Sunday, September 15, 2013

The Origin of Poor Data

Why do we have data quality problems? What is the underlying cause, or set of parameters which lead us to a situation where data quality becomes an issue? Can we pull it out at the root? Do people have the potential to master data management through tweaking the basics of the underlying causes earlier on? can we eradicate data quality issues altogether?

We already know that data quality issues arise from sub-optimal delivery of information. It is not a result of incompetent professionals who do not know how to use the right information once they have it. So the issue is really, as noted by many - quality at source.

There are several reasons why the source of the data is poor at times. It stems from either a lack of understanding or a lack of acceptance of the importance associated with the needed quality of information. When it comes to the former - this is usually a matter of informing and clarifying the requirements with the right audience. For the latter - controls in the form of reward and punishment are likely to be most effective.

But this is not the underlying cause. Why do people fail to understand the requirements, and why are information providers not accountable to the information from the start? The answer of course is context and relevance, as I have alluded to in previous posts and this seems fair enough. I have my set of circumstances to deal with, and you have yours. We both act in the best interest of the values we hold and the responsibilities that are assigned to us - and we hope for the best!

That, unfortunately, does not sound quite right. If we want to reach Teneo Vulgo, then we must be able to assimilate higher level of awareness to others' information needs. Can we know everything everyone wants? well of course not. So, what do we do? How do we ensure that the responsibilities and context is sensitive enough to reduce the impact of siloed context of information?

One approach would be to educate people from a young age to appreciate the multiple reasons and uses of information. We do this in language, when teaching them that a single word can mean different things. Story tellers use this duality (or ambiguity) to create mystery and surprise their audience - but this is, again, context specific. The generalization of this is in the context of education. We need to promote the value of correct information (by showing for example how wrong information can lead to problems e.g. lying or Information Quality Trainwrecks) we need to demonstrate, in real-world examples how the same information can be used by different people for different reasons, and what it really means to look after information; and we need to give more credit to people who do this right.

But let's get practical. Although this is what the true generation of Teneo Vulgo will value and practice - we want to improve the quality of information today. Unfortunately, I have no better cure than clarity and control. But here is an afterthought: You might want to combine the two by tying them together. In other words, people's performance and remuneration should be linked as closely as possible to data management so that they will develop an appreciation to the impact of poor quality of data they distribute.

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