The Data Dilemma - Managing Data During An ERP Implementation

In my experience managing ERP implementation projects across multiple platforms and solutions, the one area of an implementation that is most often underestimated is data. The client is often faced with many questions as to what should they do with their legacy data. More often than not, the legacy data that is required to make the new ERP solution operational is in need of cleanup – the legacy system may not have had a good way to manage duplicate entries, had little in the way of validation, or as the business grew over time, solutions were put in place as stop gaps creating disconnected data. Another issue that we experience is that the naming conventions and/or structure of the data is archaic and would benefit from the client being able to revise the naming conventions and/or relationships prior to having the data ready for integration into the new system. This is the area in which the effort that is required by the client is often under-estimated and adds risk to the project as the timelines can be drawn out as the client struggles with internal discussions on how and what data may require changes.

Prior to deciding on the data that is going to be integrated, the client should ask the following questions:

Is it unstructured or structured?
Do you know the source of the data?
Do you have to repeatedly cleanse spreadsheets and send them to partners, managers, co-workers, and customers?
What is the value you are getting from the data?
What aren’t you getting from the current data set that you require?
What is your budget for initial integration efforts?
What is your budget for maintaining data quality?
Do you have the in-house expertise to extract and clean up your data?

One of the ways in which MIBAR helps to mitigate this risk is to budget data mapping sessions into our overall project plan. These sessions are designed so that the client can sit knee to knee with our implementation consultant to review each file that will be integrated and discuss all of the data points that are required by the ERP solution and, as importantly, the legacy data points that are meaningful to management that may not be in the new ERP solution. It is often at these sessions that a client gains a better understanding of the challenges they may face in extracting the data from their legacy system. This is the place in the project where we must discuss if there is a need to build data transformations that will map the old values in the legacy system to the new values that are desired in the new system. Data transformations are, for example, when a client may decide to change their Item ID’s – we may have to build a transformation table that identifies the old ID with the new ID for integration of any item specific data and referential purposes.

As the client, you are starting a new system and it is best to start with a solid foundation of clean data. We recommend only bringing in the data that is required to continue processing and supporting the analytics that the company requires. If your legacy system is still accessible it is often a much less expensive and acceptable solution to leave that software running for users that may need to go back in history instead of trying to bring in years of history into the new solution. Remember, the best practice we have found regarding data is that less is often more.

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