QA as the key for business performance in SAP

What's the key to a successful migration project?

In one sentence, I'd say: a good identification of the people involved in the project and a realistic budget. When I talk about human strength, it's very important. You need to identify trustworthy partners (including good testers) and the project players on the customer's side.

What do you mean by "trustworthy partners"?

I think it's really important to surround yourself with specialists and work hand in hand with each of them. That means working with companies with experience in the field. This ensures a quality migration and a well-defined project. At QESTIT, we're fortunate to have over 25 years of software testing expertise, and SAP specialists, including myself.

How do you ensure that collaboration with the business referents is a success?

To manage an SAP Project, it's really important to understand the different businesses that will be impacted. The analysis of the existing system, the “as is”, is crucial and enables us to build a future version, “to be”, that really meets the needs. Nobody likes change in their working habits, so our role is to anticipate it as best we can to avoid frustration during the go-live. We call this “change management”.

With all the projects you've done and followed, what are the differences between an SAP project and others?

The main difference with SAP is that this software includes modules that are more or less adapted to customer needs. So you have to set up the right modules and customize some of them to suit your business needs. In a “classic” project, you start from scratch and create everything. The approach is therefore quite different.

You've worn many hats on these projects, what's the most crucial role you've played?

The key to the success of this type of project is the team. But if I had to single out one role in particular, I'd have to say the person in charge of data migration. Data is essential today, and very precious for some companies. You need to be able to clean up the data and adapt it efficiently to the new system, by defining the right new rules (Mapping, data management and integration rules, etc.).