Supply chain management (SCM) forecasting software uses mathematics and algorithms to provide a look at what a
company's forward demand plan should be. Forecast planning is typically bundled in with other capabilities as part of a broader product suite, often in a demand planning system, according to Tim Payne, research director at Gartner Research.
In manufacturing, Payne said, many companies making a foray into SCM forecasting are switching from manual forecasting. While most ERP systems offer basic forecasting tools, the tools are very limited in terms of the way they model forecasts and are not responsive to changes in demand.
Forecasting technology has been around for a long time but in the last year there has been a big increase in its adoption. Manufacturers use forecasting software to simulate changes and track potential demand downshifts across geographies and product sectors, which is especially helpful in an uncertain operating environment. It's an area where companies are still investing despite the economic downturn, Payne said.
SCM forecasting software also gives a company a view of possible scenarios and provides options for handling specific situations and resulting outcomes. "Companies better understand how to buffer against the variability in the supply chain and how to apply appropriate supply chain strategies to cope," he said. "There's always going to be variability, but it's how you plan for that and what strategies you have in place."
If a manufacturer discovers an error in its supply chain plan -- dipping too often into their safety stock, for example -- managers can figure out how to adjust plans accordingly. "The key thing is [finding out) what is the error and [determining) what am I going to do about that," said Payne. "You've got the forecast, but you've got to do something with it."
But Payne warns that though SCM forecasting software offers a glimpse at potential future manufacturing scenarios, forecast accuracy only goes so far. "There comes a point when you really say, 'I've got that as good as I can get it,'" he said. "The Holy Grail of 100% forecast accuracy is never going to be achieved. It's learning to live with the variability and inaccuracy of the forecast."
About the author: Christine Cignoli is a Boston-based freelance writer who covers IT infrastructures and storage technology. She is a regular contributor to SearchManufacturingERP. Contact her through her website.