Understanding Workforce Modeling: A Data-Driven Approach, Part 2

In my previous post, I introduced workforce models and their usefulness in workforce planning. Here are some detailed ways this may play out in various workplace categories.

With a more transactional scope, like a call center, work is usually triggered by an end user or direct customer. Positions like these tend to spend about 80% of their time in direct contact with customers or end users, resulting in bottom-up functional analysis/work service content driven models. A non-customer contact model can be useful for positions that include oversight roles for the customer-facing staff. These positions may still correlate with customers or end users, but as supervisors and managers, they are tried directly to customers, end-users or “span of control.” Workforce planning for knowledge workers, whose main work stems from knowledge, is harder but not impossible. These range from programmers and architects to physicians, pharmacists and scientists. And as variable as the roles, so are the workforce models used to build their predictions.

Business support models focus on those functions that correlated to the growth of the organization’s workforce. Examples within organizations include HR, IT, facilities, legal, finance and, in some cases, sales. These tend to grow as the size of the organization grows. While these types of models are distinct, in any department you can see more than one model being used depending on the type of work, amount of work and the functional analysis done within that department or organization.

Regardless of the category, the analytical and data driven process for developing the model is fundamentally the same: identify scope and workload factors, complete a functional analysis of the core work, through fall direct and indirect data analysis, iterate through development.

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Workforce models often reveal quick targets for focused improvement efforts and can instantly identify the impact of new workload, changing requirements and growth targets on key processes.  This gives the organization the ability to do some what-if planning. Whether the goal is to launch a new product or move into a new territory, you can plug in the forecasted increase in customers or users and see instantly the impact. For example, an employee at a health insurance company had the idea to expand a requirement for more healthcare providers to submit a certain form annually. This would take a state-level requirement impacting a small fraction of providers and expand it to 100% of all providers in the plan. It was well intended and sounded good on the surface, and the required changes to send out the forms, track their return, chase those missing, log the results and audit the form were plugged into the model. This change would have resulted in significant administrative burden on already overworked administrative staff. The resulting negative ROI made it immediately clear that the idea should be rejected.

Another common use case arises in businesses experiencing a large number of unfilled positions.  Modelling the impact on the organization if these positions remain unfilled allows you to decide what level of improvement has to be made in order to maintain the same level of productivity with the existing workforce.

Workforce planning enables quick adjustments as unexpected changes occur. The Workforce Model also provides a year-end workforce overview. If your forecasts are accurate quarter over quarter, then so is your plan. Understanding that a plan rarely unfolds seamlessly, inputting new information as it becomes available enables agility where and when necessary. As one enlightened SVP admitted, “If these are the key factors that drive my organization, I probably ought to be paying closer attention to them.”


Developing a workforce model is not for the faint of heart. It requires significant time and understanding to deconstruct the organization and put it all back together while keeping the key variables that drive work in mind. Once it’s done, you will gain immediate visibility into the workforce impact of the most important of those variables. This can be a meaningful strategic advantage in determining impacts of changing business requirements as well as new changes in the market. By making the commitment to use data that you already have or have access to, you can move your organizational decision making from abstract guesswork to informed choice.

Jeff Kahne

Jeff Kahne
Dr. Jeff Kahne, PhD, is a principal with Firefly Consulting.

Jeff Kahne

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