Big Data, Big Hype or Big Opportunity? with Specsavers' Helen Mannion

The importance of being a data driven organisation goes well beyond the world of customer. Making informed and speedy decisions and utilising customer feedback is imperative in today’s age where markets and economies can change very suddenly.

We were lucky enough to hear from the Global Data Officer at Specsavers Helen Mannion who has been leading the charge of building an internal culture that has data at the heart of everything they do.

Emma and Helen share stories on using data to drive a strong customer experience, the challenges of building that culture internally and even sheds some light on where the future of data and analytics is heading.

This one is not to be missed, so please enjoy the show and please hit the subscribe button to make sure you don’t miss another episode.

• Harvard Business Review - to compete today, companies need to be data-driven
• Culture is the biggest barrier to enable data-driven transformation
• Important to understand the value that data can bring

• At Specsavers - creating data assets (platforms/tools/accessible)
• Showcasing value -demonstrations
•  Create a culture of sharing - creates a ripple effect across the business

• You need to be willing to share and train others
• Team spirit - our stakeholders aren’t different, we’re all in it together
• FOMO if people aren’t sharing these stories gleaned from the data

• 66% drop in referrals during lockdown to opthamologists 
• Shared with NHS and Glaucoma UK
• That informed the decision to keep all optometrists open for appointments
• This was derived by business users and made a huge impact

• The regional difference and separation 
• Global vs. local strategy
• Taking everyone's micro-objectives towards big goal
• Continued alignment when everyone wants to be apart of it
• Balance the foundation building and delivering

• Culture is more important than technology
• Re-platforming was tough (Azure) but a great decision
• Tech isn’t the solution to everything

• Can work together and be effective in any industry
• At giffgaff - we used it as additional approval for credit vetting
• Can save time through automation, reduce churn
• Big impact for customers, but also for colleagues - processes/job satisfaction

• It happens, but almost unintentionally
• The care and emotion can’t be replicated by AI and needs to be embraced

• It comes down to personalisation and relevance
• We are trying to get back to that 121 feeling (impossible) but data does it for you

• Sharing capability and can-do attitude as part of a mission
• Strong engineering focus
• Data science capability along with governance
• Community-minded +++

• Need support at senior level
• Once you have buy-in - then identify pain points
• Find owners for important assets and adoption will come
• Lots of hearts and minds to get it embedded - show the benefit

• Customer experiences and colleague experiences
• Better job satisfaction and opportunities for your colleagues
• Each company will be subtly different

• When companies make a really positive impact i.e. health/society
• Companies that are using AI

• You need to give people time to get there, cultural shifts take time
• Once you’ve achieved that, you can move at pace and get stuff done quickly

• Historically brains > muscle but now its about emotion for humans
• Data skills are as common as Excel and Word
• Huge amount of robotics, automation and personalised experiences

• (Ed - you will have to listen to the podcast to find out)

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