{ 0 comments }
Background
Demand planning always has new terms that are necessary to keep up with. Two of the present ones are demand shaping and demand sensing. I decided to include both in an article because for some time there, I would get the two confused for one another, and its important not to do as they are unrelated, except for being two terms which are currently popular.
Demand Shaping
Demand shaping is the process of creating incentives through with customers that smoothes demand, or in eliminating pre-existing incentives such as promotions or end of quarter pushes which distort the demand history making forecasting more difficult to perform.
Demand Sensing
Demand sensing is the use of a procedure to analyze the demand history in order to gain new insight as to how to develop a better forecast, and to make changes in the short term to the forecast. This entry into Wikipedia on the topic is patently ridiculous..
The typical performance of demand sensing systems reduces near-term forecast error by 30% or more compared to traditional time-series forecasting techniques. The jump in forecast accuracy helps companies manage the effects of market volatility and gain the benefits of a demand-driven supply chain, including more efficient operations, increased service levels, and a range of financial benefits including higher revenue, better profit margins, less inventory, better perfect order performance and a shorter cash-to-cash cycle time. Gartner, Inc. insight on demand sensing can be found in its report, “Supply Chain Strategy for Manufacturing Leaders: The Handbook for Becoming Demand Driven.”
This entry was clearly made by a software vendor selling demand sensing software. No forecasting methodology produces a reduction in forecast error by 30%. If the forecast error were 30%, this would mean demand sensing improved the forecast by 30 % x 30 % or 9 percentage points. I would very much like to see the hard data on those numbers. Secondly, what is near term forecasting? Forecasting is produced long term and the sales orders exceed or are short the forecast. I am not sure that “near term” forecasting is a legitimate term. If the lead time is longer than the duration of the short term forecast to sale, how to adjustments to the forecast help?
Searching for Logical Consistency
The more I read on demand sensing, the less it makes any sense. Firstly, many of the things that are often touted as part of demand sensing are should actually be performed by the normal demand planning system. Secondly, making short term changes to the forecast introduces a great deal of noise into the forecast. Forecasts need to be set, and left unchanged. Sales orders may be higher or lower than the forecast, but the forecast is a value which is to bet frozen. The entire purpose of creating a forecast is that there is a lead time, if there were no lead time, there would be no need to forecast. The entire concept of demand sensing is on very weak ground. At this point it seems to be simply a trendy term which is used to sell software rather than any substantial addition to the realm of demand planning. Secondly, in seeing demand sensing put into action at several companies, there tends to be two opinions as to whether the software is adding any value. Those with an incentive to be able to change the forecast love the idea, and those that do not complain of the constant noise demand sensing introduces. One problem I consider is what is the actual forecast that is archived? Is it the original one, the demand sensing adjusted one, one in between? This brings up more questions.
Using Them
Demand shaping is a very valuable function, however extremely few companies actually perform demand shaping. In fact the vast majority of companies perform the opposite or demand distortion. This is because the supply chain department does not control the conditions and terms or pricing that their product is offered to customers under. This is determined by sales or marketing, which generally does not give two hoots about how difficult this makes it for operations to actually fulfill the demand, or what the cost of sales is. Therefore its strange to hear so much about demand shaping, when demand distortion rules the show. So while its an important concept, there is very little chance of this occurring, so it makes not a lot of sense to continue to discuss. The topic should be passed to sales and marketing, who will promptly put the idea in the waste bin.
Conclusion
Neither of these will amount to much in the longer term. One is a great idea, but companies are positively opposed to its implementation, and actively engage in demand distortion, thinking this maximized profits and helps them meet quarterly numbers in a pinch. The other has little foundation in any logic, and seems to distract companies from improving their forecasting capability by adding an post-forecasting processor that jiggers the forecast around. Truly, there are so many opportunities to improve forecasting just in applying truly innovative technologies such as attribute based forecasting,
http://www.scmfocus.com/demandplanning/2010/07/pivot-forecasting/
or discontinuing active forecasting for unforecastable products,
http://www.scmfocus.com/demandplanning/category/pivot-forecasting/
…that its difficult to see how these two concepts are worth the effort to implement.
{ 2 comments }
