The data that is collected in an ERP system, effectively delivered, can drive real bottom-line benefits for organizations. But to drive desired improvements, manufacturers need to be confident in the quality of that data; it’s being used to make important decisions, and it’s driving their plan.
ERP stands for Enterprise Resource Planning, used to describe the systems that run companies. Unfortunately, the “Planning” in ERP is often ignored by organizations. A symptom of a poor plan is the frequency of changes within the planning cycle.
Manufacturing companies tend to ignore forecast accuracy. If a forecast is only usable for planning in manufacturing, it consists of two numbers: anticipated demand and confidence factor – or the probability of that number being accurate. As forecast accuracy improves, the confidence factor goes up, and fewer changes must be made.
There are warning signs, or preventive analytics, that you can take from the ERP system itself that speak to the effectiveness, efficiency and probability of a plan in place – in other words, the quality of that plan.
For example, an organization has a high percentage of past-due orders, which makes it more difficult to make supply chain decisions and prioritize production and outcomes based on availability of material. It’s not unusual for a manufacturing company to find old purchase orders on the books with due dates of two to three years ago. If dates aren’t valid, how can any business use that data to schedule use of those materials?