S.F.T. Inc.

The answer is most companies do make the effort, but are limited by the accessibility to the data and the tools that can easily manipulate the data into credible information. Therefore, the effectiveness of the effort is limited.

One of the key problems in developing an accurate forecasting process is the inability to obtain a thorough, real-time view of forecast variations. Most forecasts are developed based upon static information and assumptions, and the usual differences between actual demand and forecast demand are often misinterpreted, resulting in attempts at fixing a non-existent problem. This causes a chain reaction of events that cascade down through the company, often resulting in higher inventories, poor customer delivery performance, longer customer order lead times, and increased overhead costs due to excessive changes to production plans.

To obtain the highest quality forecast, a thorough understanding of products and customers must be obtained. To complete this analysis, the data must be segmented by a combination of customer, product line, sales region, sales channel, units, revenue, average selling price (ASP), costs, and time-frame. To review a forecast with this degree of detail, it is necessary to manipulate the data in several combinations of these segments to see how well the past trends align with the future predictions. On a regular basis, often weekly and sometimes daily, the task becomes impossible without adequate tools.

A possible result is finding that the graph represents a normal trend in the business with no corrective actions necessary. It is also possible that the total revenue versus forecast may be in sync (note A), however mismatches may exist in the unit, average selling price, customer or product type mixtures. In each case, this information would not be known unless this type of analysis were available as well as being in place for some time in order to understand the long term trends as well.

1. Competing goals between the Sales / Marketing and the Finance / Operations groups.
2. Inherent difficulties in obtaining a highly accurate forecast.
3. Loss of forecast data visibility when it is converted to a production build plan.
4. Inability to obtain a thorough view of the forecast exceptions in a real-time manner.

Competing Goals

An achievable process is one that provides Sales with the ability to perform adequate demand analysis so they can provide their "best" estimated forecast. Most often, the Sales / Marketing organization is in the best position to employ the most current information about the forecasted demand requirements, nevertheless, those requirements can change quickly today's economy.

In reality, both groups must recognize that the forecast is the best understanding at that time and that there will be errors. The emphasis is to reduce the adverse impact. This is achieved by managing the forecast errors quickly and efficiently by using exception planning and real-time demand trend analysis. The key to success is to empower both groups with meaningful real-time information and business motivations for joining together in the corrective action process.

The issue is further compounded by several logistical difficulties in managing and manipulation of the data. Spreadsheets are often used; however they are inadequate for this degree of analysis. MRP, WIP and financial software packages usually do not include such analytical capability as their primary objective is to meet accounting requirements, to control user transaction screens and to integrate with other software modules.