Data Governance Journey toward Data Citizenship

Data Governance Journey toward Data Citizenship.

BY Henry Peyret, Principal Analyst, Forrester Research, Inc.

Data governance has long struggled, as it oversimplified three key elements of a governance model: objectives, structure and processes. As firms become more insights-driven, the stakeholders in data governance expand, and objectives become more complex. A new approach to data governance is needed – ‘2.0’ version with an end-state of data citizenship.
But there is no single path to this end-state, as every firm has their own dynamics.

Forrester Research examined the last 5 years inquiries with our customers and found :

1. Organizational issues dominate – and are changing. Questions about how to organize the data governance function, and where it should report, have been the most common questions during these five years. But recently, the nature of these questions have shifted from basic ones around roles structure towards more about efficiency and including a broader range of stakeholders.

2. Objectives and justification is a top issue. These client inquiries ask about how to improve business alignment and the right metrics to track and communicate. They indicate that, today data governance still continues to be viewed as a cost.

3. Process rigidity kills DG efficiency. The predominant data governance domains of compliance, security and data quality tended to think that only strong processes would ensure good results. But with new domains – like MDM and privacy, a more loosely collaborative approach which better addresses these DG domains is needed.

At Forrester we see that data governance is deeply changing – ultimately transforming to a state we call Data Citizenship. With data citizenship, everyone (company staff as well as customers and external partners) acts on their responsibility for the data the company manages. But while the end-state is known, and some companies are already moving toward that state, we find the journey to that goal is different for every industry and company, due to their business model and the importance of key topics to their customer relationships. Privacy is an example topic that is tackled differently in different companies and industries.

We are calling the journey to data citizenship Data Governance 2.0 because the objectives and domains of applicability: quality, uniqueness, lifecycle, compliance or security, deeply evolve from data governance 1.0. This journey is not only changing the domains objectives – it is also adding new ones.

Every enterprise will discover these as they experiment with issues like 1) privacy – offering transparency of data usage to their “opted-in” customers, and 2) machine learning – ensuring that data-driven algorithms correctly obtain the desired result out of the data sets which it should apply, and governing the data sets used to learn.

The data economy brings an additional trend as companies share more data transparency with regulators, with aggregators, with their customers or different type of communities, such as for health research, or energy saving.

This data governance journey toward data citizenship is more than just evolving a business glossary and some processes around that to manage changes. It requires continuously reviewing risks vs rewards to get the best decisions in a shared and transparent assessment. It represents a cultural change around data – and nothing is more difficult in enterprise than a cultural change. Data was invisible to most of the employees. Data should become visible to everyone including the rules and policies associated with this data – the data context which is broader and easier to interpret to business users.

While companies continue to ask for benchmarks, that makes less and less sense as every data governance journey is different.
So companies should
1) seriously work their data governance – evolving objectives and showing better value thru business alignment,
2) rethink their organizational positioning to extend stakeholders involvement but not diluting enterprise goals, and finally
3) bring more agility in the governance process, delivering the value to different stakeholders in line with their own objectives.