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Ruud calls me one Tuesday morning. He’s a Business Intelligence Manager at a food processing company, and has a problem that he wants to share with me. Ruud is responsible for all reports, but his figures don’t always turn out to be correct. He could do without these issues, because the company uses his reports to makes vital decisions on a daily basis. So what now?
Ruud is by no means an exception. We’re regularly asked how organisations can improve their data quality. The first thing I want to find out from Ruud is how he thinks the figures end up being incorrect. He explains: “I’ve asked our Data Management department how our SAP ERP can contain incomplete or incorrect data. Data Management said that there’s not a lot they can do about it, as they receive the incorrect data from other departments. Their data is then also created in SAP.” Peter, the company’s Data Manager, adds that this problem also affects the Data Management team. They have to correct the necessary data in the system, which takes a lot of time.
Fortunately, Ruud knows that it would be unfair to point the finger at the Data Management team – they’re just as annoyed about the problem as he is. Ruud wants to run correct reports, and the data team wants to spend less time chasing different departments to have their data delivered correctly and on time. Nobody wants any wrong decisions being made based on incorrect data.
To get a clear picture of the current situation, I asked Ruud and Peter to give some practical examples of the daily data challenges in the organisation. They came up with the following list:
Ruud and Peter are obviously no exception. If you want to find out how we can help, make sure to read my next blog post.