Demand Driven Supply Chain: No more the Holy Grail of Operations Management.

The article “Cleaning the Crystal Ball” discusses about the necessity to establish a clear forecasting mechanism to be able to plan the operations in a particular direction. The reason for forecast year after year even though they happen to be incorrect is that they lend direction in an otherwise intuition driven decision making. Now that at least we have a solid inference drawn from data analysis to base and evaluate our intuition driven decisions.

Though there is no denying in that the forecast mechanisms have to develop before they can be claimed dependable, the maturity levels attained now would be of better use if we could integrate forecasting and data analysis to the inputs of a company’s quarter on quarter strategy planning. Most companies fail to derive the complete benefits of forecasting. Objective forecasting to arrive at one or range of numbers is parallel to choosing to walk with one eye when all one has to do is open the other eye for better visibility.

No one model can actually yield best results for all the organizations. The forecasting models have to be developed from within the organization by incorporating the error quotient and monitoring the forecast against the actual results. Incorporating more factors that were not considered earlier would strengthen the forecast mechanism though at the cost of complexity. Demand forecasting in most cases leaves the team with a range of numbers. They sometimes make people see patterns that could have otherwise escaped the minds engrossed in other directions. There are reasons for this distribution of numbers, rather than focusing on the demerits and complaining about the flaws in forecast and one could benefit by accepting that the forecasting mechanism is yet to reach a level of maturity and focusing on

•    What factors influence the range positively/negatively?
•     What factors are most sensitive to output?
•     What drivers can we control/monitor to adapt to the situation?
•     What are the key indicators for us to focus on to reaffirm our strategic position every week (or     month)?
•     How would my cash flow look like at each of these ranges?
•     Establishing a contingency plan for threats that are assigned priority after both qualitative and quantitative analysis.

Besides all this, a company can somehow get to form a team with people from various domains like the Sales, Supply Chain Management, Marketing and Strategy planning and establish an agile process in place to help the suppliers and manufacturers cut down the response time taken. This could effectively save a lot of inventory cost and waste especially in the Consumable Goods Industry. While it could even take decades for the forecast models to reach the expected levels of accuracy, the companies that take leverage of the existing advantages of forecasting would have a strategically competitive position and less things to catch-up later when the model matures. It is interesting to realize how the article “Four Steps to Forecast Total Market Demand” starts emphasizing the importance of the byproducts of forecasting and sort of resonates with our discussion thus far.

It would be interesting to ask ourselves “Shouldn’t companies focus on deriving best out of existing provisions to continuously adapt as the forecast model develops?”

Article to Check

http://hbr.org/1988/07/four-steps-to-forecast-total-market-demand/ar/1