Beyond Data Governance:
Discussing the Evolution of Data Governance, featuring Patrick Dewald and Darius Clayton of Diaku
What is it like to deliver data governance capabilities into large organisations on the front-line and what should organisations be doing to go beyond Data Governance?
These are just some of the topics I put to Data Governance practitioners Patrick Dewald and Darius Clayton. They form part of the team at Diaku, a company that specialises in Data Governance services but who have also been winning praise for their innovative Axon Data Governance software.
Dylan Jones: Thanks for joining us today. So what are your backgrounds, how did you both get involved with data governance (DG)?
Darius Clayton: My early career was in software design and development before moving into business analysis and change management. I worked for several years for one of the big consultancies, delivering large-scale business process outsourcing – a business transformation role that involved a lot of collaboration with operational teams and tight cost management.
Working across multiple disciplines let me see the different data issues faced by various groups and how these issues cost the business. In 2007 when I was tasked with operationalising a DG service across a wholesale bank, I saw the value that DG could provide and that was me hooked!
Patrick Dewald: My first project was a large client system implementation and I was lucky enough to be involved from the very start until successful rollout across an entire wholesale division of a global bank which took the best part of four years. That was a period of immense learning for me, both on the hard core data side as well as the softer side of reconciling competing views and trying to change attitudes.
My next project had to be a data governance project, and it was. This was 2004 when banks were starting to implement Basel II.
Dylan Jones: I was talking this week to a financial organisation that is attempting their second try at data governance. Why is that so many organisations are struggling with data governance when there are more consultants, books, conferences and training resources than ever before?
Darius Clayton: It’s always going to be difficult to try to do something when it has failed before – people remember. To change their minds you need to be able to articulate the value of DG; not just at a company level, but also for each party being involved. But even if it’s a first try it isn’t easy; DG needs effective collaboration between stakeholders. Since data is used by everyone in the business, that’s a lot of involved parties to get working together.
Data governance is a bit like a health kick – you can buy the books and get a personal trainer, but no-one can do it for you. You have put in the effort to see results. For organisations, that means changing behaviours around data, which goes beyond policy and traditional data roles.
Patrick Dewald: We were faced with the challenge of wavering support in our data governance implementations when the drive of the big change programmes at the time like Basel II, IFRS etc. started to fade.
Classical Data Governance implementations typically have a top down approach and manifest themselves through roles, committees, policies and maybe the odd data dictionary. These components may excite data people but do not engage nor bring much obvious value to the day-to-day of most business users.
The key to doing better around data, collectively as a firm, is to create a better understanding of data and its usage. Shared understanding brings people closer together, builds engagement and lowers barriers to changing behaviours. Making data understandable is what builds lasting traction and empowers people. Collaboratively creating and maintaining that corporate understanding is what has been Diaku’s focus in recent years.
Dylan Jones: How can organisations overcome the problem you cited above, the issue of dwindling support when the regulatory initiative everyone has been focused on starts to fade and lose urgency?
Darius Clayton: Support from senior management is always finite, so it’s important to use it while you have it. To survive beyond the sponsorship phase any DG initiative must prove its worth to its stakeholders.
Two key objectives:
Demonstrate that DG works by supporting a key project or programme and publicising the successes;
Build and embed a set of practical services that promote participation and help the day-to-day activities in the business – sharing information, bringing the right people together, providing a trusted go-to point for data issues etc.
If the DG function provides valuable services to its stakeholders then ongoing support won’t be a problem.
Patrick Dewald: Often data governance initiatives do set out to solve a specific data problem but overlook also addressing the environmental problems that prevent the organisation from making better decisions around data i.e. what Darius described in services terms. Creating the necessary conditions and environment to allow people to collaborate more effectively around data can not only be a great boost in terms of support, it also empowers people to address their day-to-day data challenges and by doing so unlocks value beyond the initial business case.
