Monday, December 16, 2013

The Theory of Data Mind

People have different metadata for their lives. Not only from a fundamental semantic perspective (I.e. language), but also at a more complex levels ranging from domain specific formally obtained (I.e. education) to personal semantics built over time (I.e. life experiences).

Now when you were a child, your caregivers thought you the theory of mind (hopefully). This is the ability to understand that other people's perspective could be, and actually is, in most situations - different from yours. In professional terms we call the application of this theory - stakeholder management. To succeed in your tasks you need to satisfy the requests of the people who will judge its completion. It might be yourself, your manager, your client and/or other authorities. In effect, to be successful you need to convince your stakeholders that you have completed the task to their satisfaction.

In data management we talk a lot about context. The semantics, quality, responsibilities and impact relating to data all mean different things to different people. This is because they have different responsibilities, life experiences and education. Learning to deal with these differences is an essential to the success of implementing data management.

Interestingly enough, the practice of data architecture, which forms part of the discipline of data management, is in itself entangled by semantics and theory of mind issues. Too often people rely on a limited set of theories and a limited set of stakeholders’ perspectives to both define and implement data management.

What is the difference between data and information architecture? Who is responsible to the data profiling? What is the best reference framework to use in implementing data management? Most likely, everyone reading this post has their own opinion. As long as we continue to support independent organization – there is nothing wrong with adopting different sets of tools and practices. However, it does make it more challenging (and costly) to create a sustainable data strategy. Imagine the rotation of responsibilities between existing employees and new employees. The more exceptional your approach – the more difficult it would be to introduce it to people and to integrate it to existing processes.

The reality of it all is that in practical terms, companies will continue to implement different strategies towards data management. Some of the variations will originate from the different characteristics and requirements of each organization, while other differences will be due to the lack of consensus on a single “golden” reference framework to implement data management. Companies will only align their approach when there is a real business need to do so.

So what all of this mean to you, as someone concerned with the well-being of the data in your organization? When implementing data management limit your scope (but keep a strategic mind).  Keep theoretical conversations outside the formal data management conversations. The leaner and meaner (precise and useful) your strategy is – the more likely you are to succeed.

Just be warned: you will get nowhere if you forget to apply the theory mind to the application of your data strategy.

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