I just had dinner with a friend who works with customer data for a new line of business (LOB) for a very large and established company. My friend – I’ll call him John – was brought on board to help with the transition when the company bought a set of customers from John’s previous employer. These customers were critical to launching the new business line, and Jack knew them and also knew the unique business rules associated with their contracts and billing agreements.
So I spent the evening being greatly impressed by my friend’s work. He designed the data flow for the LOB’s accounts receivable process. He introduced a standardized process, along with protocols for adapting the process to meet legacy requirements. He identified data quality risks, quantified them, and introduced controls to avoid, detect, and correct anomolies. He inserted checklist-based QA steps into data preparation tasks, data reconciliation tasks, and invoice preparation. He trained staff.
So? Typical Data Management stuff, right? A little Data Architecture mixed in with Data Quality, focused on Business Process Improvement. Working close to the money, introducing efficiencies and quality improvements in a high-value, business-focused enviroment. It’s what so many of us do, right?
Except the person he reports to doesn’t “get” Data Management. Acts like she might consider the work he does as just a couple of steps above clerical work. Ouch. Ouch. Ouch.
Anyone ever been in this position? What did you do to get validation? Where did you go? What advice could you offer my friend?
