International Business Program

Predicting customer demand is a critical process in the business world, both for manufacturing and distribution. This process is a fundamental step towards achieving a good level of service with reasonable costs based on an adequate level of inventory.

Predicting the outcome of the application guides clients on what to buy, including when and how, all companies need a reasonable forecast accuracy to define an effective plan to meet customer needs.

The reality is that no result can achieve an accuracy of 100%. forecasting future demand, directly or indirectly involved in trying to predict uncontrolled variables that somehow influence the behavior of sales, as economic climate, regulations, activities of competitors, consumer preferences and trends , new products and promotional activities. We can’t wait until someone is able to predict the behavior of all these variables all the time.

At the same time, lack of accuracy in forecasting sales is costly, with excess inventory, exhausted, low productivity, low levels of service and, usually, the friction between sales and marketing, manufacturing and distribution any business.

Then raise the level of precision is an impossible mission?

In today’s competitive world, most companies of all sizes are using an integrated information system (ERP) systems can plan and monitor their daily activities, they also provide basic functionality to forecast customer demand But without in most cases, these tools do not meet all the requirements of good prognosis in the company.

Understanding the need to improve forecast accuracy, firms tend to pay a high cost for the use of knowledge in sales and marketing executives in the collection of sales data and place it in a spreadsheet Excel or Lotus and develop the forecast, typically a complex process that takes several days.

In many cases 95% of the time of these meetings is used to collect data and calculate forecasts, the remaining 5% in the evaluation of results. Given this situation, the same proportion seen in the results, 95% of the time with a bad result and 5% luck. Many companies were resigned to the situation and do little to improve the quality and accuracy of sales forecasts, spending valuable resources unnecessarily.

But for companies to refuse to accept the results, if possible to streamline the forecasting process to improve the quality and accuracy of forecasts?

Obviously not an easy road as any benefit has a cost. So how can you justify the investment? Symptoms such as high inventory levels, exhausted, low level of service and emergency call may be the best justification. However, if still not satisfied, do the following exercise to determine where it could reduce systematically to increase safety stock levels if the accuracy of forecasts.

By increasing between 10 and 15% accuracy in forecasting will be obvious to you that the effort is worthwhile.

In the next two installments will look at two Australian companies have been able to implement and streamline their forecasting process, Cardinal Health and Furniture freedom.