Strategy+: 7 guiding principles to jumpstart an effective data governance journey

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A set of a well-defined governance principles is the heart of a high maturity operating model

Establishing an effective data governance structure is very important right now, especially, for the organizations that are moving towards S/4HANA and their complementary data solutions, including: MDG, Data Intelligence and Data Warehouse solutions, both cloud and on-premise solutions.

Data Governance is an important component to achieve your business objectives. Data Governance effectiveness is measured by how successful you are in managing, protecting, and taking advantage of your data to continuously enhance your business capabilities.

Having a common and a well-defined set of guiding principles can guarantee a successful data governance journey. These principles should be well-articulated and well-aligned to the values and needs of your business. Wherever possible, I encourage C-Suite to embed data governance responsibilities within their existing structures rather than building new ones. Now, let us explore the 7 guiding principles to jumpstart your data governance journey.

7 guiding principles to jumpstart an effective data governance journey

1. Align your data priorities with your business needs – From time to time your data priorities will shift according to your business objectives. You do not need to dwell on the low issues, however, you need to determine the key issues that your governance should address and your priorities should articulate what you want to do and be understood by everyone in the organization.

2. Embed your data governance within your existing structure – At the start of your data governance journey, it is better to embed data governance responsibilities within the existing structures and processes, rather than establishing new ones; embed your data governance within your working structures including technologies, processes, and operational responsibilities. This will allow your teams to embrace and share data responsibility more openly. This will also allow you to focus on the additional skills and resources you need to design, operate, and monitor a high maturity data governance operating model.

3. Design a flexible but a working data governance structure – I see many companies invest the time in creating a framework, setting up a center of excellence model, hiring the top data executives and creating many policies. However, many of the same companies do not initiate or mobilize the data governance program effectively, leaving all the policies and procedures sitting on the shelf. Effective data governance allows companies to meet their objectives fast with a strong commitment to data protection and data utilization transparency.

4. Classify your data and quantify the breach – One of the critical guiding principles is to establish the right classification techniques for your data and continuously improve your working model. I highly advise using risk and impact assessments to clearly define the gaps and to measure how mature your governance model. It is also important to quantify the risk in a monetary value to get the support needed from the senior leadership.

5. Focus on creating the right behaviors – Handling your data effectively is not just streamlined by policies and technologies. Behavioural changes are critical to improving the quality of your data and to managing your data issues. Between both data producers and data consumers, they need to understand what is expected and required from each other. Formally setting data flow and reporting expectations is critical. It is also critical to formalize and monitor data consumption and reporting at the individual level as well as at the company and departments level.

6. Create a technology platform that consume data effectively – Data, good quality data, is the perquisite for successful machine learning, real-time analytics, and AI programs. If you design and build a technology foundation with the goal to improve your business processes, then you will be more likely to succeed in achieving your data-driven business strategy.

7. Enforce accountability and get executive support – Everybody in the organization has a shared responsibility for effectively managing and protecting their individual and their company data. High maturity data governance model includes a clear sponsorship from the leadership, a clear ownership and accountability for managing, protecting, and consuming data, and a clear understanding of data security and privacy requirements.

Bringing it all together,

Data Governance is much more than managing data operationally, it is about developing an environment where the full potential of data is realized. An effective data governance approach integrates smoothly with the way your business run, while generating insights and building trust among your stakeholders.

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The views, information or opinions expressed in this short article are views of my own.  All information in this article is provided “as is”, with no guarantee of completeness, accuracy, timeliness or of the results obtained from the use of this information.