This might be more about me than you wanted to know, but guess what? The new season of Dancing with the Stars is on. My girls and I are enjoying being all snarky about outfits and physical coordination; we are jointly rooting for Evan and Nicole and I, of course, have a personal fondness for Pamela. Watching dancing that’s alternately enjoyable and gut-wrenchingly horrible naturally gets me thinking about — wait for it — forecasting and demand planning. Are most companies good at forecasting?  How would they rank as contestants on FWTS (Forecasting with the Stars)? Okay, I won’t take that one any farther.

Just the same, most of the research from the likes of AMR/Gartner indicates — and our experience at Demand Foresight certainly reinforces — the idea that the current state of forecasting and demand planning is in a state similar to a young couple learning how to dance. They might currently be focusing on spins or twirls or lifts, but it isn’t until it all comes together in fluid, integrated simpatico that it really works and makes the dancers and the audience happy.

The perfect steps
What, then, is the perfect incarnation of demand planning and forecasting?  Ideally, it would be a way of day-to-day working in which:

• Every professional within an enterprise understands that the forecast is the most important business tool to get right and use correctly.

• It would be supported by simple and straightforward processes and enabled by intelligent and helpful technology.

• It would be measured.

• It would form a large portion of compensation.

• It would be an articulated focus of the organization and its leadership in pursuit of its vision and strategy.

Unfortunately, in most enterprises, the current state of demand planning (modeling and managing the demand side of the business) falls far short of unison, confidence and grace.

For example, we as a business community don’t even know what to call it: Demand Planning? CPFR? S&OP? Forecasting? Sensing? Guessing? We discussed that in an earlier set of blogs – hopefully our definitions make sense.

Timing the steps: what are the time frames for demand planning and forecasting?
Some of the terms above and/or approaches are delineated by time frames (someone mentioned demand sensing the other day) — short-term forecasting focused on minutes, hours and days. S&OP, on the other hand, is purported to focus on mid-term time frames — 6 to 18 months out. Then, of course, there is Strategic Planning (the providence of highly paid prognosticators, researchers and people afraid of getting their hands dirty actually making something), which focuses on issues years out (minimum 18 months and longer) — capacity requirements, brands, market positioning etc.

In my mind, all of these time frames are included in a successful demand planning and forecasting dynamic.  They feed into one another and are dependent on each other.  Successful forecasting around a new product launch (very near-term forecasting: “Do consumers like this color?”) will impact strategic thinking about what new products in which to invest. Investments in capacity will drive new marketing activities, which will promote sales volume that needs to be forecasted 2 to 4 weeks out, if that capacity is domestically sited. I think you get the point: fundamentally, the process needs to include what is going to happen 10 hours from now, 10 months from now and 10 years from now — all are part of successfully integrated demand planning.

I also want to spend a little time with this oft-occurring question: what is the right view point to drive demand planning and forecasting? Sales forecasts?  Marketing forecasts? Customer forecasts?  Financial forecasts?  These are different pictures of demand based on inputs from professionals with specific responsibilities, external factors, and business requirements (“We need to have this market share or margin,” etc). The answer is not that one of these viewpoints is correct, but that each of them has value in the true picture of demand and need to be included into the process of continuously quantifying demand.  The hard question is how to include all of these points of view.

You are well aware of the appropriate technical platform for enabling this work…right? But what is best process? The best process is the one that works, the managers are willing to enforce etc. All the same stuff has been laid out in numerous books and courses through out the years. But I think there are a few other keys…

Ownership of forecast accuracy
One key we have seen is that regardless of the process, one person or group does have to own the forecast and its accuracy.  One way we have seen this work well is for each group to have its own forecast (our software happens to support multiple forecasts across an organization): sales will have a forecast, as will marketing, maybe even the customers’ forecast can be integrated, too. Then each is locked according to the process time frame, i.e., first Wednesday of the month).

Now, let’s say the planning group owns the forecast. They will perhaps host a meeting (a consensus meeting?) and get everyone to compromise enough to generate one consensus forecast that can be sent to operations and/or purchasing.  Or if planning really owns it (and is measured on it and compensated by it), they will make the decisions unilaterally.  The key is: each forecast submitted from each areas of focus can be measured against actuals to get a specific view as to forecasting accuracy.  And that will help drive future process improvements and allocation of responsibilities.

In order to keep everyone focused on the process — do not forget, this is really, really key — do not forget to have every one of the input groups, from sales to finance, have part of their compensation predicated on forecast accuracy.  There are number of ways to do this, and perhaps we will share some experiences in a future post. But the big point is to have forecast accuracy drive compensation in some form or fashion.  And this makes perfect sense if you believe in the importance of forecasting for bottom line performance and competitive advantage over time.

When this holistic version of forecasting is working well, it is like a really enjoyable dance.  When one professional from sales makes a change to a short-term forecast, they understand they are also impacting the planning group’s 13-month rolling budget view and the strategy group’s 3-year investment plan.  During the monthly forecast cycle — time should be spent 12 or 13 month out — think what this would save (time, resources) for annual planning process.

And like the beautiful, organic dance routine that the new dancers want to master, this is a goal for demand planning and forecasting in companies that are going to thrive in the future. In fact, it is imperative that everyone understands and accepts the responsibility for as accurate a forecast as possible.

This means accounting for as many time frames as possible. It means taking into account the many different perspectives within and without an organization; Utilizing the many forms of data currently available to organizations — both internal and external. It means making demand forecasting a strategic imperative within the organization, tied directly to the successful attainment of the corporate strategy and vision. And that means making sure compensation is tied to the accuracy of the execution level forecast. And by the way, the technical platform to enable this is key and I happen to know a solution that can enable this nicely.

P.S. Go, Pamela!