How is your organisation using data and analytics to support the corporate vision and purpose?
Data and analytics are critical to DWP’s ability to understand the issues that the UK is currently facing, and to ensure that we are delivering an appropriate and effective response. To that end, we have developed and published the department’s first data strategy to directly link data analytics to the delivering of the DWP business plan and is linked to the National Data Strategy.
This has enabled us to shape a new data reference architecture, using the principles of data mesh, to support the re-architecting of DWP from multiple, segregated, lines of business onto a single logical application reference architecture, which will support improved analytics, segmentation and service delivery personalisation, as well as improved fraud and error detection.
This is all focused on supporting the most vulnerable in our society and rebuilding the labour market.
2020 was a year like no other - how did it impact on your planned activities and what unplanned ones did you have to introduce?
Our year starts on 1st April, so we were straight into the immediate crisis response which meant that we rapidly had to reassess and adjust to the new circumstances: 22,000 colleagues temporarily unable to work as they did not have mobile workstations; no longer able to undertake face-to-face identity verification for new claims; massive growth in data volumes; huge increase in attempted fraud; demands for new and more frequent MI; and deeper and more urgent analytics requirements.
The first lockdown, and the temporary reduction in DWP capacity, meant that we needed to develop new people and workplace analytics overnight in order to understand the dynamics of demand for DWP services and the supply. This meant we had to scale prototype cloud analytics workspaces and bring legacy data we had never previously used into modern, virtualised environments, alongside system data that we had never used for such purposes. This push has enabled us to get to the most accurate and dynamic productivity analytics that DWP has ever had.
The lack of in-person identity checks forced us to use a range of new data sources to validate a new claim, primarily existing government identities such as HMRC’s online tax accounts. This has been an acceleration of plans that we had been working on and proved that this was both possible and led to improved customer service.
We had to put a lot of effort into basic data architecture and engineering as the pandemic blew our data growth models for the year, meaning that we needed to rapidly increase our OPH capacity and accelerate planned performance improvements on our cloud platforms. Again, this has been hugely beneficial as it has provided the impetus for addressing data technical debt.
New demands for more frequent and deeper management information have accelerated our plans for enterprise reporting. Before the crisis, we were only reporting on a weekly basis, but we were very quickly having to provide intra-day updates on Universal Credit directly into the COBRA briefings.
Finally, we were able to harness the ingenuity of the cross-Government data analytics community to solve incredibly urgent problems such as the Vulnerable Persons Service, when clinically vulnerable citizens were directed to shield. Working with NHS colleagues, we set up a first-of-type data trust in order to rapidly match and segment based on priority. This information was then shared with partners to deliver supplies or direct emergency services interventions.
This year has demonstrated the power of small teams of data analytics professionals and has delivered urgent and, in some cases, lifesaving support to our fellow citizens.
Looking forward to 2021, what are your expectations for data and analytics within your organisation?
Our primary focus will be on the labour market and supporting the Plan for Jobs across the UK. This will mean improved place-based analytics and local labour market intelligence to support jobseekers, employers and local economies to build back as quickly as possible.
We will need to put a lot of effort into hardening the data estate as we have moved at such pace and claimant volumes have increased significantly during FY20/21 that we need to continue to develop our data non-functional requirements to maintain performance.
We have a large number of additional pieces of work in the pipeline too. For example, we are supporting the move to an electronic national census with the Office for National Statistics (ONS); we will be developing the minimum viable product (MVP) for the new data reference architecture; we are evolving our data governance approach to one of adaptive data enablement (ADE) and improving the operating model for data throughout the organisation; finally, we will be working with wider colleagues to ensure we support the UK’s exit from the EU and enable elements of Scottish Devolution.
This is a hugely exciting and energising year ahead.
Is data for good part of your personal or business agenda for 2021? If so, what form will it take?
