I started my career in the US as a statistician for NASA, analysing data on quasars and black holes. Two years later, I moved into healthcare, joining the Department of Veteran Affairs (VA), leading statistical research on mental health, the impact of prescription drugs and evaluating services provided by the VA. This was one of 19 VA health centres of excellence across the US. After two years, I moved to the private sector with Health Dialog, a care management start-up at the time, currently a wholly-owned subsidiary of Rite Aid. I held a number of roles over a seven-year period and served as the company director of analytics. Our main focus was on predictive modelling and population stratification for disease management and shared decision-making. In 2010, I joined Bupa, the largest UK health insurer, and set up a new analytics function managing Bupa’s claims spend. The main areas of focus have been evaluation and measurement, provider contracting, care co-ordination and claims leakage and fraud prevention. Over the last two years as the global head of data and analytics for insurance, I have set up a centre of excellence, setting standards globally and supporting local businesses on their path to maturity, setting an analytics strategy, building a data culture and developing talent.
Over the last 20 years, I have worked in analytics roles in different capacities and settings, from an analyst to an executive, across public and private settings and different geographies. As an executive, I have taken pleasure in successfully building analytics teams from the ground up, leading professionals from diverse backgrounds to new levels of success in a variety of competitive roles and fast-paced environments. Changing culture, embedding data and analytics in the core of a business and developing talent -along with delivering business value and successfully demonstrating that - has been the most rewarding element of my work to date.
Be open and engage others in your work. Don’t get frustrated easily and accept others’ differing views and find ways to move things forward even if you have to amend your original intentions. The power and value of insights based on data will help align views and expectations.
I suppose nothing ever turns out exactly the way you expect - 2018 was no different! We have made some great progress in terms of establishing an analytics global centre of excellence within Bupa, but challenges in finding talent, working across time zones and working with fragmented data and ever-evolving data regulations have forced us to amend the way we operate as we go along. GDPR has been long anticipated, but lack of understanding across business functions and the risk of breaching its requirements has slowed us down in some areas and led us to rethink our approach in others.
I am seeing the thirst for data and insights growing bigger globally. As some industries and countries are still in early phases of digitisation, data collection and the methods of big data, I expect the demand for skilled resources to grow strongly. At the same time, technology continues to race ahead, creating great value, but at times also a lot of noise, requiring ever more skill in being able to select the right areas to focus on to minimise the waste of time and resource, the two most constrained resources. Data regulation will be a challenge as everyone tries to figure out what is the right level and where to draw the line.
Getting highly-skilled and experienced people is a challenge. Our approach is to recruit more at entry level and focus on retention. Although it might seem easy to recruit and train, this has its own challenges as retaining talent in a highly-competitive environment is a big task. People at early stages in their career have high expectations, are eager to move around and gather experiences and will chase quick wins. Retaining the ones that you manage to keep through that phase is key and helps retain expertise and specific business knowledge.
Machine learning and AI are quite exciting uses of large amounts of data. Learning from vast amounts of data from past experience which a human would be challenged to process in order to automate tasks and decisions can have tremendous implications for where we focus our intelligence and efforts as a society. I think it can liberate us from repetitive work and allow us to focus on more intelligent areas.