Breaking the Data Chains

Change is hard, and frankly, people do not generally like change. We all enjoy having our routines. The same route to work, the same familiar faces, smells and sounds. It gives us comfort knowing what to expect. Moreover, there are many instances where good habits and predictive behaviour is helpful in maintaining a well-functioning society.

But change can be good, especially when it is as a result of a well-thought of plan. You may want to improve your well-being and start doing more exercise; you may want to improve on your financial well-being, learn new skills and improve your contribution to the business.

Data chains, however, refer to the phenomenon where an organization fears systemic risk on their data, and in effect avoid changes that may “rock the boat”.  It is of course natural and sensible to mitigate risks, however, this should not come at the expense of opportunities, and can lead to loss of competitive advantage and optimization.

As an example, assume a company that handles customer information.  When customers complain that the system limits the amount of information you can input to an address field - the company responds by providing interactive assistance in abbreviating parts of the address. For example, helping the customer abbreviate street to st. drive to dr. and so on.

You do not have to be an information architect to appreciate the adverse impact on your customers. Imagine you are the customer, and you want to update your service provider with a new address. Will you spend 10-15 minutes working out how to fit your 150 characters street address into a 50 character space? I know I got very irritated when I did that. This is an example of a data chain.

The designers and developers of the system decided to add dubious functionality instead of correcting the flaws in managing the data requirement appropriately. Don’t even get me started on the poor interoperability and life-time cost of maintaining this solution.

People compromise on sub-optimal data management solutions with a short to medium outlook. This is a dis-service to the business, which ties down the organization to complexity and higher systemic risk.

To liberate your organization from data chains, you must create a clear vision and a capability to guide workers towards that vision. This will allow you to make decisive decisions on how to design and implement data solutions. And in the event where time and money is a constraint (now when did that ever happen…) - factor in the long-term implications of the solution, implement a short term fix, but secure the funding and commitment to revisit the problem and ensure the adverse long term negative impact is addressed.

Now go on, set your data free...