In a recent blog post called Hamsterdam and Data Anarchy by Phil Simon on The Data Roundtable it is described how rules, policies, and procedures sometimes are suspended in an unusual situation and how dangerous that may be.
I remember being part of such a situation back in the 80’s. The situation also included that I as an IT guy became “the business” and the situation could have been big business for me – or big time jail for that matter.
Quick-and-dirty
My first real job was at the Danish Tax Authorities. The government is always looking for new ways of collecting taxes and at that time a new kind of tax was invented, as a new law enforced taxation on the big money piling up in pension funds.
As the tax revenue was needed quickly the solution was a simple construction for the first year and a more complex permanent construction for the following years.
The burden in implementing the collection on the authority’s side wasn’t that big, so the operating team was basically a legal guy and me, being an IT guy. We collected the names and addresses of a few hundred companies in financial services that might administer pension funds and sent them a letter with instructions about calculating their contribution for the first year and turning over the money.
Money on the table
Because no one else in the organization was involved in the one off solution for the first year the returned statements and checks ended at my desk. So at that time my morning drill was opening envelopes with:
- A statement that I registered in a little data silo I controlled myself and then passed on to the archive
- A check that I passed on to the treasury
Some of the checks were pretty big – as I remember what resembles more than 50 million Euros.
So I did consider an alternative workflow for just one of the big ones. It could have been as this:
- Deleting the company in the data silo I controlled myself
- Archiving the statement in my kitchen bin at home
- Cashing the check for myself
Well, probably I would have been handcuffed when executing activity number three.
Liliendahl on Data Quality 