The extent of DWP’s reach is within the boundaries of the UK but, within these constraints, we are committed to data for good as a number of sustainable development goals are part of the department’s core mission set: our analysis on the Family Resources Survey and Households Below Average Income enables us to support work to address poverty; improved local labour market intelligence will help DWP support decent work and economic growth; we are constantly innovating and our progress towards data mesh will be a key part of this; and, we are developing analytics that will assist DWP in supporting the UK journey towards net zero.
What has been your path to power?
My career has always been focused on the use of evidence-based decision-making, from my early career developing operational analysis in the Army, which led to my first civilian role using statistical process control in the insurance sector. This enabled me to develop my technical data and analysis skills in preparation for a move to Accenture, which provided the opportunity to develop a really deep technical skillset.
During my eight years at Accenture, I worked up through the development of database schemas for SAP materials management to the cleansing and migration of over 60 million unique taxpayer records at HMRC as part of the Modernising PAYE Processing for Customers programme. During this time, I was also able to undertake more experimental data and analytics work in the medical imaging sector, which allowed us to identify the root causes of relatively high cancer mortality rates in Brazil.
In 2012, I moved on from Accenture into increasingly sophisticated data programmes at Detica and the Home Office, during which time I was responsible for developing social media analytics, biometric analysis and more traditional data warehouse design and build. This led to a fascinating opportunity at the National Crime Agency to build the data and analytics capability required to implement the National Cyber Security Programme.
In March 2017, I was fortunate to be appointed as chief data officer for the Department for Work and Pensions. The scope of this role is awesome – I have a team of 550 data engineers, data managers, data scientists, statisticians and software developers, who are responsible for one of the largest data warehouses in Europe and for ensuring that we are able to support over 22 million UK citizens in times of need.
The consistent theme throughout my career has been the use of data and evidence to create insight in support of UK citizens, something I am very proud of.
What is the proudest achievement of your career to date?
My proudest achievement continues to be my work at DWP, especially over the past year as we have had to work extremely hard as part of a much wider team to support people during the most complex and stressful periods in their lives. This gives the whole team a huge sense of purpose, in order that the right support is delivered to the right people, at the right time.
Tell us about a career goal or a purpose for your organisation that you are pursuing?
The goal we are jointly working towards is the enablement of an improved welfare data eco-system. The intent is to work with partners across government in order to improve the join-ups between datasets so that the citizen has a better experience of engaging with services at stressful times in their lives. This requires us to modernise our data architectures, change our data operating model and build new capabilities within the organisation. It will be difficult but rewarding and it will enable DWP to deliver better services to users and the taxpayer.
How closely aligned to the business are data and analytics both within your own organisation and at an industry level? What helps to bring the two closer together?
Much more closely than in previous years.
This year we have made much greater efforts to develop the alignment between service delivery and data by pushing data teams further upstream, so they are closer to the user need and are developing thematic specialisms. This has really paid off in parts of our business such as Universal Credit, health, counter-fraud, finance, and people and capability. As a result, we are seeing some genuine innovations that have directly improved citizen outcomes.
For instance, in UC, the stream-aligned data team have developed natural language processing that flags claimants at risk of self-harm, which leads to proactive outreach to support that person. This approach is being adapted to help us identify other vulnerable individuals and to help protect our staff.
As a result of embedding a data team in the finance group, we are now rapidly scaling our self-service enterprise reporting service. This has taken away a huge amount of manual report collation for every period and has established a commonly held single version of the truth around reports which has changed the nature of conversations across the organisation, from debating the veracity of the information to focusing on outcomes.
What is your view on how to develop a data culture in an organisation, building out data literacy and creating a data-first mindset?
Data teams must be part of the business in order to understand, respond and coach towards a more data literate/data-first ethos.
This takes a lot of time and engagement if this is not the natural way that an organisation operates. For us, this has been a four-year journey so far, and we have a long way still to go. However, putting the right data people in the right places, and steadily building credibility, really helps build support for a more data-led approach.
It also requires a lot of effort on non-data capabilities, such as strategy, comms, engagement and operating model design, which means that we have had to develop a much wider skillset in order to continue on this journey.