Executive Briefings

The Process Needs to be Re-Calibrated

Analyst Insight

In discrete industries, leverage your demand forecasting investment by adopting automated workflow and decision-making technologies. The statistical forecast is primarily a baseline on top of which the impact of the channel sales has to be added. Statistical forecasts are not as important, but increasing the planning frequency and adopting workflow technologies are critical in these industries.
-Nari Viswanathan, research director at The AberdeenGroup

Aberdeen research finds that 50 percent of consumer industry companies are reporting that it takes more than one month to sense changes in demand, a potential pitfall in today's business environment if it is not addressed and improved immediately.  There are significant opportunities for companies to gain improvements in top-line sales, profit margin, and inventory levels through improved demand planning practices.

The key characteristics to focus on within demand planning are:

• Single number forecasts. Aberdeen research finds that best-in-class companies are 70 percent more likely than their peers to have a single demand forecast with inputs from multiple roles within the organization. This contrasts with poorer performing companies, which are more likely to have multiple, unintegrated demand forecasts.

• Frequency of consensus forecasting processes. A total of 60 percent of companies forecast at a frequency of less than a month. This dynamic approach requires a rethinking of the frequency of forecasting from the all-too-often static monthly forecast to one that is dictated by the frequency of significant changes in the marketplace-increasingly, daily or weekly.

• True customer demand. In the consumer industry, due to the availability of point-of-sale data in syndicated format or through demand signal repositories it should be expected that everyone should be forecasting based on true customer demand. However, only 48 percent of companies report that they use true customer demand.

• Technology innovations. Short-term forecasting techniques, attribute-based forecasting, and intermittent demand forecasting techniques are some examples of, not necessarily ground-breaking, but definitely under-utilized capabilities that should be evaluated by companies based on their business problems.

The Outlook

The spotlight on S&OP in the industry is providing renewed interest in the demand planning and forecasting space. In 2008, we can expect to see increased focus on updating with more best-of-breed demand forecasting systems. Companies, however, should be extremely particular about the how the solution fits within their industry and select solutions appropriately.

Analyst Insight

In discrete industries, leverage your demand forecasting investment by adopting automated workflow and decision-making technologies. The statistical forecast is primarily a baseline on top of which the impact of the channel sales has to be added. Statistical forecasts are not as important, but increasing the planning frequency and adopting workflow technologies are critical in these industries.
-Nari Viswanathan, research director at The AberdeenGroup

Aberdeen research finds that 50 percent of consumer industry companies are reporting that it takes more than one month to sense changes in demand, a potential pitfall in today's business environment if it is not addressed and improved immediately.  There are significant opportunities for companies to gain improvements in top-line sales, profit margin, and inventory levels through improved demand planning practices.

The key characteristics to focus on within demand planning are:

• Single number forecasts. Aberdeen research finds that best-in-class companies are 70 percent more likely than their peers to have a single demand forecast with inputs from multiple roles within the organization. This contrasts with poorer performing companies, which are more likely to have multiple, unintegrated demand forecasts.

• Frequency of consensus forecasting processes. A total of 60 percent of companies forecast at a frequency of less than a month. This dynamic approach requires a rethinking of the frequency of forecasting from the all-too-often static monthly forecast to one that is dictated by the frequency of significant changes in the marketplace-increasingly, daily or weekly.

• True customer demand. In the consumer industry, due to the availability of point-of-sale data in syndicated format or through demand signal repositories it should be expected that everyone should be forecasting based on true customer demand. However, only 48 percent of companies report that they use true customer demand.

• Technology innovations. Short-term forecasting techniques, attribute-based forecasting, and intermittent demand forecasting techniques are some examples of, not necessarily ground-breaking, but definitely under-utilized capabilities that should be evaluated by companies based on their business problems.

The Outlook

The spotlight on S&OP in the industry is providing renewed interest in the demand planning and forecasting space. In 2008, we can expect to see increased focus on updating with more best-of-breed demand forecasting systems. Companies, however, should be extremely particular about the how the solution fits within their industry and select solutions appropriately.