One wants to make it as easy as possible for people to find the right answers to data related challenges & questions, so aligning with and leveraging what is there becomes the norm, rather than unwittingly adding to the chaos.
Dylan Jones: You state that your mission for Diaku is to help companies go “Beyond Data Governance” – what do you mean by this?
Darius Clayton: Data doesn’t exist in isolation. It exists for a business purpose.
If we want to ensure data supports the business, we need to look beyond data and include its business context.
Our approach is to create a shared view of the business, with data at the heart of that view. It means that regardless of your focus (processes, projects, semantics etc) you can find the data relevant for you, share your perspective on that data, and see how other people use it.
In the same vein, change is a collaborative enterprise. To improve the data landscape we must change the business – processes must be modified, systems changed, reports revised etc. To manage this we need to look at an accountability framework beyond data roles. With roles and responsibilities linked to each facet of a shared view we get the ability not just to think together, but also to act together.
So what we really do is break down barriers across the business to facilitate quick, easy communication and collaboration.
The tools and methodology helps us manage our data objectives and empower local teams to work in a more connected way across the organisation, which is a huge part of being data-responsible.
It takes data governance beyond committees and fora, and makes it part of the day-to-day working practice for everyone.
Patrick Dewald: One could almost argue it is not about data. Data governance should mostly be about creating an environment of understanding and collaboration, to empower everyone to implement changes quickly knowing one is aligned with set standards and strategic direction.
Some very successful organisations are faced with a very fragmented, duplicated and suboptimal data landscape, not because of any specific property of their data but because the environment beyond the data is simply not in place to make well informed and joint up decisions.
Dylan Jones: Many practitioners and authors who write about data governance are openly opposed to the term. What are your views?
Darius Clayton: It’s not ideal. As data governance has matured the term has become too narrow to describe the discipline, its activities and its objectives. The data governance industry has also struggled to stay aligned in its definitions and application of data governance, with some practitioners and tooling vendors still offering early interpretations of DG that have limited value.
Having said that, the phrase “Data Governance” has a lot of ‘mind-share’ and is recognised as a key business function, which is important. It’s our job to educate the business about what DG has developed into. At some point that may transition to new terminology, but that takes time. Whatever your opinion on the term it’s one we’re going to have to live with for a while.
Patrick Dewald: Indeed some practitioners oppose to the term, since governance could trigger connotations of bureaucracy and other less than favourable associations one has with government. If your data governance deployment shows some of these characteristics, this image is reinforced and you are in trouble.
Dylan Jones: Why did you feel the need to create a Data Governance software solution?
Darius Clayton: Our methodology is based on some key principles:
Data is used by everyone, so everyone could be a stakeholder;
Stakeholders need to see data and its context from their own perspectives;
A data governance initiative must bring data awareness into the daily activities of the business, and
DG activities must be valuable to all the members of the community to ensure lasting success.
We looked at the market to see if we could satisfy these needs, and we couldn’t find a product that worked for us. The most common challenges were that the tools were either on the technical side (and so wouldn’t engage the business community) or that the tools were so focussed on a specific user group that they didn’t provide the breadth of understanding our DG approach requires.
One of the toughest things to deal with is the licensing model for most applications. When you have limitations on users or hardware you are providing a financial incentive for the client to reduce the number of people who can contribute to your DG initiative, either limiting them to the sidelines (view only) or with them having no access at all. This is amazingly counterproductive. With our own platform we can remove this problem, making data governance something that really can be for everyone.
Patrick Dewald: We had an extensive look at the tools out there under the Data Governance software banner and none of them supported the collaborative, knowledge driven model we advocate and definitely not in a modern 2.0 manner; so we built one ourselves.
Both of us have a background in software implementation and we managed to build a great agile development capability. Only after three years of battle-testing the software in the most challenging wholesale banking environment did we feel the software was good enough for us to reach out to new clients.
In 2013 we started approaching financial institutions in our network and we are currently deploying the solution with a number of those clients.
