Last time in Sales, Inventory & Operations Planning (SiOP) – Part One I talked about the Segmentation and Product Management steps of the cross-functional process of SiOP. For this blog we will discuss the Demand step.
Demand
A product launch and end-of-life happens in close collaboration with marketing or product management. Once the product is mainstream, the best information is to be found with the sales force and the channel partners.
We still find many companies that churn out empty excels where they ask the sales force to predict on a customer-product-shipto what is the expected sales 12 months out. In parallel we see that finance is asking sales for an update on the current month and the current quarter. Whereas supply chain wants to see the physical volumes, finance wants to see Euros or Dollars. Where supply chain wants to see details, finance is OK with aggregated levels like per region and product group. Living these parallel worlds is a recipe for failure (for supply chain).
Finance will get its info, as it is typically linked to the reward system of sales. Supply chain will see limited adoption and get a forecast that lacks sufficient accuracy to be of any practical use. The lack of a good forecast creates service issues, unbalanced inventories and operational firefighting costs.
There is a couple of tricks you can apply to make the (forecasting) job for sales more realistic, as such enhance the accuracy of the forecast, and at the same time ensure that all stakeholders get the info required on the level of detail and the horizon it is crucial to them.
First of all, ensure that your ground work is done by statistical techniques. Instead of providing empty excels, statistical techniques can typically help to give a first estimate. To maximize the efficiency of the statistics, it is key that you first separate your historical demand in what you can call a ‘baseline’ or ‘run-rate’ demand, and ‘events’, which could be promotions, tenders, projects, …
Separating these 2 also creates more focus towards the future. For the ‘baseline’ demand, the statistics typically hold sufficient and reliable information. The key for marketing and sales is to focus on the ‘events’, their latest status, and their expected impact. Make sure that your toolset allows this split. It reduces the workload for sales and allows them to focus on where is the most value add. Depending on the company different people might be involved in planning and follow-up of the so-called ‘events’. Ensure that your process is built to consolidate the information gathered by each of them.
A second key to keep the job ‘manageable’ for sales is to allow easy aggregation and disaggregation. If statistics provide a baseline, and they can validate the events on a detailed level (yes, the devil remains in the details). In a next step they should be able to validate on an aggregated level, in both volume and in value, to ensure finance gets the info required as well. Again, ensure that your toolset allows this. It reduces the workload for sales and ensures the financial forecast and the supply chain forecast point in the same direction.
Many companies have been working on improving the above. They may not be there, but at least there is awareness and we are confident they will be making steps. Another key opportunity is in collaborative forecasting with key customers and channel partners. When you do a ‘forecastability analysis’ you will find ‘high-volume’ products that are ‘highly erratic’. If you analyze in more detail, you will find that key customers (cfr. your segmentation) and/or channel partners are causing the variability.
Many companies share the analysis but little share the solution: collaborative forecasting. It is old knowledge that the ‘sell-out’ of your channel partners or the ‘consumption’ of your key customers is more stable than your ‘sell-in’ or ‘historical sales order pattern’.
There is only 1 way to improve service and reduce cost and inventory in this type of situations: collaborative forecasting. Instead of ‘guessing’ what these customers will buy … review it with them. It requires a significant effort, but there is no alternative. Ensure that your toolset allows you to pull-up and adjust customer specific views! It will be key in getting adoption from key account managers.
There is only 1 truth in forecasting: the forecast will always be wrong. What matters is ‘how wrong’ and ‘which steps are adding value and which are not’. Too much has been written on which forecasting KPI’s to use.
We typically use the Mean Percentage Error to measure bias, and combine it with the Mean Absolute Percentage Error to measure accuracy in the month. We tell to sales that the bias should be between +5% and -5%. On average we should be right. Targets for the MAPE depend on the product and the market. We have stopped the religious fights on how to measure the accuracy. Just make sure that you have a measurement to which everybody agrees. And ensure that your supporting toolset allows to configure your measurement that you have developed. The more relevant discussion is how to monitor which steps in the process are adding and destroying value, and feed that information back to the stakeholders.
Make sure that your toolset allows to compare the forecast accuracy of the statistical forecast, the forecast as adjusted by the account managers, the forecast as adjusted by marketing, the forecast as adjusted by the sales director … in fact measure the value add of each of the stakeholders. Reviewing and discussing the forecast value add will reveal issues like ‘over-optimistic’ marketing people, ‘sandbagging’ sales directors and or ‘too conservative’ supply chain people. Many companies are ignoring this debate or hold the debate in the corridors instead of in the demand review meetings. With the right toolset and the right reporting of the forecast value add, you can have the debate in the demand meetings and ensure it translates into improved forecast accuracy.
Last but not least we see that more and more companies are tired of the disproportionate effort going into the yearly budgeting exercise. In many companies it seems to go in endless cycles and result in a plan that is unrealistic as of the very moment it is finished. The ultimate dream is to have a rolling budget where we update our financial plan 18 months out on a monthly basis. We’ve not seen too many companies in that situation already. A first step however is ensuring the budget forecast starts from the SiOP forecast, which already aligns volumes and value. The difference between the budget and the forecast is the ambition. Ensure that your toolset allows you to work with “scenarios” or “forecast versions”.
If you want to build an “aggressive” scenario, start from the current plan, and review with sales in which customers and products they would be able to realize the extra volumes and margins. You might save that scenario for future reference. In any case you want to save the “budget scenario” as a reference for the monthly follow-up. Reporting where we are with respect to the budget, and addressing gaps both positive and negative is key in navigating your business, along the budget, towards you strategic goals. Ensure that your toolset supports this.
