Recently we sat with Ursula Kuni, the Chief Data & Analytics Officer at Hollard, to ask her about her strategy and the future of this role in South Africa.

Ursula, you’ve spent the last 8 years or so in a senior data analytics role - what path did you take to get to where you are? 

I started my career in management consulting with Bain & Company, one of the leading international strategy consulting firms. In 2002, I moved into the data analytics space when I joined Capital One. Capital One was one of the pioneers in this area – an unsecured lender with a business model that was focused on differentiation through analytics and “Test & Learn”.

In 2009, I joined Edcon after the acquisition through Bain Capital to build their Data & Analytics capability. Retailers typically sit on masses of shopper data and this was the time when retailers increasingly invested in driving value from their customer data. After 6 successful years at Edcon I joined Hollard to lead the Group on its journey to drive better decisions and bottom-line value by leveraging data and advanced analytics.

You’re now the Chief Data & Analytics Officer at Hollard and so you’re part of a small group of C-levels in this position in South Africa. What were the reasons behind Hollard appointing a CDAO and what are your main strategic objectives? 

Insurers generally have lagged other industries when it comes to adopting analytics outside the immediate Actuarial space. A big part of Hollard’s business is generated through our partners – brokers, retailers, banks, motor dealerships – and our partners traditionally own the customer relationship. And the customer data. However, our partners increasingly look to us to help unlock further business value through understanding customer behaviour and leveraging advanced analytics.

In addition, regulators over the past few years have put more pressure on insurers to understand their customer base. This gave rise to the creation of the CDAO role for the Group back in 2015. The main objectives of the role are to enable management to drive better decisions based on data and to drive innovation through analytics – across the value chain. In addition, we are focused on enabling effective and efficient regulatory and compliance reporting.

What are some of the biggest challenges you’ve faced, and overcome, in your 2 years at Hollard? And what have been some of the key factors to your progress and success? 

Given the complexity of the Hollard business with various partners and different systems that house customer and other data accessing good data sets for insights and analytics was ,and in some cases still is, a big challenge. Our technical infrastructure was also outdated which impacted the ability of the team to access and process data quickly. Over the past two years we have done a lot to improve access to data for the Analytics Team – we introduced a new infrastructure and developed warehouses and marts. While we are by no means at the end of the road we now have key data sets accessible to the team and the business.

We also spent considerable time on recruiting and developing the right talent for the team. A good analyst (today often referred to as a data scientist) combines strong maths and coding skills with sound business thinking and problem solving abilities. In addition, (s)he needs to be able to work and communicate effectively with business leaders around the Group. While they are not unicorns this talent pool is still limited in South Africa.

While we spent considerable effort on laying data and talent foundations we were very clear from the beginning that our journey needed to be led by visible value generation. As we recruited, built and developed the team we mapped onto each of our businesses and worked with the business teams to identify opportunities to drive value through insights generation and advanced analytics. This way, we quickly built success cases which demonstrated the value-add of data and analytics to the business. At the end of the day, bottom line matters. Having senior leadership visibly supporting and driving our journey is key.

There’s a lot of talk about the increasing role of AI in business. What are your thoughts on the application of AI, Machine Learning, Deep Learning etc. in your environment? Has it always been used or just coming into play now? And does business get it and, do they need to? 

Thanks to the generation of massive amounts of data in our digital world combined with the evolution of our ability to process these vast amounts of data effectively and efficiently the field of analytics is advancing fast. But it is still an evolution from more basic analytical techniques some businesses already used many years ago. I find the term AI is often misused and applied to a wide range of techniques and approaches – some of them not much more sophisticated than what was possible and done decades ago. Having said this there is no doubt that new algorithms and methods in the space of machine learning, AI and deep learning are evolving fast and finding their way into business applications.

I don’t think everyone in business will “get it” as these methodologies become more and more specialised. Key will be that business has a strong translator in the middle – someone who is close to business, understands priorities and opportunities and at the same time understands where new analytical approaches can add value and bring them in as needed. The other important aspect to realising value from analytics is the ability to operationalise AI, machine learning and other solutions – i.e. successfully and sustainably embed them into workflows and decision processes.

I’m currently focused on understanding skills development initiatives in South Africa to increase the future pipeline of data analytics candidates. Do you have any thoughts on what should be done to ensure that more kids are interested in data science as a career? Do you have any grad programmes at Hollard and if so, are they proving to be successful? 

There is no question that one of the biggest challenges to making data and analytics work and deliver the right bottom line impact in South Africa is talent. I earlier described what a good data scientist looks like. McKinsey a few years ago predicted a shortage of close to 200 thousand data scientists and 1.5 million analytically minded managers by 2018 in the US alone. One can only imagine what the equivalent situation in South Africa is. Developing strong talent starts at root level – at schools and then universities. Children need to be shown what is possible and need to be encouraged to engage in subjects like maths and engineering. This is where typically a lot of the people come from who have been successful in our field.

Our parent company Yellowwoods launched the Harambee Youth Employment Accelerator in 2011. To date, we have placed 40 thousand unemployed youths and we want to double this number by 2020. A focus of the programme is on data skills. In addition, we are starting to focus our recruitment efforts on universities that offer relevant subjects. Universities are increasingly introducing curricula that specialise in fields like analytics, robotics, data science and machine learning.