Data quality projects

I have been in this situation many a time – if you are reading this blog you probably have too. It goes a little something like this:

 

 

Marcus: “How are you moving forward with your data quality strategy?”

Customer: “We aren’t. We have hit a stumbling block in getting the business case through the board. Until we get approval nothing can happen. They just don’t see the value in the project.”

As frustrating as this scenario can be it does raise perhaps the most valid question of all (and one most data quality vendors like us often struggle to answer) – how can I show real return on investment from data quality projects?

The truth is that most investment in larger scale initiatives is reactive. Industry commentators will be quick to point out that data quality projects are usually born out of an “event” that has caused significant pain to the business such as failure to meet regulatory compliance, data loss, significant customer complaints (that become newsworthy) or the need to migrate from one CRM system to another (it’s worth pointing out that the quality of the data is still often ignored as part of this process).

So how do you make the business case for data quality in the absence of a catastrophic event? And even more challenging how do you make a POSITIVE case for data quality rather than spreading the rumours around the fear, uncertainty and doubt of doing nothing. Well, there is a well-known joke floating around the analyst community that the fastest way to kill a data quality initiative is to tell the board you are spending their budget on cleaning data. The truth behind this tale is that cleansing and standardising data is rarely embraced for the sake of it. The key is to attach the initiative to the strategic goals of the business. The impact of data quality projects (particularly relating to customer data) can be felt on most of the common KPI’s found on business scorecards such as customer churn, operational costs, customer profitability, customer satisfaction and obviously top line performance in terms of revenue growth. These are the areas to focus on when making your business case to the board. Obvious? Probably. Essential place to start? Definitely.

I think if I left you with that information alone then making the business case for data quality projects would remain an impossible dream for your organisation, so let me leave you with this thought. Most data quality vendors will provide you with an assessment of your data (some will even do it for free depending on the volume of data you hold). If you ever get offered this option take it because step one in your journey is to understand exactly where you are with regards to the standard of your data. You will then have a figure – my data is x% accurate. What does that mean? You are still no closer to a board member putting pen to paper. The trick is to understand the relationships within your data that the % of inaccuracy relates to. For example on the surface 95% data accuracy for a bank sounds very credible indeed. But if the 5% of inaccurate records relates to 30% of their mortgage book that small percentage becomes a big problem.

The key to achieving the impossible dream is to understand the relationships between your records and attaching a financial value that means something.