There is a famous anecdote about Volvo car dealers heavily discounting green models because consumers preferred other colors. Volvo’s manufacturing plant, seeing the resulting spike in demand for green models, perceived it as consumer interest and upped the production. That’s right…even more green cars!
It’s a sad story that’s often repeated, and a story that begins with a demand-shaping strategy to offload unwanted inventory. It’s a prime example of distribution planning in supply chain management and how a dealer’s {read distributor’s} behavior can create confusion and lead to unnecessary increases in a manufacturer’s inventory holdings and, by extension, the stock of its suppliers, too.
Why Forecasts Get Out of Whack: The Importance of Distribution Planning in Supply Chain Management
The problem is twofold: 1) a lack of understanding of the root cause behind an upward or downward spike in demand, and 2) the fact that the spike may be result of conditions that are unlikely to happen again. These spikes will skew forecasted demand numbers. For example:
- When a product is promoted successfully, the result is an upward spike in demand. Once the promotion has ended, there can be a temporary downward spike in demand because customers have ‘stocked up’ on the promoted item.
- Initial consumer interest in a new product will spike downward when that product does not meet expectations, or when a competitor introduces a better, cheaper alternative.
- For businesses that capture demand based on shipped quantities, a stock-out will appear as a downward spike in historical demand.
What happens is, the more the demand varies, the less accurate the demand forecasts become. And the usual response to low forecast accuracy is to increase safety stock or buffer inventories – a costly strategy, to be sure!
What Distributors Can Do About It
As demand data travels up the supply chain, distributors can (and should) help decrease the bullwhip effect of demand variations by 1) cleansing their demand data and 2) sharing it with their partners.
Because statistical forecasts are built using demand data, it is really important to cleanse demand data prior to the forecasting exercise. Cleansing the data decreases the level of demand variation from one period to another; in other words, the cleansing exercise smooths out the demand by removing spikes or outliers caused by conditions that are unlikely to reoccur.
By sharing more accurate forecasts built on clean data, distributors actually help their suppliers improve service levels. This reduces the reliance on safety stock because it brings more predictability into the supply chain. Everybody wins!
The Role of Technology
This is also where information technology plays an important role. Without the right distribution management system, data cleansing is a daunting task. Without the right technology, the sharing of data between trading partners is, while not impossible, rather improbable.
As a distributor, initiating a collaborative demand planning process is tough enough. But not doing it is worse, because without good tools to cleanse and share data, manufacturers will continue to build products based on faulty demand signals. The results will be, well…the same as if Volvo continued to make more green cars when statistics show that over 70% of the world prefer white, silver, grey or black!