Demand Planning 102: 10 Tips
Now that we have a working definition of Demand Planning (See Demand Planning 101), I’d like to offer the following Top 10 Tips to help you think more like a demand planner. Remember, demand planners have it tough. Like noble refs, they get few accolades for making lots of good calls and plenty of guff when things go awry. That’s partly understandable; inaccurate demand forecasts throw a wrench into planning and policy setting, both in-bound and out-bound. And that can have a severe financial impact.
The following tips should help you begin to think about the Demand Planning process in greater detail. Each one emphasizes one or more of the three main drivers of success (and failure): people, process, and technology. Some tips fall into all three areas.
As you read, consider each practice a measure of your organization’s supply chain maturity, especially as it pertains to Demand Planning. Know that none of the organizations we’ve come across in our work as supply chain technologists have mastered all of the Top 10 Tips, nor have any organizations completely mastered all three drivers of success. Demand Planning and other analytics-based processes are lifelong journeys of constant refinement. With that said, I offer you the following:
- Only that which gets measured, gets improved. The key performance indicators (KPIs) that your organization measures are the only business metrics that stand to improve, so choose well. If it isn’t getting measured, it isn’t getting noticed and it isn’t getting fixed.
- Garbage in, garbage out. This is a basic best-practice for any analytics-based business-intelligence process. If you can’t trust your underlying assumptions, you can’t trust the forecast. So be purposeful and engage a data-quality process that starts right at the beginning.
- Collaboration is king. Whether you’re in sales, finance, or operations, planning in a silo is a quick way to screw things up. Even if you’re using the most appropriate forecasting algorithms, there is a ton of information not yet in the data, items like upcoming promotions, or large commitments from new customers. The point is, you’ve got to harvest this knowledge and insight from colleagues across the organization and get it into the data stream.
- Manage by the numbers. Keep emotions in check, and out of the analytics process. For example, don’t get hung up on exceptions. Remember the 80/20 rule; 80 percent of revenue is generated by 20 percent of customers. This should help you identify exceptions that should not be pulled into the forecast.
- Assign owners, and watch! No one is served without a consensus understanding of the Demand Planning process, the individual and team contributors, and those responsible for reviewing and or approving changes. Above all, document this process or implement a technology platform that does it for you automatically. The point is, make sure to assign an owner for each process and make the expectations clear to all contributors.
- It’s not just what might happen, but how likely. Remember that solid Demand Plans are often the result of highly iterative simulations, which go well beyond single-point forecasts and low-medium-high scenario analyses. Monte Carlo simulation delivers a wide range of potential outcomes for each course of action, and the occurrence probability of each. Consider this a superior alternative to the low-medium-high approach. I’ve never met a decision maker who didn’t want to know the probability of his plan’s success.
- Cross-educate. As you collaborate with colleagues in sales, finance and operations, it is imperative that everyone involved understand the meaning and purpose of the Demand Plan: what it is, and what it is not. It is not, for example, the sales forecast, nor is it the budget. But it does require that all parties understand their roles in the process.
- To err is human. If there is one truth in forecasting, it’s that no forecast is 100 percent perfect. There is no perfect algorithm, and there is no perfect way to mine the knowledge and insight of your workforce. The goal is to be as close as possible.
- Reduce cycle time. The shorter the forecast cycle, the more frequent the updates, the less safety stock needed to absorb demand variability. This is fairly simple, though you need the processes and technology tools in place to get started. Once in place, you may continue to modify levels until you get the results you want.
- Invest in a best-of-breed Demand Planning platform. There are many studies out there that show that forecast-based Demand Planning solutions improve financial results across the organization. Most pay for themselves within a year. Simply put, this is better than trudging through laborious and error-prone spreadsheet processes. Choose a best-of-breed solution that improves forecast accuracy, supports custom workflows, and enables multi-team and multi-plan collaboration.