Knowledge Integration Dynamics

The devil in the data framework is tactical delivery


By Johann van der Walt, Knowledge Integration Dynamics (KID)
[Johannesburg, 5 July 2011]

A data strategy, more simply put, is a data management framework. It's a means to formalise and govern an organisation's data. And every business needs one. However, that's not to say they actually employ one.

The simple terminology used to describe it also represents one of the greatest dangers of the data management framework: that organisations create a framework but never develop a single tactical delivery, and so the framework is a pointless exercise, a waste of money and the organisation continues to founder in its own mire.

The truth is that most organisations don't have some formal means of organising their data strategy or governing their data. It never filters down to the chaps in the basement. Most often they develop one informally over time and it is seldom recorded anywhere, except perhaps in a dusty project document in the corporate library – if at all. Usually the data strategy is an informal collection of accepted practices in the IT shop, a sort of word-of-mouth history passed on from one administrator and technician to the next.

Be honest with yourself and you realise it's not the most effective approach. Dig a little deeper and you begin to see that besides making data ineffective, it actually costs the business money, efficiency and flexibility. It inhibits the ability to respond to market conditions – an oft-used phrase but, to put it in perspective, a data management and governance strategy must cover visibility, measurability, accountability and ownership. Those are the critical elements, the pillars that define a solid framework.

But they aren't going to get acted on if the business rules don't reflect what they aim to achieve. The framework may set the tone, but the business rules put the letters in place. You have to ally all of this with the systems, the software and the hardware, many of which incorporate standards and practices, sometimes disparate, and ensure that all components of the data management framework mesh throughout the organisation.

Once the C-level execs have had their say, they've distilled the mission statement into a vision for the data to follow, the enterprise architects, project managers, programmers, lawyers, security administrators, database administrators, and line managers must co-operate to develop the tactical components of the strategy. Without that follow-through, the act of developing a framework is near pointless.

Without a clearly documented strategy with derivative tactical objectives, the enormous volumes of data that many organisations collect are diluted in value. Documenting the strategy and the tactics and handing them over to a project manager for implementation, then following up with consistent revisions, are paramount.

Why paramount? Because without doing so, three things take a hit: interoperability, data quality, and the ability to re-use data.

Poor quality data means interrupted operations, poor and costly decision-making, and corrupt planning. Bad interoperability means slowly developed and released financial products, for example, snail's pace customer relations that lead to churn and erosion, laggard accounts and billing with a direct impact on revenue streams, supply chain interruptions with resultant out-of-stock situations that once more result in lost customers and eroded revenue streams. Poor re-use is expensive because it means getting data, making sure it's fit for purpose, using it, and then discarding it. The return on investment is extremely low, speed-to-market is awful, and human resources wasted.

In addition, there can be poor traceability, poor governance, poor accountability, and those erode organisations to the point where executive heads begin to tumble and many more besides.