Imagine the scene. You go out to dinner at a favourite restuarant – maybe, you want to take the opportunity to close an important business deal, propose to your significant other, or just enjoy time with your family or firends.
You order your usual, the delicious house special, and enjoy a small bottle of the house Dry Red.
Everything looks and tastes good, the ambience is great and the service is attentive.
During the course of the evening the maitre d’ gets a call. He attracts your attention, aling with that of the other patrons, and announces that due to a small emergency in the street they have been asked to evacuate the restuarant through the back. There is no reason to panic – everyone can gather their things and leave through the staff entrance at the back.
As you are leaving you notice that the kitchen, which is closed off from the dining area, is filthy. Dirty dishes are lying around on the floor, cock roaches are rampant, and their is a strong and unpleasant smell coming from the cold room.
Even though you have eaten at this restuarant for years would you go back? If you were a health inspector would you close them down?
Many of us in data management are a bit like that maitre d’! We produce BI reports based on poor quality data, and massage the results until they look right – just like the decent food produced in unhygienic conditions. We spend millions on new systems, just like the resturant updating the decor, without considering the impact of poor data that we will take on. What is the value of upgrading the dining room if the kitchen is an epidemic waitng to happen? And we fudge our audits! Who cares about a lasting solution for compliance if we can fake it yet again.
Until one day we have an unexpected emergency and we are exposed. Maybe the auditors arrive unannounced and we cannot put in our usual clean up. Maybe changing business circumstances cause management to ask an unusual question – and the BI system simply cannot be massaged to produce a result. Maybe our new system, developed at massive expense and wth much fanfare simply fails to deliver on core functions – because the data is not up to scratch.
Data management is about being proactive on an ongoing basis, not waiting until you have an emergency from which you will fail to recover.
A clean kitchen is maintained by instilling a culture within your staff of keeping things clean and in place, all the time. This doesn’t require massive investment in new faciities – but once you have lost control it can be very difficult to get it back. Similarly, data management principles should be built into your environment to keep your data fit for purpose.
Historically, organisations could ignore the perils of poor data hygiene. Now external auditors are increasingly including data quality audits as part of their stadnard approach to the financial assessment of the business. Business need to begin to audit their own data quality, using specialist data profiling tools, to avoid the risk that a poor data quality audit may result in a qualified financial audit. Like the dirty kitchen, you don’t want to be caught off guard by the health care specialist