The joy of throwing data away

A typical battle field when it comes to joining subjective and objective data is the vast range of possibilities. It is very demanding (and requires a solid scientific base) to throw data away, but simplicity is a must. Simplicity is necessary especially because people are involved in all kinds of customer interaction. People must be able to get orientation quickly. This requires a simple and quick approach, or the best data does not help.

Luckily, Subjective Quality people have lived with this all their lives, recognizing that the perception of a single person cannot be stretched without disruption. This makes the solution an easy one: All kinds of objective data that support the insight into value creation are welcome. All others have to take the way to the bin.

And what happens if we need the data in the future? This is a standard argument in BigData, but the implied answer justifying data retention is a fallacy. All existing business models can be broken down into seven basics. For each, the data requirements can be well defined (when it comes to customer data). Throw away what is apparently garbage, as it does not show up in any of these seven!

Even if someone invented a new business model in the future, would this new way of doing business rely on data from years ago? In technology driven markets, this is unlikely, especially as there will be so much new data, and the real interest is in future business.

The half-life value of customer data is generally over-estimated. So – let’s keep court and garden clean, simple, and relevant.

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