Dylan Jones: How does the product accelerate or simplify the data governance challenge?
Darius Clayton: We’re a data governance consultancy firm with a methodology and approach to data governance that gets the business involved and brings value to the organisation.
Our product is designed to support that process in a progressive manner from day one with a very low learning curve. Given the collaborative nature of the process and tool, many user groups are invited to make a small contribution each, only around what they know best and as a result allowing to chart or discover an area very quickly.
Axon creates data understanding within a rich context. Axon can take context input from depth tools like technical meta-data tools, BPM tools, project & policy directories, semantic modelling tools etc. By leveraging and connecting what is already there one not only creates a richer understanding, but also brings the disciplines and communities together. If we are all looking at the one connected view seeing the whole one can make changes fast and with confidence.
Patrick Dewald: Axon provides what we feel is the missing ingredient in most data governance deployments i.e. a platform for and by the business to progressively build their view and understanding of data and the context in which it operates. Having people take ownership on the basis of a shared understanding is so much more productive.
In creating that business understanding Axon goes well beyond the classical data glossary tool. Understanding requires the rich context in which the data operates to be captured, namely the data connections into processes, reports, calculation, change projects, regulation etc. This focus on understanding within the business context and allowing it to be built up progressively and collaboratively is what sets Axon apart from anything else in the market.
Dylan Jones: Earlier you talked about “creating an environment of understanding” for everyone in the organisation. What type of user groups are accessing or using the product? Have there been any surprises in groups that you never expected to see using the tool?
Patrick Dewald: Data is everywhere in the modern firm and most members of staff are creating or manipulating some data on a daily basis. We want to empower every user group to leverage and contribute to a better understood and leaner data landscape.
That said, the initial build up of the knowledge base relies on those subject matter experts in the different lines of business (e.g. FX trading, Loans servicing etc.) or functions (Operations, Finance, Risk etc.) who can make a start by extracting the core elements from existing data documentation or by lack thereof starting afresh.
As soon as an initial description of data elements has been captured, the other disciplines can get involved in connecting those up: process people describe processes and connect those to the data and MI, Regulation, System, Policy etc. people would do the same for their objects.
The moment some critical mass exists, the change community typically joins in and the interactions with knowledge repository become multi-directional and in tune with business priorities rather than through a set data take-on process.
The biggest surprise during our first large scale implementation was to see very senior people logon. Their feedback was that for the very first time data had been expressed in understandable terms within a business context they could related to. The insight gained allowed them to make better informed decisions around their data challenges and implementation projects.
Needless to say it was a welcome surprise!
Dylan Jones: Why do you think the product has been so well received in the finance sector?
Patrick Dewald: Many financial institutions have grown quickly through mergers & acquisitions which leaves them with quite a challenging data landscape. The financial crisis has added further strain on their already stressed data capabilities in terms of risk reporting and additional regulatory pressures. Although the data related spend has increased year over year in most large firms, there isn’t an increased confidence that the data problem is being addressed at its core.
Our collaborative approach not only empowers an entire firm to contribute, it also allows the crowd-sourced view to be analysed, measured, baselined and improved. In times of scarcity being smart and responsible about deployment and configuration of existing assets is a message that resonates particularly well.
Patrick Dewald is a Data Governance Architect and founding partner in Diaku. Patrick has a wealth of experience designing Master Data Management and Data Governance solutions for financial institutions. He has been heading up Data Governance initiatives, designing and implementing group-wide data services from the ground up for the best part of 15 years. Patrick is recognised by his peers as a thought leader in the field of data governance.
Darius Clayton is an experienced data professional and founding partner in Diaku. With a strong background in business transformation and outsourcing he brings a practical, value-driven approach to data disciplines.
Since 2007 his focus has been on data governance, collaboration, and the business view of the data asset. Darius has spent the last six years working with financial institutions to control and improve their data while delivering tangible business benefits.