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Blog |  6 min read

Agile Information Governance For The New Data Economy

The emergence of Big Data and the new data economy, where the focus isn’t just on data but the ability to get value from increasing amounts and types of data, has brought with it the need for new ways of Information Governance. Now, the emphasis needs to be on being more agile in your governance of information and that task has been simplified thanks to a new approach pioneered by IBM.

In his book The Macroeconomics of the Global Technology EconomyHoward Rubin talks about the data economy, the cost of managing data in order to run the business. He estimates that 92% of the cost of doing business for a financial services organisation is spent on data. These costs can be broken down to acquiring – 5%, storing – 11%, retrieving – 6%, distributing – 15%, delivering – 12% and processing – 34% of data. While companies focus on storage, cloud, outsourcing and managed services they should be looking at the economics of data.

Big Data started out as an architecture solution for increasing volumes and types of data. It is becoming an economic problem for organisations that already have more data than they can manage and are struggling with the cost of trying to manage an order of magnitude more. Agile Governance is knowing when and how to spend money on data. What happens if you clean, gut and cook a fish and then after the first bite realise it tastes terrible? If Big Data is like truckloads of fish being dumped on your desk every day – how do you know how to find the best tasting fish?

The Agile Governance Way

A part of the Big Data push is a new way of getting value out of data – to get more value out of more data in less time with less people and less money. This requires a Big Data architecture and in order to trust the results and handle inherent risk in the handling of data, it requires an innovative approach to data governance.

The IBM Agile Information Governance Process, shown above, consists of six steps across three distinct phases. In the Plan phase, information governance teams define the business problem, obtain executive sponsorship, align teams and understand data risk and value. In the Act phase, organisations implement one or more projects based on common use cases. Finally, in the Assess phase, information governance teams measure results.

The IBM Agile Information Governance Process is built as a continuous loop. As information governance teams measure results on one project, they start anew by defining the business problem that may spawn additional projects.

What differentiates the IBM Big Data story from a lot of others is that they come back to results – they always put Big Data into a Governance sandwich. Up front are the steps for starting a Big Data project, at the end is the measurement of the results.

As a final step, the organisation should assess the results of the information governance programme and make adjustments. After this assessment is completed, the information governance programme loops back to define new business problems or to make adjustments to existing business problems. The process then starts over again.

Assessing and measuring results is the key to building systems of advantage. Cost effective data management and the governance of that data lets you roll out more information-driven systems of advantage and trust the results you get from those systems.

Join the IM is the New Black Group. This group is open to IM professionals, looking to share insights, encourage innovation and keep abreast of cutting edge technologies in this exciting area.

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