Getting the most out of SAP is as much about ensuring that essential data is accurately entered into the CMMS / EAM system, as it is about identifying and retrieving useful information from the system. These two sides of the same coin are both very important contributors to helping improve maintenance efficiency and OEE.
Many organizations operate in the heat of the moment and spend most of their time on reactive maintenance. They have limited standard work processes in place, and as a result, the quality of their data can be compromised and inconsistent.
Many do not enter equipment repair history into their system at all. The most skilled craftsmen, who had been with the company years, carry the information in their memory, so when they leave, the equipment history leaves with them. As baby boomers retire, this problem will increase.
At some companies, well-defined work processes are in place, yet their SAP system’s design and use, and the organization’s knowledge, skills and responsibilities are misaligned. This contributes towards flawed data.
Why does this matter? Let’s take one aspect. Well-tracked equipment and system history in SAP PM supports reliability initiatives by enabling bad actor identification, for example by tracking:
To get to the point where essential data is accurately entered into SAP EAM / PM and all key work process events are consistent, a good overall approach needs to be in place:
SAP is well known for being a very robust, yet complicated software solution. Difficult navigation and fragmented reports make it a challenge to gain insights into the activities of the maintenance organization. There are various ways of gaining access to important information such as backlog, KPI’s, cost, etc
Once the data is consistently and accurately captured, there are many ways to turn it into meaningful information. We offer a number of powerful analysis tools that our clients use on a daily basis. The key, however, is that all our clients made the effort to ensure that everyone in their organization understood the importance of clean, concise, consistent and accurate data capture.
What are some of the ways that your organization ensures data quality and relevance?