In my last post, I discussed the critical reporting and accountability burden that the Sarbanes-Oxley Act of 2002 places on companies. SOX reporting affects forecasting and financial projections, including revenue, margin and market share based on volume. How much confidence shareholders have in the management team’s control and understanding of the business can make all the difference in how they react to these quarterly “surprises.” Herein lays the opportunity for supply chain managers to play a critical role in meeting SOX requirements.
Historically, one of forecasting’s major problems has been huge inaccuracies at the execution level. Put a different way, we’re good at making general forecasts, but lousy when it comes to predicting buying patterns at the SKU level, which is right where we can have the greatest impact on the supply chain. For example, while it is important to know that we will sell 10 cars, it’s more valuable to know that five will be blue and five will be black, four will have automatic transmissions and six will have manual, etc. These are the specific details from which raw material ordering takes place, production runs are scheduled, inventory is managed and customer service levels are set and managed. Hence the term “execution-level forecast” and its importance to supply chain efficiency.
In most companies, this level of forecasting does not occur because they don’t have a system or process capable of making it work, and those that do often operate with a level of error that exceeds 50 percent when measured on an absolute basis. The frustration for operations is that they will plan production runs and inventory rates to four decimal points and then have to scratch it all because the forecast from sales and/or marketing contains more than 50 percent error at the execution level. The operations team’s response is to disregard the sales forecast and create their own; at least that way, they know where the numbers are coming from.
What does this have to do with SOX? It highlights the historical reason for the separation of data. The same phenomenon that creates a disconnect between sales and operations also occurs within the finance side of the house. Since finance doesn’t trust the forecast either, they create their own. It is not unusual for companies to create, maintain and use three different forecasts that have little, if anything, to do with one another. So, when the finance team is surprised by poor sales performance and then has to report a deviation to the Street and alter the forecast, their credibility is hurt. And squandered credibility is hard to earn back.