of integrations with other tools, enabling seamless workflow management. The learning curve for ClickUp can be pretty steep for new users, requiring a fair amount of time and effort to be able to use all of the features.

4. Wrike – A Good Resource Project Scheduling Tool

Wrike is a cloud-hosted work management platform that includes features for resource planning, project tracking, and team collaboration. It’s a good choice for those who work in the creative industry or design agencies. Key Features:

  • Resource management and capacity planning
  • Task prioritization and project scheduling
  • File sharing and document collaboration
  • Customizable project workflows

source: wrike

Wrike offers comprehensive reporting and analytics capabilities, providing valuable insights into project performance. Some users find the user interface of Wrike to be less intuitive compared to other tools, requiring additional training for team members.

5. Asana – A Good Project Management Tool With Capacity Planning Features

Asana is a popular project management software that provides capacity planning tools, task tracking, and team collaboration capabilities. Key Features:

  • Resource allocation and workload management
  • Task dependencies and milestones
  • Team communication and collaboration
  • Kanban boards and progress tracking

source: asana

Asana offers a simple and intuitive interface, making it easy for teams to get started and collaborate effectively. The reporting and analytics capabilities in Asana are relatively limited, which may be a drawback for agencies with larger teams that require in-depth project insights.

6. Parallax – A Solid Resource Capacity Planning Software

Parallax is a capacity planning software that focuses on resource allocation, scheduling, and project management for agencies. Key Features:

  • Capacity forecasting and allocation
  • Resource scheduling tool and calendar integration
  • Business intelligence and reporting
  • Team collaboration and communication

source: parallax

Parallax provides a user-friendly interface with intuitive drag-and-drop functionality, simplifying the process of resource allocation and scheduling. Some users have reported occasional glitches and technical issues with the software, which required contacting customer support for resolution.

7. monday.com – A Fair Work Management Software With Customizable Features

monday.com is a web-based collaborative capacity management software that offers a capacity planning component, project tracking, and team coordination capabilities. Key Features:

  • Resource capacity and workload management
  • Customizable project boards and task tracking

source: monday.com

monday.com provides extensive customization options, allowing agencies to tailor the platform to their specific workflow requirements. Pricing for monday.com can be relatively higher compared to other tools, making it less accessible for smaller agencies with budget limits.

8. Saviom – A Good Choice for Agencies Looking for a Capacity Management Software

Saviom is a resource scheduling software that includes resource planning features, workforce optimization, and project scheduling capabilities. Key Features:

  • Resource demand and capacity forecasting
  • Skills and competency mapping
  • Project planning and scheduling

source: saviom

Saviom offers comprehensive resource optimization capabilities, enabling agencies to align their resources with project demands effectively. The learning curve for Saviom can be steep for new users, requiring dedicated training and onboarding support.

9. Hub Planner – A Good Resource Capacity Planning Software

Hub Planner is a resource management and scheduling software that provides capacity planning tools, resource tracking, and team collaboration capabilities. Key Features:

  • Resource allocation and capacity forecasting
  • Interactive scheduling and calendar integration
  • Team availability management

source: hubplanner

Hub Planner offers a visually appealing and intuitive interface, making it easy for agencies to manage their resources and schedules effectively. Some users have reported occasional performance issues and slow loading times when working with larger datasets in Hub Planner.

10. Forecast – A Fair Project and Resource Management Tool

Forecast is an AI-powered project and resource management platform that includes a capacity planning component, time tracking, and collaboration capabilities. Key Features:

  • Resource forecasting and capacity management
  • Real-time business intelligence
  • AI-driven resource allocation recommendations

source: forecast

Forecast leverages AI and machine learning to provide intelligent resource recommendations, optimizing capacity planning and resource utilization. Some users find the initial setup and configuration to be time-consuming.

11. Mosaic – A Solid Resource Management Software

Mosaic is a comprehensive resource management software that offers capacity planning features, project tracking, and team collaboration capabilities. Key Features:

  • Skills and competency tracking
  • Task assignment and progress tracking

source: mosaic

Mosaic provides robust reporting capabilities, offering detailed insights into resource utilization, project progress, and team performance. The user interface of Mosaic may appear overwhelming for new users, requiring time and effort to become familiar with the software.

Capacity planning software is a great choice for agencies looking to optimize resource allocation, streamline project management, and achieve optimal business performance. The planning software that we mentioned in this article offer a range of features that capacity planning, but it’s important for agencies to consider their specific needs such as IT capacity planning and choose a tool that aligns with their requirements and budget. By implementing effective capacity planning software, agencies can improve productivity, decision-making, and deliver successful projects on time. If you’re looking for an all-in-one tool that has powerful features and is able to handle advanced planning, complex project management and provide accurate forecasting, you might want to book a demo with Productive.

