What is capacity management?

Capacity management often gets confused with resource management. This typically happens for two primary reasons. First, both terms sound as if they might be describing the same type of thing, although that’s not the case. Second, both terms describe activities that should occur early in an enterprise’s history, during the early conceptual planning stages.

But capacity management and resource management are not interchangeable phrases. They are sequential terms, and the sequence is important to maintain. During the planning stage, capacity management is a key planning activity—so important that it usually must precede most other considerations.

Here’s the difference between the two:

• Capacity management is a bottom-line determination that seeks to find out whether a planned enterprise will be able to conduct normal business functionality as planned.

• Resource management is the set of procedures and processes that helps establish how available resources are coordinated and the various details that govern when and how projected work gets completed.   

Capacity management touches upon aspects of resource planning and project planning but boils down its conclusions to one set of driving metrics—whether the planned enterprise will be able to process its projected allotment of workloads and execute on business requirements.

But that’s just one part of capacity management—the other part requires some prognostication in the form of forecasting future demand and how the system will accommodate such growth before that time occurs and future needs become present demands.

Before moving forward, it makes sense to delineate the different meanings of the term “capacity management” to avoid possible confusion. There are really three “magnifications” of the word, each pertaining to a specific sense of scale:

• The company view: This is the “macro” perspective of a business’s total theater of operations. This is populated by various client projects, all of them being driven by unique project management parameters, needs and timelines.

• The operational view: In the sense of operational efficiency, capacity management means resource planning and how personnel, materials and machinery are governed by the immutable laws of resource availability and resource capacity.

• The IT view: Consider this the “micro” view of the business. Here, capacity management goes “under the hood” to monitor IT resources and how to coordinate them with IT services and IT infrastructure to effectively measure data volumes.

For the purposes of this discussion, we’re considering all three levels of magnification simultaneously because that’s how business works. Everything is usually happening all at once and multiple perspectives must often be maintained concurrently.

Managing capacity is more than simply keeping an eye on storage capacity limits and making sure assets have enough room to fit. Effectively dealing with capacity issues requires implementing forecasting techniques and using data and artificial intelligence (AI) to study past projects and plan new ones. Here are the key steps involved in capacity management processes:                                   

• Measurement: Studying present resource capacity by measuring the enterprise’s total various resources and how they’re being used.

• Monitoring: Tracking resource availability, how resources are being presently used and how they’ve been leveraged in the past.

• Allocation: Prioritizing workloads and workflows and defining resource allocation, according to resource availability and pressing business demands.

• Recalibration: Repurposing the historical data from past projects to help set project expectations for current and future projects.

• Making projections: Estimating future capacity and coming demands on resources in upcoming projects is an essential part of the capacity management process.

Different organizations address their capacity management issues with various methods and strategies. The following strategies reflect multiple levels of performance management.

There are several ways that you can play the game of business capacity management. One means is by implementing a lag strategy, in which the organization adapts more of a relaxed business posture as opposed to a more proactive approach. Organizations that use a lag strategy wait to increase their capacity until demand has sufficiently grown.

In this strategy, the company doesn’t seek to engage in forecasting demand and instead waits on the solid figures indicating increased demand. This option is often chosen by companies with solid client bases, but which might be dealing with budget constraints.

For organizations wanting to pursue a more engaged and proactive approach to capacity management, there is the lead capacity strategy to consider. Here, a company will boost its production capacity in expectation of coming future demand.

The obvious benefit for the organization is that it’s better prepared to deliver on that coming demand, should it materialize as expected. An example of a commonly followed lead capacity strategy can be found in toy companies adjusting production in anticipation of the Christmas shopping season. This aggressive approach typically relies on advanced demand forecasting.

In a hybrid type of approach, the average capacity strategy seeks to occupy the middle ground between an aggressive approach (lead capacity strategy) and a reactive approach (lag strategy). Accordingly, the average capacity strategy seeks to find the capacity that will match its expected average demand.

In some ways, this can prove to be a risky strategy, although based on broad averages, this type of “balancing act” with capacity aligned with the expected level of demand should work if the company’s average estimates turn out to be reliable. The quality of the organization’s forecasting is particularly important.

The match capacity strategy is really a modification of the lead capacity strategy. The key difference is investment.

In a lead capacity strategy, the company invests in more capacity in anticipation of future demand. The match capacity strategy achieves most of the same goals without laying out large sums of money in advance. Instead, the company chooses to micromanage incoming data about actual current demand and will adjust based on those findings. The match capacity strategy depends heavily on watching emerging and evolving market trends and basing fast actions on the resulting data.

There are at least a half-dozen reasons why organizations turn to effective capacity management strategies and solutions:

• Less employee burnout: Capacity management helps limit the burnout of staff members by letting the enterprise know when it needs to hire more workers.

• Better resource utilization and allocation: Two of the key metrics that capacity management monitors are resource utilization and resource allocation. Through them, organizations can tweak performance and boost cost savings.

• Smoother inventory management: Typical supply chain issues can usually be ironed out when more effective inventory management is enabled through the thoughtful support provided by capacity management.

• A comprehensive view of human resources: By putting capacity management principles into place, businesses can derive a fuller view of company talent, including the expected capabilities and limitations of team members.

• Improved budgeting and decision-making: The goal is to make the smartest decisions possible. Capacity management supports this by enabling organizations to make data-informed decisions and craft realistic budgets.

• Heightened production efficiency: Efficiency gets an overall lift when production cycles are scheduled ahead of time with capacity planning and capacity management.

Effective capacity management finds ways to stymie some persistent challenges that can negatively affect efficiency:

• Bottlenecks: Like a traffic jam locked so tight that no vehicles can move, a bottleneck is a point of failure in which capacity dwindles to a trickle and can’t sustain demand. The results are delays in processing and interruptions to functionality. Many possible causes can be at the root of bottlenecks—most involving some type of syncing problem. For example, workloads are coming in faster than they can be absorbed properly, or some part of the process is working ahead of schedule and beyond what was determined during capacity planning. Bottleneck detection is achieved by checking resources with low-capacity utilization rates.

• Shortages: When a system’s operating capacity can’t keep pace with demand, a shortage occurs. Shortages happen for numerous reasons. First and foremost among them might be that the system simply doesn’t have sufficient capacity to meet demand. Or there might a labor shortage that compounds the situation, or a mechanical or computer problem with the machinery typically used. Similarly, a lack of raw production materials or the presence of quality fluctuations can trigger shortages. This is why companies go to great lengths to create capacity management plans and implement real-time data into their forecasting practices.

Several capacity management tools are in popular use, including the following:

• Excel: Microsoft’s flagship database program has several tools for capacity management, such as multithreading (which shortens calculation times) and memory usage optimization.

• Float: Float is a capacity planning tool that offers real-time views of staff availability, giving teams the means to workload optimization. Float automatically churns capacity calculations.

• Jira: Agile teams depend on Jira for several reasons. Jira maintains dashboards for individual users as well as team pursuits, and ensures that all stakeholders have access to team data.

• Kantata: Kantata Software deals with professional services and service management. Its database ranks team skills and provides resource suggestions for variables like pricing.

• Runn: Runn helps its users plan for projects and maintain the necessary resources to forecast resource demand, so that expected service levels can be maintained at all times.