Forecasting for Value

↓

​Learn more about the People Analytics course →​

Hi Friends,

As I speak with people analytics teams, I often notice that many off them get very much into the weeds and details. True, they are data professionals, but it is difficult (in my opinion) to be an effective data scientists without understanding the context.

The problem is really not the lack of expertise, but maybe it is spending too much time in details and not focusing on the true problem we are trying to solve.

This is especially evident in forecasting.

And many organizations don't really do forecasting. But when they do, they quickly get sucked into model specifications discussions, algorithms and historical parameters.

It is a technical exercise.

But the purpose of forecasting is not data modelling, is it?

It is workforce planning?

Or in other words, are we getting too caught up being in the weeds of "how" things are built, rather than focusing on what value it delivers.

And you know me, I am all about value.

Anyways...

The fundamental goal of forecasting is not to select the most complex model or fill out a planning spreadsheet to satisfy an annual milestone.

People create forecasts because they are trying to answer questions about the future:

• Can we deliver value with what we have?
• How flexible is our operating model in different scenarios?
• What trade-offs must we be prepared to make?

We need to shift forecasting conversation from details to being at the executive table and looking into the future.

Let's go to the room where it happens

At this table, leaders and board members don't audit your regression formulas or debate specifications. They simply need a framework to understand uncertainty and make strategic choices (h/t to Roger Martin).

To move from tactical model selection to strategic value creation, leaders must shift their mindset:

1. Focus on the Decision, Not the Math

A forecast has ZERO intrinsic value if it does not alter a decision or clarify a trade-off.

Before reviewing any numbers, executives should define the underlying decision:

Are we opening a new region, restructuring a function, or committing capital to long-term hiring?

If the forecast doesn't directly inform a capital or operational leverage point, what is the point of dumping resources into doing one?!

2. Evaluate Trade-offs and Variance, Not Point Estimates

Complex models often produce a single, highly specific point estimate—for instance, asserting that the company will need exactly 1,200 engineers in four years.

Haha! Don't you feel like you are in control with these numbers?

Executives need to know the range of plausible outcomes and the cost of being wrong in either direction (under-hiring vs. over-committing capital).

Remember: Scenarios, Scenarios, Scenarios.

3. Treat Forecasting as an Early-Warning Signal

Instead of viewing a forecast as a static destination to be verified years later, treat it as a dynamic monitoring system. Say, a radar.

The value of a forecast lies in establishing baseline assumptions so that when real-world market signals arrive, leadership can immediately identify what changed and reallocate resources accordingly.

After all, do you really think you can predict the future 3-4-5 years in advance?

If you did, you probably would be a billionaire by now.

Elevating the Role of People Analytics

For CHROs and People Analytics leaders, lifting the conversation means changing how work is presented to the C-suite and board.

Instead of presenting dashboards filled with model methodology, lead with business impact:

• Workforce Planning: Don't present a detailed 5-year headcount projection model. Present the financial and operational risks associated with different demand scenarios, highlighting where the business has built-in flexibility versus fixed liability.
  ​
• Skill Taxonomies: Don't get stuck in the technical taxonomy of mapping thousands of micro-skills. Frame the discussion around strategic capabilities required to defend market position or accelerate new revenue lines under varying market conditions.
  ​
• Capital Allocation: Frame talent commitments through the same lens CFOs use for capital expenditure. What is the downside risk if market conditions deteriorate, and what optionality exists to pivot without destroying organizational performance?

And yes, leave the methods for the appendix. Especially if you only have a few minutes to present.

The Financial Capital Lens

One of the key lenses that gives value to forecasts.

With this lens, remember, no self-respecting business leader evaluates capital project based only on mathematical elegance.

They evaluate the project's return on investment, sensitivity to downside risk, and alignment with strategy.

Workforce strategy requires the exact same financial discipline:

1. Define the questions, decisions, and time horizons
2. Model plausible scenarios
3. Evaluate risk, trade offs, and ROI

Stop focusing on the model, but ask yourself, why are you building it.

K

Whenever you’re ready, there are 2 ways I can help you:

#1

If you’re still looking to get started in People Analytics, I recommend starting with my affordable course:

​Practical People Analytics: Build data-driven HR programs to 10x your professional effectiveness, business impact, and career. This comprehensive course will teach you everything from building an HR dashboard for business results to driving growth through more advanced analytics (i.e., regression). Join your peers today! ​
​

#2

If you are looking for support in your human capital programs, such as engagement, retention, and compensation & benefits, and want to take a more data-driven approach, contact me at Tskhay & Associates for consulting services. Or simply reply to this email!