What is Capacity Planning Software? Capacity planning software refers to a set of tools and applications that aid organizations in estimating, managing, and allocating their resources effectively. These software solutions typically have key features like resource forecasting, workload balancing, team collaboration, and reporting capabilities. By using a planning software, organizations can optimize their resource utilization, make informed decisions, and enhance overall operational efficiency. Can Jira do capacity planning?  Yes, Jira can be extended with various plugins and add-ons that enable capacity planning features. Plugins like Tempo Planner and Advanced Roadmaps for Jira provide capacity planning functionalities within the Jira ecosystem. How do you do capacity planning in Excel?  While Excel is not specifically designed for capacity planning, it can be utilized with certain formulas and functions to create basic capacity planning spreadsheets. You can use Excel to track resource availability, calculate capacity utilization, and visualize resource allocation using graphs or charts. Does SAP have capacity planning?  Yes, SAP offers capacity planning capabilities through its various enterprise resource planning solutions. SAP ERP systems, such as SAP S/4HANA and SAP Business One, provide modules and functionalities for capacity planning, enabling organizations to optimize resource allocation and manage production capacities efficiently. How to do agile capacity planning?  Agile capacity planning involves estimating the team’s capacity to take on work during an iteration or sprint. It typically includes considering factors like team velocity, individual availability, and any external dependencies. Agile capacity planning can be done by reviewing historical data, conducting team capacity discussions, and factoring in any upcoming leave or holidays. What are the eight steps in the capacity planning process?

  • Understand Business Objectives: Align capacity planning goals with the agency’s overall business objectives.
  • Gather Historical Data: Collect and analyze past performance data to identify capacity patterns and trends.
  • Forecast Demand: Predict future demand based on market trends, customer needs, and historical data.
  • Assess Current Capacity: Evaluate the agency’s existing capacity and identify any gaps or constraints.
  • Identify Resource Requirements: Determine the resources and skills needed to meet projected demand.
  • Allocate Resources: Assign resources to projects or tasks based on availability, skills, and priorities.
  • Monitor and Adjust: Continuously track resource utilization and adjust allocations as needed.
  • Review and Improve: Regularly review capacity planning processes, identify areas for improvement, and implement changes to enhance efficiency.

What are the five capacity management strategies?

  • Demand Forecasting: Predicting future demand to anticipate resource requirements accurately.
  • Resource Optimization: Maximizing resource utilization by balancing workloads and ensuring optimal allocation.
  • Scalability Planning: Preparing for growth by evaluating and expanding capacity as needed.
  • Risk Management: Identifying potential bottlenecks and mitigating risks to maintain smooth operations.
  • Performance Monitoring: Continuously tracking and analyzing capacity metrics to identify areas for improvement and make informed decisions.

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Trudeau announces $2.4 billion for AI-related investments

Spending commitment unveiled sunday latest in string of pre-budget announcements.

business intelligence for capacity planning

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The Liberal government is setting aside $2.4 billion in its upcoming budget to build capacity in artificial intelligence, Prime Minister Justin Trudeau announced Sunday.

The bulk of that — $2 billion — is going into a fund that will aim to provide access to computing capabilities and technical infrastructure.

Trudeau made the announcement in Montreal as part of a pre-budget tour.

He said the federal government will begin consulting with industry soon on a new AI Compute Access Fund and an accompanying strategy to expand the sector in Canada.

"We want to help companies adopt AI in a way that will have positive impacts for everyone," Trudeau said, adding that $200 million will go toward boosting the adoption of AI in sectors like agriculture, health care and clean technology.

  • With 'superhuman' artificial intelligence looming, Canada needs law now: AI pioneer
  • AI could have catastrophic consequences — is Canada ready?

The government plans to launch a $50-million AI safety institute to protect against what it calls "advanced or nefarious AI systems," and another $5.1 million will go toward an office of the AI and Data Commissioner to enforce the proposed Artificial Intelligence and Data Act.

Bill C-27 is the first federal legislation specifically aimed at artificial intelligence. It would update privacy laws and introduce new obligations for "high-impact" systems.

The proposed law has been studied at committee since September 2023.

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Artificial intelligence 'godfather' Yoshua Bengio opens up about his hopes and concerns

Innovation, Science and Industry Minister François-Philippe Champagne said Canada is a world leader in AI.

"Let's stop asking what AI will do to us, and why don't we start asking what we want AI to do for us," he said.

Latest pre-budget announcement

The Liberals have been setting up their April 16 budget with a series of campaign-style stops across the country.

Last week's announcements were focused on housing, including money to help build apartments and affordable units. Housing Minister Sean Fraser also said a full housing plan will be released ahead of budget day.

The federal Conservatives, meanwhile, have sent a letter to Trudeau outlining their demands for the fiscal plan.

