Infosys has a compelling post entitled “What’s the right forecasting approach in the current business environment?” This is a great question in light of the volatility most businesses face today. I posted my comment on their site, but have also included it below as well.
### My comment ###
I have a few comments about the original post as well some of the follow on entries.
I do agree overall with the approaches recommended by Aatish. I think to sum it up, demand planners need to ensure that they are not relying on simply one input (the quantitative forecast driven from demand history) but rather to consider (and challenge) inputs from multiple providers including sales, marketing, product management and key customers in order to make more informed decisions. Sales forecasts tend to be more accurate in the short term while marketing forecasts tend to be more accurate further out along the curve. Working with key customers on collaborative forecasting programs can help improve the quality of the forecast because you are getting closer to the ultimate source of the demand. From experience, it’s also a great way to improve overall customer relationships because it’s often the case that the customer sees this as a value-added service that can distinguish you from other vendors.
The demand planner is the individual in the organization that is responsible for providing sober, second-thought to all of the inputs gather during the forecasting process. They typically are the only role that brings a historical perspective to the process because everyone else either has a short memory or would prefer to forget past predictions. How often has this customer backed out at the last minute or overstated the business that they thought they were going to do? What happened the last three times we ran this kind of promotion in the spring? How quickly did demand materialize the last time we introduced a new model of this product? These are all the classic types of questions that, if given the opportunity, the demand planner needs to ask when driving to a consensus of future demand and that’s just to get to ‘square-one’ i.e. what is demand going to be given what sales, marketing and customers are planning to do. The next step is to then use that information to try and shape demand in order to align it with what the business wants to do (represented by high-level management forecasts propagated down to the SKU or product level). This might mean shifting marketing focus to higher-margin products or regions, implementing specific add-on or upgrade incentives with key customers, or adding key features to a new product.
Just two final points. Aatish started off his post by saying ‘Now, when the consumer demand is extremely volatile and sentiments are down across almost all the industry segments… ‘. I would argue that the comment about extreme volatility has been the norm for quite a while now at least in high-tech and consumer electronics segments. The approaches being suggested are really becoming the minimum mandatory for companies that want to survive the operational and margin pressures faced by a lot of today manufacturers. The other key point is related to Vikram’s comment about demand planners not having the time to attend review meetings. I believe this is a symptom of the process and tools used to support the demand planning process (i.e. planners are spending too much time collecting and rationalizing data). There are tools available now that provide the ability for all participants in the process including sales, marketing, finance and even customers to simultaneously input their information into a single data model that is ‘pre-rationalized’ so that demand planners can spend more of their time actually planning.