Data Governance – An Engine for Innovation?

There is a bit of a kerfuffle happening in the world of Data Governance. From Laura Madsen’s book “Disrupting Data Governance” back in 2019 to Redman, Ladley et al calling out the failing of Data Governance in CDO Magazine earlier this year, to John Ladley and Bob Seiner collaborating on a call to reset the narrative on Data Governance, a lot of people are saying the quiet bit out loud now. And if we throw the recent noise about reform of GDPR to reduce “red tape” we have an interesting turmoil to unpick.

All the right notes, just not necessarily in the right order?

The Morecambe and Wise Christmas Special in 1971 featured Andre Previn and ends with Eric Morecambe delivering the punchline: “I am playing all the right notes. Just not necessarily in the correct order”. I think this might sum up where we are and where we have been in the world of Data Governance for the last thirty years – we’ve been doing (mostly) the right things but not necessarily in the right order or for the right reasons.

Redman and his co-authors in CDO Magazine identified several restraining forces that have held Data Governance back, ranging from knowledge and training to organisational issues and people issues to a simple lack of understanding of what Data Governance actually is. Ladley and Seiner go a little further and call out specific points of misinterpretation of what Data Governance should be. In my own TDAN.com column last month I chipped in my perspective on the issues.

But, regardless of how we come to the diagnosis, the fact is that slavish adoption of “three level models” and tick-box approaches to developing oversight and controls, often driven by a technology focus or bias (because the “data thing” obviously has to be an IT function) has brought us to a point where we continue to have high failure rates and governance of data is often seen as a burden rather than a necessary overhead in the organisation. The focus on form rather than function has hampered adoption and is, I would suggest, what has prompted discussion of “red tape” reduction around GDPR and other data-related regulations.

Business First Data Goverance

Data is at the heart of everything we do. It is, as John Ladley puts it, “the 24×7 recording of human existence”. Simply put, data is created as a record of an interaction between people or things to evidence that that thing happened or to document important attributes of that thing. From automatically generated log data to your cat pictures, the creation of data is the recording of a thing. And some of those things are important to enable organisations to deliver services or generate cashflows. That’s what makes some of those things valuable as assets.

If data is, in fact, an asset it needs to be managed by the organisation as an asset. That means having systems and processes to know what you have, why you have it, and where it is. It means having to think about when that asset is past its ‘use-by’ date and should be retired or disposed of. It means having to think about what your legal basis is for having that asset and what might constrain your use of that asset, and what might constrain how others might use that asset.

Not all ‘stuff’ that an organisation has is an asset however. The ability of something to be an asset depends on what the objectives and purposes of the organisation are and whether the ‘stuff’ is of an appropriate level of quality or usability to enable the organisation to do that ‘stuff’. This is true whether the asset being talked about is people, plant and machinery, paper clips, or data. Broken down machinery or poorly maintained equipment in a construction business is at best a maintenance money pit and is more likely a liability timebomb. Data is no different.

The key issue for data governance is we need to govern data as an asset of the organisation. That means paying attention and prioritising what the organisation needs to be able to do with that data and what are the risks to the organisation that can arise from having that data.

The role of Data Strategy

Controversial statement: Not every organisation needs a formal data strategy and you don’t need to wait for a full blown data strategy to get started with Data Governance. What you do need though is a clear understanding of the ORGANISATION STRATEGY which you can map data needs from. That may evolve into a Data Strategy, but I’m not a fan of the proliferation of strategies in organisations. We are, I feel, one step away from Gartner recommending that companies need to have a Cappuccino Strategy.

Keep it simple. And when you do start to define a Data Strategy make sure it is aligned with the organisation’s strategy and priorities and supports the translation of key business priorities into data objectives. The role of data governance then is to ensure that the execution of that strategy to meet those objectives stays aligned with the Organisation strategy and co-ordinates and oversees how data is put to use in the organisation. This is no different to the financial governance of an organisation that makes sure that the raising and spending of finance and the booking of billable time and management of invoicing and credit are being done in a way that is ensures compliance with law and supports the strategic financial goal of (at its simplest) taking in more money than you spend.

Balancing Governance and Innovation

Data Governance requirements such as the GDPR’s requirement for organisations to have a Register of Processing Activities are flagged by some as being “burdens”, and it would appear they are up for the chop in a culling of “red tape”. But all a ROPA is at its simplest is a list of the important things the organisation does to do business, the data they need to know to do that, what their legal basis is for doing that, where that data is stored, and details of 3rd parties involved in the process.

Please tell me where there is something there that an organisation wouldn’t benefit from from having it documented. The problem is it is overhead. And when it is only done for the purpose of ticking a box to comply with the law it’s not valuable overhead. But if the process is used to keep a focus on processes and to identify opportunities for improving efficiency, reducing waste, simplifying processes, or managing risk, then that overhead has value.

Data Governance that is approached in an overly mechanistic way and which is shoehorned into a cookie-cutter 3 level model with rigid adherence to a standard or reference model will inevitably fail as it will be seen as a barrier and a blocker to innovation. Data Governance that is aligned to the business objectives and is positioned as the “critical friend” to innovators can thrive as it is contributing to value delivery. That’s not to say that Data Governance should roll over and have its tummy rubbed – but it needs to be seen as a GUIDE DOG not a GUARD DOG!

They are already playing the notes

Your organisation, regardless of its size, is already governing data. It’s just being done inconsistently, unconsciously, and without any formalisation of guiding principles or processes. Your colleagues are already playing the notes. They just might not be in the right order. And they are possibly playing different songs in different keys (and Marketing has just turned up with a kazoo).

The role of Data Governance and Data Governance leaders is to bring the orchestra together to get everyone playing the same song, in the same key, at the same time. That requires a focus on tempo not templates, change management, and people and process behaviours rather than tools and technologies.

Your organisation is already trying to (and potentially is succeeding) in innovating. They may be adopting new technologies and tools to capture data in frontline contexts. For example they may have mobile devices or sensors to capture data about things that are important to one process or function. But they might not have thought about how that data might need to be integrated into the organisation’s wider data landscape. It might be a proof of concept or academic research project that now needs to scale up to a full blown enterprise roll out that requires different or additional regulatory or process considerations.

To stretch the musical metaphor… you may find lots of people in your orchestra standing up to do solos. But unless they are playing a solo that relates to the structure of the overall piece and unless the different solos are not overlapping and clashing, you’ll be left with a discordant mess. Or Progressive Jazz.

So, the role of Data Governance and Data Governance leaders is to guide the innovations to ensure that they can align with each other and with the data strategy and organisation strategy.

But what about the technology agenda?

Technology changes and evolves. That is one of its strengths and its weakness. Data persists. Having a clear orchestration of data and the roles, responsibilities, and structures and formats for data helps us to make smarter choices about the appropriate technologies for our organisations. It also helps sharpen the understanding of requirements for implementation of technology. This helps de-risk technology projects. But it also makes it easier to evolve technology architectures to deliver greater benefits and mitigate risks.

Grieg’s Piano Concerto does not sound as impressive when played on a kazoo or a ukulele. The objective of the performance guides the governance needs and directs the selection of appropriate technologies to deliver.

The end goal for Data Governance needs to be the right notes, played in the right order, for the right reason, on the right instrument!