Kevin Hellon -

Case study: Seeing clearly with data at Specsavers

Helen Mannion, director of global data and business transformation at high street opticians firm Specsavers, opens up about the importance of data to the organisation

Specsavers opened its first high street opticians branches 40 years ago. Since then the business, which is still family-owned, has grown to more than 2,000 stores in the UK, Europe, Canada and Australia.

The company now also provides audiology (hearing) services, and has more than 6,000 employees. It is well-known for its “Should’ve gone to Specsavers” advertising slogan, which was first used in 2003 and has since gone on to become an everyday catchphrase.

More seriously, the business also has a strong purpose, promoting eye and hearing health in both the UK and further afield. Specsavers opened an optometry training centre in Zambia in 2012.

The business’ rapid growth, though, masked some challenges. Although Specsavers captures a lot of data, its systems for processing data and sharing that information across the organisation lagged.

Helen Mannion, the company’s director of global data and business transformation, joined Specsavers in 2019. At that time, most data were captured and shared using spreadsheets, she recalled, during a presentation at the recent Big Data and AI World conference in London.

“When I joined the organisation, it was a very immature data organisation,” she said. “I took over a team of five people and predominantly their job was to extract data from a variety of systems into CSVs.”

Organisational change

When Mannion arrived, colleagues fell into three broad categories.

The first were sceptics, who felt that the business was growing well, and Excel spreadsheets did all they needed.

The second group she described as “despairing” because they were unable to access the data they needed to do their jobs, and did not believe that Mannion could make a difference.

The third group could see the potential. “They were real advocates,” she said. “They’d say, ‘We really need to uplift data in this organisation. But you’ve got a big job. I don’t really want to be in your shoes’. They were the core three opinions that I came across in those first couple of months.”

Undeterred, Mannion and her team set three core goals.

“The first was to establish data culture, second to enable self-serve, and the third was to deliver priority projects,” she said. “Our first was around clinical reporting.”

Improved clinical reporting quickly proved its worth as the Covid-19 coronavirus pandemic hit the UK and the country moved into a series of lockdowns.

During the first lockdown, Specsavers’ clinicians spotted a worrying trend in the data Mannion’s team provided. The number of people being referred to hospital ophthalmology departments had fallen by two-thirds. The result could have been glaucoma, causing avoidable blindness.

“Clinicians spotted that, from the reporting that we’d given them, lots of people were not going to be referred. The impact of that would have been a lot of people going blind who could have been prevented from blindness,” she continued. Clinicians and charities, including Glaucoma UK, used the data to lobby for opticians to stay open during Covid for both emergency and routine care.

The change of policy will have saved “hundreds” from avoidable blindness, according to Mannion. She is understandably proud of the outcome, even though the data application was designed simply to help clinicians monitor their referrals, but because subject matter experts could view the data, they were able to identify the problem in time.

Specsavers’ store staff are given an app to monitor data, and Specsavers’ goal overall is to give more people access to it, but also ensure that having better access to data brings value to the business.

“Five years on, we’ve won multiple awards. One was for our technical reports, which have actually protected hundreds from avoidable blindness,” said Mannion.

“We’ve now got 300 users coding on our platform and 10,000 people utilising our reporting systems on a regular basis. We’ve got about 500 people coming in and making use of the data training that we’re providing.

“We’re also 16 times larger today than we were back then, and we’re about team of about 90,. I’m really proud of what we’ve achieved within that time.”

Monitoring success

More investment in data science, and a larger data team, come with more scrutiny, Mannion conceded. So, the data team needs to prove that what they do adds value.

“People start to worry and care a little bit more,” she says. “Actually showcasing value and being really clear about where that value is really important. I’m a big believer that value can come from many things – it doesn’t have to be monetary; it could be saving people from avoidable blindness. 

“But as an organisation, you have to be clear about where you want your value to come from. How are you going to measure and evidence it? You need strong, clear agreement and approval for what you’re going after, and how you’re going to showcase that value.

“And [making] mistakes is inevitable. And, actually, it’s a thing that helped us ultimately grow and develop,” she said. Part of the journey to a business that drives more value also means seeing out “honest feedback” from people who might not be data advocates.

“I’ve been working in data my entire career,” said Marrion. “The words and language that we use around data are obvious to me, but not obvious to others. But the business needs busness language.

“Apart from data professionals, no one really cares about data – what they care about is delivering their business projects and assets. So, we need to stop talking about data, and start talking about things that matter in the business.

“We’re looking at explaining it in terms of a lifecycle. We collect data, we store data, manage data. Maybe rather than talking about data products or foundations, we’re trying to get into the concept of what would you do if you had a piece of data in your hand, and whether that would work.”

As with the discoveries that led to a change in national policy over optical care during Covid, sometimes the true value of data only becomes clear when you can look at it from a different angle.

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