Leader Pierre Poilievre's letter to Trudeau says the prime minister's "out-of-control inflationary spending" has caused interest rates to balloon and that "punishing taxes have pushed people over the edge."

He called on the government to end the price on carbon, to require cities to permit 15 per cent more home building each year as a condition for receiving federal infrastructure money and to cap its spending, committing to find equivalent savings.

  • Deluge of federal pre-budget announcements draws fire from opposition, premiers
  • Video Trudeau's pre-budget pledges target millennial, Gen Z voters

Poilievre said if those conditions are met, Conservatives will agree to support the budget.

But Trudeau fired back on Sunday: "The job of an opposition leader is to criticize the government, we get that. But it's not to fearmonger," he said.

Trudeau also insisted that Liberal policies like the price on carbon and funding to accelerate home construction do not drive inflation, adding that experts and economists are "almost unanimous" in saying so.

"Once again, Pierre Poilievre is wrong, is not listening to experts and economists," he said.

The minority government has a supply-and-confidence deal with the New Democrats that will ensure their support on budgets and other fiscal measures so long as the Liberals advance key NDP priorities, including dental care and pharmacare.

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business intelligence for capacity planning

Trudeau announces AI spending plan to bolster Canadian infrastructure, computing capacity and safety

The federal government will spend $2.4-billion to bolster access to critical artificial intelligence infrastructure, build domestic computing capacity and create safeguards against the potential downsides of AI technology, Prime Minister Justin Trudeau announced on Sunday.

The reveal was the latest in a series of near-daily pre-budget announcements, in which the government has been unveiling its spending plans ahead of the release of the full federal budget on April 16.

Canada is home to world-leading AI researchers, but in recent years the country has fallen behind in providing the infrastructure needed for the growing field, particularly the advanced computer chips crucial for building and running AI models. The shift has led many to call for more government intervention.

Although Mr. Trudeau offered few details at his announcement, which he made during a news conference in Montreal, many in the industry celebrated the promised investment. Others said past experience with government spending announcements had left them skeptical of Ottawa ’s ability to execute on the new promises.

Money to build and make accessible more computing power will make up the most significant portion of the new spending.

In a news release, the government said $2-billion will be shared between two new initiatives. One of them, an AI Compute Access Fund, is intended to give “near-term support” to the industry and researchers. The government provided no further details, but one way of providing this support could be by facilitating access to computing power from foreign tech giants. The other initiative, a Canadian AI Sovereign Compute Strategy, is intended to speed up the development of Canadian-owned and located AI infrastructure.

“Access to computational power and capital are two of the largest barriers to developing new AI models or applications,” Mr. Trudeau said.

The government did not specify how much of the $2-billion would go to access and how much would go to building domestic computing power.

A Finance Department official told The Globe and Mail the money would be spent over five years, and that more details would be released in the budget next week. The Globe is not identifying the official because they were not permitted to discuss detailed spending plans.

Mr. Trudeau’s announcement on AI spending follows more than a week of other funding announcements in areas including child care and housing, totalling tens of billions of dollars in new federal loans and spending. Until the budget is released next week, it will remain unclear how the new spending will affect the federal government’s bottom line.

Without accounting for the new spending announced so far, last year’s budget projected that the federal deficit for 2024-25 would be $35-billion. At his news conference, Mr. Trudeau was asked about his government’s spending and about Conservative Leader Pierre Poilievre’s call for the government to find a dollar of cuts for every new dollar spent.

“We’re investing responsibly,” Mr. Trudeau said, adding in French that “a confident country invests in itself, invests in its citizens, and that’s exactly what we’re doing today.”

The government’s news release said it will also spend $200-million to help accelerate AI adoption in critical sectors and help startups bring new AI technologies to market. Another $100-million will help small and medium-sized businesses scale up and increase productivity through AI, the government said, while an additional $50-million will provide new skills training for workers displaced by AI.

A further $50-million will create a new Canadian AI Safety Institute, and $5.1-million will be set aside for the enforcement of the Artificial Intelligence and Data Act, legislation aimed at regulating AI that was tabled in 2022 and has not yet passed the House of Commons.

The announcement was broadly endorsed by one of the leaders of AI research, Yoshua Bengio, whose role in developing the technology has earned him (along with two others) the nickname “godfather of AI.” He is a professor at the Université de Montréal, and founder and scientific director of Quebec’s AI institute, which is called Mila. He was among the speakers at Mr. Trudeau’s announcement.

“The government of Canada is acting responsibly and is positioning itself on the right side of history with this announcement,” Prof. Bengio said.

Speaking in French, he said such investments are critical for economic development and an essential tool for addressing national security and geopolitical challenges. Countries that don’t have AI computing infrastructure risk being left behind, he said.

