”Under new management” is a common sign in the window of a restaurant. The purpose of the sign is to tell: Yes, we know: Really bad food was served in a really bad way here. But from now on we have a new management dedicated to serve really good food in a really good way.
By the way: Restaurants are one of the more challenging business entities to handle in Party Master Data Management:
- They do change owner more often than most other business entities making them a new legal entity each time which is important for some business contexts like credit risk.
- On the other hand it’s the same address despite a new owner, which makes it being the same entity in the eyes of other business contexts like logistics.
- In many cases you may have a name (trade style) of the restaurant and another official name of the business – a variant of this is when the restaurant is franchised.
Master Data Management is not trivial – serving restaurants or not.
Improving Master Data Management starts with the sign in the window: Yes, we know: Really bad information was served here in a really bad way. But from now on we have a new master data management dedicated to serve really good information in a really good way.
Then you may have a look at the menu. Do we have the right mix of menu items for the guests we like to serve? How are we going to govern a steady flow of fresh raw data that’s going to be prepared and selected from the menu and end up at the tables?
What about the waiters attitude? Serving is much more fun if you are proud about the dishes coming from the kitchen. It’s pleasant to bring compliments from guests back to the kitchen – not at least given along with great tips.
The information chef have to be very much concerned about the raw data quality and the tools available for what may be similar to rinsing, slicing, mixing and boiling food.
Liliendahl on Data Quality 
Henrik,
Great analogy, I like it a lot.
We Data Quality Professionals need great analogies like this one to get our message across. This helps us in conversations with senior management. It helps us explain the criticality of high quality underlying data.
Having convinced senior management of the obvious need for high quality raw ingredients – the challenge moves to proving instances where the raw ingredients were not of high quality.
In a restaurant scenario, the customer can verify the quality of the meal against a “known source” – his or her past experience, and expectations of the meal.
It is not so easy to detect problems in Information derived from underlying data.
There is seldom an “external source” against which to verify “derived information”.
From a senior management perspective, the meal served up (The Information) looks OK, smells OK, and tastes OK, and was prepared by “good people”.
It is perfectly reasonable for senior management to take the above stance. It is also perfectly reasonable for them to expect their “good people” to have an audit trail proving that the raw ingredients were “fit for purpose”, and showing the transformations and calculations applied to produce “the meal”.
The bottom line:
In the absence of a trusted external source against which to verify the end result, one must have an audit trail. This is the least that Regulators will expect. In time, Regulators will also expect a “Data Accuracy Scorecard” or “DAS”.
To avoid being left with a bad taste in your mouth – Make sure you have data flow audit trails!
Ken
Ken, thanks for visiting my little data quality and master data management café.
I agree with you that we will see more movement around regulations and other quality assurance activities in the realm of master data similar to what we are used to in the financial data realm.
Master Data Management is the new bookkeeping. Any enterprise is described much better by having a look into the Master Data than by reading the Financial Statements made up from the Transaction Data.
Great example of analogy! I really like it!
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