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In a related topic about resource management, James Cho outlined the main activities the Resource Management team is responsible for, briefly touching on the topic of demand/supply management. As my first blog post as TSIA’s new director of professional services research, I wanted to provide a closer look at what goes into demand/supply management, more specifically, capacity planning.

What is Capacity Planning and Why is it Important? 

In the context of professional services (PS), capacity planning is an activity the resource management office (RMO) would own, or at least help to facilitate. The goal is to have the right people with the necessary skills in place at the right time to meet your business needs.

In order to make investment decisions, knowing what the future demand will look like is a key aspect that makes capacity planning an important process for PS. It allows you to determine how many people to hire, when and where to hire, and which skillsets are necessary to meet your business objectives. 

The goal [of capacity planning] is to have the right people with the necessary skills in place at the right time to meet your business needs.

Here are some of the standard tasks/activities that should be performed as part of capacity planning:

  • Analyzing and estimating demand
  • Translating demand into capacity requirements
  • Understanding existing and planned capacity
  • Aligning supply, demand and business goals

Each of these involve a combination of science, the analysis of existing data, and art that fills in the blanks when the necessary data is not available.

Analyzing and Estimating Demand

Estimating the demand involves combining your sales opportunity pipeline and your existing delivery backlog. However, there is a lot more to establishing an accurate estimate of demand than a simple mathematical formula. The quality of the pipeline and backlog data directly impacts the precision of the demand estimate.

Let’s break it down a bit further: 

Opportunity Pipeline

Sales opportunity pipeline data from your sales tracking system, preferably from your CRM (customer relationship management) system, provides the baseline to begin estimating the demand. 

How accurate is this data? Consider the historical tendency of the pipeline being overstated, as well as situations where opportunities exist with forecasted values that are placeholders for real opportunities that haven’t materialized yet. These factors have a direct impact on estimating the PS demand.

Many companies do pipeline analysis and have quantified data that can be used to augment the demand calculation. When quality data or detailed analytics aren’t available, you are left with making an educated guess on what percentage of the pipeline is real and may be overstated.

Engagement Backlog

Engagement backlog data from your engagement tracking system, preferably from your PSA (professional services automation) system, provides the baseline to estimate the other portion of the PS demand.

Just like the pipeline data, the backlog data quality needs to be assessed. Consider the situations where certain types of engagements or certain customer engagements end early or run long. Engagement escalations also have a direct impact on the PS backlog, and thus impact the precision of demand calculation and the overall capacity plan.

Services Demand Rollup

Now, let’s consider the subtler subjective areas that may impact the quality of the PS demand rollup. It’s hard to quantify the impact of customer account rep changes, organizational changes, changes in business priorities, and even changes to the customer org or their business priorities. These potential events could impact the precision of the demand rollup.

Translate Demand into Capacity Requirements

This is one of the more challenging aspects of capacity planning. The translation of demand to capacity is a two-step process involving the estimation of the raw headcount (HC) needed to meet the demand, and developing accurate timelines for when the demand/engagements will or can be delivered.

Based on TSIA benchmark data, only a small number of companies provide resource estimates and schedules in the early opportunity phases of the sales cycle. This results in the need to translate the pipeline and backlog from currency values to raw HC. 

One of the more common methods is the use of ADR (average daily rate per delivery resource), by taking the total value of the PS demand and dividing it by ADR the result is the average man days to deliver estimated demand. Factor in average utilization and partner delivery mix, and the result is a value in terms of resource required.

The Real Challenge with Capacity Planning

Estimating the schedule for when the resources will be needed is one of the more challenging aspects of capacity planning. It relies heavily on resource and project scheduling and a fair amount of artistic insight when historical scheduling data is not available.

There are many deep analytical approaches to the forecasting of project and resource schedules, and is an area that can quickly be over-engineered. I am reminded of a phrase “perfection is the enemy of good enough,” so my recommendation is to find the calculation that is good enough for your needs.

Understand Existing and Planned Capacity

Talent and skill management activity is a key activity for resource management and is the primary source for understanding existing delivery resources and their skills. 

Human resources (HR) will also have important data to help understand existing and planned capacity. They will have details on recent hires, open requisitions, and attrition rates, along with information on how long it takes to recruit and hire specific delivery resources by role or by geography/region.  

The current health/condition of business metrics such as utilization, margin, delivery mix, and PS backlog should be as part of the alignment process working toward an overall capacity planning strategy.

Aligning Supply, Demand, and Business Goals

With the PS demand and PS supply identified as precisely as reasonably possible, the focus shifts to the business goals and objectives. The current health/condition of business metrics such as utilization, margin, delivery mix, and PS backlog should be as part of the alignment process working toward an overall capacity planning strategy. These metrics are impacted by capacity planning decisions of when and how many people to hire or not.

Next are the big picture influencers such as mergers, acquisitions, divestitures, industry trends, market changes, economic, political, and geographic changes, which all play a significant part in creating a capacity plan. Aligning supply, demand, the business goals, and the influencers is much more art than science.

Capacity Planning Conclusion and Takeaways

Capacity planning isn’t easy. To do it well involves detailed scientific analysis of all available data, as well as intuitive artistic insights into many influencers that don’t exist in datasets.

When capacity planning is done well, improvements in the overall health of the business, predictable utilization, lower attrition levels, improved margin and generally happier operations and delivery resources can be realized.

In the bigger picture, successful capacity planning facilitates a competitive advantage through reduced time-to-market for new solutions, improved growth, enabling scale, and helping the business to be more agile and respond to market changes more quickly.

TSIA benchmark and capability assessment data indicates that our members are having varying success with capacity planning. How mature are your capacity planning activities? 

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David Young

About Author David Young

David Young is the senior director of professional services research and operational best practices for TSIA. In this role, he is responsible for developing and delivering research programs that are focused on helping TSIA member organizations build and optimize professional services. He is also responsible for leading and delivering operational best practices to member organizations. David has over 25+ years of experience in technology, operations, analysis, project management, and consulting, including experience in hi-tech semi-conductor industry, software product development, program management and professional services working in large enterprise and small startup organizations.