The cost of poor quality is often seen as the “cost of doing business”, and often the thinking is tightly stuck in that rut. The only approach that I’ve ever seen come close to addressing the holy grail of good quality data has been to:

1) Tackle people and processes to change behaviour that causes common errors
2) Put measures in to track the changes in behaviour (profile data on the way into your systems for example)
3) Then make the changes necessary to the systems to address the causes that are inherent in the system, or are required to address other process weaknesses that cause poor quality data.
4) And then (either at the end or in parallel to 1) and 2), start working to clear out the crummy data in the systems.

Unfortunately, executives are too used to the “zip bang flashing lights” of IT systems delivery (for example sexy new web applications or call centre tools) to appreciate the hidden value in the unglamorous work of mucking out the database and making the processes hum along to stop crud getting in.

It’s a bit like people being enamoured with “slim-quick” diet pills and ‘magic potions’ while not recognising the real long term value of going to the gym to improve fitness. The former gives unsustainable results quickly, but the latter gives longer lasting and more far-reaching benefits.

And on that… just popping out for a run….

Schöne Grüße aus Köln
Petra