One of the challenges of fitness for purpose

A common definition of quality data is data that is fit for purpose.

Last week, I suggested that Steinhoff’s accounting shenanigans can be attributed (at least in part) to poor data quality and, more directly, to poor governance.

Francois Marais’s Response to ‘a Steinhoff guide for dummies’ gives non-financial experts an understanding of what Steinhoff were doing.

Is this really a data quality problem?

It depends on your perspective – or, in my judgement, your purpose.

If you were the Steinhoff accountants trying to present a more positive face to the world – then the data was of good quality.

If, on the other hand, you were an investor or a creditor, then the numbers were arguably of a poor quality.

A great example of how data can appear to be of good quality until it needs to be used for another purpose

In recent news – Steinhoff 2016 results also need to be restated







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