Some Information Governance deliverables are unpredictable

Publish date:

As with most projects, Information Governance programs, too, should set clear objectives, timelines and: expected outcomes, i.e. deliverables. As the exact nature of an IG program’s workstreams often becomes apparent only once the program is up and running it is difficult to describe the content, format and deadlines for some of these deliverables at the […]

As with most projects, Information Governance programs, too, should set clear objectives, timelines and: expected outcomes, i.e. deliverables. As the exact nature of an IG program’s workstreams often becomes apparent only once the program is up and running it is difficult to describe the content, format and deadlines for some of these deliverables at the start.

But we must try. Take the example of your Business Glossary. Your organization probably has a number of product data standards already, e.g. definitions for “Product”, “Item”, “Range”, “Product Status”, “Group”, “Type”, “Segment”, “Family” etc., or a product hierarchy, or a classification standard. But they might be kept in different locations, poorly documented, sometimes even with unknown definition owners.

In this example, even the Business doesn’t know at the start of your IG program which definitions are still missing or need to be harmonized, where the issues are in the Product hierarchy, and what values in the classification standard are out of date. And nobody would dare to venture a solid estimate of how long it might take to agree, sign off and implement a new and improved Business Glossary.

So how do you plan such deliverables? Well, while there are too many variables in specific deliverables, some more general deliverables can be planned very well, e.g. your IG maturity As-Is assessment, your data domain criticality assessment, the documentation of outputs from the kick-off workshops, the review and analysis of existing standards documentation, the continuous dialogue with the IG stakeholder community, Data Quality profiling results, a roadmap, and of course the go-lives of major information management programs that your IG initiative might be aligned with.

The reality is that organizations often underestimate the number of stakeholders involved in IG discussions, availability issues, dependencies on other programs, the complexity of some of the topics, office politics and other distracting factors. Workstreams therefore often do not conclude within expected timeframes. Which is why your program should run many workstreams in parallel in order to deliver a trickle of outputs at any given time, even if it’s often unpredictable exactly what outputs they might be and in which order.

You’ll need to find a good balance between predictable and unpredictable deliverables and place caveats into your project plan accordingly. At the end of the day, what matters most is the level of support from your most senior Business sponsor. It is he or she who will ultimately need to say “keep going” even if one or two of your deliverables were to slip beyond its original timeframe.

For more information on Capgemini’s QuickStart Information Governance framework, please contact Ralf Teschner.

Related Posts

AI

Beyond the AIOps hype: Part 2

Sindhu Bhaskaran
Date icon August 7, 2020

In this, the second in her blog series exploring AI for IT operations (AIOps), artificial...

AI

Interconnected World Of Big Data and Other Technologies Redefining The Future

Sumit Kumar
Date icon July 31, 2020

Data has always been an important asset in business, however the value of data was redefined...

Information Governance

Avoiding information governance failures

Sumit Kumar
Date icon May 29, 2020

The steps that organizations should take to avoid failure in information governance