He also said the Canadian Institute for Advanced Research, where he co-directs the Learning in Machines and Brains program, has been mandated to create the safety institute. The scientific questions the institute will address are existential and absolutely need to be figured out, he said.

“How do we build future AI systems that may be even surpassing human intelligence, that are also safe? That will not turn against humans? We don’t know how to do that,” Prof. Bengio said. “It’s urgent to invest in this.”

AI systems require immense computing power, and that need is expected to increase as the technology becomes more prevalent and as new applications for it are developed.

Canada is ranked fifth in the world for its AI capacity, according to the Tortoise Global AI Index , which measures countries based on a variety of factors. But when ranked on AI infrastructure alone, Canada falls to 23rd.

Some experts said they aren’t convinced Ottawa’s announcement will lead to a material improvement.

Jim Balsillie, a former co-chief executive of BlackBerry Ltd , described the plans as a good idea. But he said the government “has not demonstrated the ability to competently design or implement such investments.”

Others, including Own Innovation founder Jim Hinton, said they were concerned that the federal announcement didn’t address intellectual property issues related to AI.

Mr. Hinton, whose firm supports technology companies on intellectual property strategy, said he is skeptical of the future of the new initiative, considering the fact that past government innovation initiatives have been cancelled or postponed.

“I am afraid that this is just another announcement without execution or substance,” he said. “Call me when there are results and globally competitive Canadian AI companies at scale, or more likely, call me when the program is wildly unsuccessful.”

The Conservative Party said in a statement that it does not believe the government is competent enough to execute the announced plan.

With a report from Sean Silcoff

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Microsoft and OpenAI plan to build a $100 billion supercomputer to power artificial intelligence: report

  • Microsoft and OpenAI are working on a $100 billion supercomputer, according to The Information.
  • The project could launch as soon as 2028 as part of the companies' five-phase plan.
  • The US-based supercomputer, known as Stargate, would far exceed current computing power.

Insider Today

Microsoft and OpenAI are planning an unprecedented supercomputer that uses millions of specialized server chips and could cost up to $100 billion, The Information reported this week.

The US-based supercomputer, known as "Stargate," would be the centerpiece of a five-phase plan focused on a series of supercomputer installations the companies plan to build in the next six years, the outlet reported. Stargate, which would be phase 5 of the plan, could launch as soon as 2028, people involved in the proposal told The Information.

Executives at both companies have already drawn up plans for the data center project, which would power OpenAI's artificial intelligence, according to the outlet.

A spokesperson for Microsoft declined to comment directly on the report but highlighted the company's demonstrated ability to build pioneering AI infrastructure. 

"We are always planning for the next generation of infrastructure innovations needed to continue pushing the frontier of AI capability," a representative for the company told Business Insider. 

OpenAI did not immediately respond to a request for comment from BI.

Related stories

Microsoft, which has already committed more than $13 billion to OpenAI, would likely provide funding for Stargate, per the report. OpenAI currently uses Microsoft data centers to power its generative AI system ChatGPT in exchange for Microsoft having exclusive rights to resell OpenAI's technology to its own customers.

Microsoft insiders told Business Insider earlier this month that the company's strategy has increasingly focused on its work with OpenAI , leading some to worry that Microsoft is essentially becoming an IT department for the startup. 

The supercomputer could be 100 times more expensive than the largest data centers currently in operation, per the report. The project signals the massive amount of money likely to be poured into the industry as artificial intelligence continues to evolve in the coming years.

Stargate also has the potential to far exceed the computing power currently supplied by Microsoft to OpenAI from its data centers around the country but would require at least several gigawatts of power to do so, The Information reported,

Microsoft's involvement in the project, however, hinges on OpenAI fulfilling its promise to boost its AI's capabilities , a source told the outlet.

The quest to obtain the necessary server chips is the primary factor driving Stargate's hefty price tag, according to the report. Finding enough energy sources to power the project could also pose challenges, and the two companies have talked about possibly using alternative power sources like nuclear energy , sources said.

The demand for AI chips has reached a fever pitch, allowing a select few companies — primarily Nvidia — to control the market. Altman has expressed frustration with the "brutal" situation and signaled earlier this year that he wants to make his own. 

The chip dilemna is just one of several details that still need to be ironed out with regard to Stargate. People familiar with the project told The Information that Microsoft needs to figure out how to put more GPUs into a single rack than it currently does in order to boost the chips' performance. The company also needs to find a way to prevent the chips from overheating, according to the report.

It's not clear where Stargate would be located or whether it would be built in just one data center or several nearby centers, The Information reported.

Axel Springer, Business Insider's parent company, has a global deal to allow OpenAI to train its models on its media brands' reporting.

Watch: An AI expert discusses the hardware and infrastructure needed to properly run and train AI models

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A pivot to China saved Elon Musk. It also bound him to Beijing .

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IMAGES

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