It’s Time to ‘Expunge’ Data Governance
In this guest editorial post, Absa Bank Head of Data Governance Dr Sizwe Gwala argues that data governance should be utterly ‘expunged’, and value-driven use cases prioritized
‘Expunging’ refers to the act of eliminating from existence (erasing, deleting, or destroying) information or records. It is commonly used in a legal context when referring to the removal of a conviction from a person’s profile. Now, you’re probably asking yourself whether there has been a mistake, or if I am a crazy person. Well, there is absolutely no mistake and I’m still psychologically sound, as far as I can tell.
I met a fellow data leader a few weeks back and spent time deliberating on what data governance meant in modern organizations. Our robust discussion led to an introspection of the appreciation and investment afforded to data governance practices, industry-wide. Ultimately, we both concurred that it has not received the prioritization and investment it warrants, and numerous reasons could be attributed to this. One that stood out was the way it has historically been positioned and sold by data practitioners, in general.
Data governance, a complex and bureaucratic practice
Data governance is often seen as highly complex, vastly bureaucratic, and extremely expensive with absolutely no business value. And data governance practitioners, those tasked with its implementation, are perceived to be solving data challenges from technical data management angles, often resulting in flawed business perceptions. Most organizations are therefore shying away from investing in these initiatives, while practitioners linger on reinforcing similar traditional approaches with little or no success.
I’m in no way undermining the essential role played by data governance in an organizational setting, it is a core component in a business data and analytics journey. My point, however, is that a change in approach is long overdue.
A change is required in moving away from embedding it as a regulatory, watchdog, or policy compliance function, but rather as an essential value stream closely tied to a business strategy. This move, however, calls for data governance practitioners to acquaint themselves with their organizational goals and objectives. And having fully comprehended their business direction and related pain points, they will then be empowered to determine which data elements are most critical and in turn prepare and maintain these sustainably.
A change in perspective towards ‘value-driven use cases’
‘Data improvement and ethical handling’ sounds much better. It’s clearer, less intimidating, and crystal clear in its purpose, but it is a simplified form of data governance. And adopting similar approaches would enable data governance to be more easily understood, thereby increasing its adoption rate and building a strong stakeholder base.
As this develops, data governance can serve as a strategic business enabler, with executive support and enhanced stakeholder involvement. Consequently, businesses will be better placed to enjoy the following benefits, made possible by high-quality, reliable, and adequately governed data;
- Improved data analysis and advanced analytics
- Factual business insights (MI/BI)
- Improved business operations support with clearly defined roles and responsibilities
- Ease of data access in a secure manner
Business value refers to the estimated well-being of a business obtained by measuring concrete and abstract elements such as monetary and non-monetary assets. These measurements are best understood within an organizational setting and are often centered around a problem statement. In data management, value can be measured in metrics such as data accessibility, trustworthiness, usability, and ownership. The required change in perspective calls for data to be positioned as a strategic business enabler with data governance practitioners co-existing with senior business leaders and empowered to contribute to strategic business decisions.
Immediate transformation is required from data practitioners
By ‘expunging’ data governance, the data community in general, and data governance practitioners in particular, should rapidly move away from traditional approaches and fast embrace value-driven strategies. Success in this regard is dependent on the priority placed on the following activities;
- Data governance practitioners gaining clarity on what business value is, how it is defined, how it relates to data, and how it will be measured
- establish a solid understanding of the technical systems and application landscape, with clarity on which data elements are most critical for business
- Practitioners create a capability to promptly provision data when required, in a governed manner
- Practitioners document a data governance stakeholder matrix with clearly defined roles and responsibilities throughout the data value chain
- Practitioners have a clear account of actual and emerging data risk alongside a comprehensive risk management plan
Data governance has historically been seen as complex, bureaucratic, and extremely expensive with little or no business value. Data governance practitioners are often believed to be too steadfast in their adherence to traditional data governance approaches which have seen limited benefits.
A change is required in moving away from embedding data governance as a regulatory, watchdog, or policy compliance function, but rather as an essential value stream closely tied to a business strategy. This move, however, calls for data governance practitioners to acquaint themselves with their organizational goals, and objectives. And having fully comprehended their business direction and related pain points, empower themselves to identify the most critical data elements and maintain these sustainably.
Connect with Sizwe Gwala on LinkedIn.