As I enter the ninth month of hosting the Data Empowerment Experts Series of webinars, it’s hard not to look back and think through all of the insights that have already been shared by our experts. The learning process and sharing of best practices was, of course, the original intent of the series. I wanted to bring together leaders and experts from all over our collective customer community to help one another. In this spirit, I find it fitting that our next episode focuses directly on education.
During this month’s installment of the Data Empowerment Experts series, I’ll be joined by Jai (JP) Bhamu, Head of Data Governance for the Department for Education (DfE). He will be sharing how they use Data Governance to deliver actionable GDPR compliance and ensure significant productivity savings for a very large and complex public sector department. You see, at the Department for Education in England, they are leveraging Data Governance to deliver practical and tangible solutions that not only enable comprehensive GDPR compliance during 'business as usual,' but also deliver significant productivity savings by empowering every data user to easily visualize and find 'trusted data' from all the data holdings across the Department.
During the webinar, JP will share his journey in delivering enterprise-wide Data Governance at DfE. Join him to learn how his team is navigating the challenges of setting up enterprise-wide data governance that includes changes to business processes, building policies/processes, updates to the operating model, and delivering an integrated data governance platform for use across the Department. You will also learn how you can effectively address the challenge of scale by building partnerships across the enterprise.
JP’s fast-paced delivery approach is polished by his more than 25 years of experience with setting up and transforming large data and analytics divisions across different countries and industries. He has worked in the public sector, consulting, insurance, energy, and telecom industries in senior executive roles and has successfully architected and delivered enterprise data governance, big data platforms on cloud, data lakes, global data warehouses, MDM, and integration platforms. JP's versatile experience gives him a unique perspective to successfully deliver architecture, design, and end-to-end delivery of complex programs, business change management, and transformations for large global organizations.
As with every episode, I sat down with JP to share his thoughts on the state of data governance:
Question: How do you choose where to start?
Answer: We established the need for data governance early on while delivering GDPR compliance for the Department. It is a foundation pillar of the Department's data strategy set out by our visionary Chief Data Officer (CDO), Neil McIvor. Data governance is a critical enabler to realize our CDO's vision “to provide trusted data for educational and departmental needs” and transform the department to an "insight-driven organization.”
The key term here is ‘TRUSTED’ data. And the challenge is how does one get trust in the data when the same data is spread across different data holdings and used (or abused) very differently in the business processes, digital services due to lack of common definitions, standards, policies, and business rules.
Our first priority was to secure buy-in of senior leaders and directors on the need to have a Department-wide Data Governance Board. So, the first step was to establish a 'Data Governance Board' to provide direction and oversight overall strategic data decisions. This included setting up integrated and coordinated governance by disbanding some of the existing boards and turning other boards into sub-boards of the Data Governance Board. This early investment to set up the right organization structure by way of Data Gov Board (has) paid us well in our journey.
Question: How do you maintain momentum?
Answer: Sustaining momentum can be a challenge for a change program like data governance. We still have our fair share of challenges, especially when it comes to implementing changes to existing roles and business processes. To address this, we took a pragmatic, multi-pronged approach early on and kept on constantly refining/re-calibrating our design, approach, and narrative linked to the wider departmental challenges, and being open to fail-fast.
It is important to build and constantly reinforce a compelling narrative at strategic level. But one’s got to be flexible and constantly (re)calibrate the execution approach by being open to change based on what works and what does not in the organization culture. Some of the things that helped us maintain the momentum in this journey are:
- Delivery approach: Data Governance is fundamentally a change program which calls for a change to people, behaviors, processes, and policies in the way we deal with DATA. Our delivery approach is to do the change WITH people. We have implemented grass root level collaboration across all delivery strands in a pragmatic way.
- Building multiple engaging data stories and constantly reinforcing those and linking the programme deliverables to clear user needs.
- Being sensitive and adaptable to shifting priorities and making tactical adjustments in the journey.
Question: How do you address scale?
Answer: The Department deals with a multitude of datasets for pupils/learners, special education needs, teachers, social care, apprenticeship service, and funding in addition to standard corporate data like HR, finance, etc. We set the overall priorities of the program based on a number of factors such as the likelihood and impact of information risk, efforts required, influence/willingness of key stakeholders. We took multi-pronged approach to address scale by setting up working groups and using automation technology:
- Working groups - Data governance is everyone's responsibility and building early partnership goes a long way in addressing scale. We set up a number of 'Working Groups' to take users in the journey with us, validate user needs and test out evolving solution components in a very agile manner.
- Community of Practices (CoP) - Agreeing on the meaning, implementation and implications of data ownership is a daunting question for most data mature organizations. It is also fraught with common challenges of human behavior like control, responsibility and accountability. We setup 'Community of Practice' made up of business SMEs to co-own some complex data domains and jointly build the business glossary, rules, processes and policies over it.
- Technology as key enabler: This is where the integrated functionality of the Informatica Data Governance solution (Axon, Informatica Data Quality & Enterprise Data Catalog) comes to rescue. We have positioned the Axon tool as a 'Google Map', a one-stop-shop for all data users to discover/search different data sets, data flows, understand applicable business rules and policies applicable to those data sets. The Enterprise Data Catalog is used to discover technical metadata, catalogue and map the data flows. Finally, Informatica Data Quality provides powerful data profiling capabilities which we use to support different projects and services.
Question: How do you measure success?
Answer: We started with soft, qualitative approaches to measure success in the beginning and with time moved to more quantitative KPIs.
Some of the early qualitative measures were the outcomes from orientation and awareness sessions with executive stakeholders and our success rate in rationalizing existing boards/committees. With time, we added some quantitative measures such as number of successful engagements with key business services and delivery projects, getting members for the data governance board, working groups and community of practices. With iterative delivery of the Informatica Data Governance platform, we are moving to much more hard measures like number of databases mapped in the platform, number of glossary items, number of business owners defined/agreed as data owners and stewards, adoption numbers of live projects, capture of GDPR related artifacts — policies, regulations and workflow etc.
Question: How has data privacy been a factor?
Answer: Data Privacy (GDPR regulation) is a key business driver for data governance program. As a matter of fact, we used the GDPR regulation as a key component of our business case early on. We work closely and in strong partnership with the Department’s very experienced Data Protection Officer (DPO) and her team. She has raised the profile of data privacy in the department to the highest level which perfectly support the data governance agenda. This working level partnership enables us to validate compliance requirements and evolving solution in very agile manner to deliver at pace.
Question: How do you empower the business to drive value?
Answer: For us, the first step in empowering business is to provide a (self-service) capability that enables easy visualization of what data exists where why in the department, its quality and the business rules/policies associated for its legal & effective use. The program is delivering this capability as 'Data Estate Map' with an associated assurance framework that defines new roles, responsibilities, processes and checkpoints for its effective adoption across the Department.
The Data Estate Map will empower each and every data user to easily find the data they need with all associated compliance, business & technical metadata in one place. This will provide assurance on the legal use of the data and result in significant productivity savings on time we currently spend.
We are empowering different business services by providing them data profiling capabilities and assurance on legal and appropriate use of the data. Don’t miss out on the next episode of the Data Empowerment Experts Series. Register to attend the webinar or watch it on demand.