ED HAYES

I was sent a message on LinkedIn from a gentleman requesting my input on their planning methods. As I was writing my response, I thought that it would be of benefit to other people, so I am posting the question and response here. Click “read more” below to read the entire question and response.

Question:

We both share the Supply Chain group on linkedin.I understand you have experience in Demand Planning & Forecasting. We at the IBF – Institute of Business Forecasting & Planning are currently researching what companies are doing to manage their inventory, reduce operating costs, improve customer retention & fulfillment in this volatile market? Especially, when history can no longer be an indication of future outcome. It would be great if you could share some thoughts on what your company is doing to remain competitive and preserve cash. Furthermore, do you feel executives are recognizing the important of demand planning & forecasting, more so now than ever before? And if so, are they only looking for technology as the quick fix, or improving processes from your viewpoint? Of course, we see pursuing technology without having proper processes in place to be dangerous.

So far, we’re seeing companies paying more attention to forecasting for items with higher value only, and doing it at shorter interval. We’re also seeing companies truly leveraging their S&OP processes, as well as their POS and Syndicated data to make better planning decisions from having a clearer picture of consumer behavior at any given time.

Response:

Thanks for the message. I was unfortunately laid off in December. However, I can tell you that we had a similar problem, and when I left we were working on reducing working capital. The problem we had was that the production planners at the plants were all trying to fill their production schedule so that the production line was utilized when there were crews there to staff it. As a result, inventory was extremely high and all of our plants.

We did a few things to try to solve this. First, I created a tool to analyze safety stocks using data from our order history and item level fixed days supply. Second, we would discuss the new safety stock recommendations, by item, with the plants before adding the new data to our Oracle Item setups. Finally, there was a push to drive production solely off of our manufacturing plan recommendations. Recommendations were driven off of daily customer orders, forecast, and safety stock demand.

Oracle adoption was pushed from very high up in the company. The one pending item that we were working on when I left was our legacy way of thinking of inventory targets. Prior to our Oracle implementation, we had inventory targets as a metric. These targets were Monday Morning levels of inventory. We assuming production seven days a week and shipping five days a week. So these levels were historically the highest point of our inventory and were the metric at which plants were gauged.

Post oracle, this economy, and staffing changes all impacted changes to actual inventories at plants, and it was apparent that a heuristic or best judgment way of creating these targets would not work. It was also apparent, in my mind, that it was a poor metric to use. Plants should not be graded on their levels of inventory as compared to one target: temporary order surges or lulls could make a plant look poor, when in fact it was producing perfectly against the manufacturing plan.

As I was leaving, I was in the process of creating a method of calculating inventory targets using the fore mentioned safety stocks, fixed days supply, and average daily shipments. Where the total volume of safety stock would be a “minimum” inventory, and a calculation based on fixed days supply and average daily shipments added to the safety stock would be the peak of inventory. Of coarse the peak may or may not land on a Monday like our prior metrics assumed; that was a change management issue that had yet to be discussed or resolved.

When it comes to forecasting, we were in the process of upgrading to Oracle Demantra when I left. Oracle Demantra would greatly improve our forecasting methods, and accuracy. And yes, It was apparent that accurate forecasts were an important part of our planning process. But, an accurate forecast is meaningless if you do not produce exactly what you are recommended to based off all of the data inputs including, but limited to, forecasts, safety stocks, and orders.

Hope that helps.