Data Leaders Summit Europe 2018 – Day One

As promised, I am taking a break from chairing Data Leaders Summit Europe 2018, to share with you.

Once again, this year’s summit has been a really useful event. Numbers of attendees have doubled, so they must be doing something right.

The advice I give the audience when I chair such events, is to identify just one thing they will do differently as a result of hearing each speaker. I will expand a little on that, dear reader, but only to share 3 points that struck me from each session.

Data Leaders Summit Europe: Kick-off

As chair, I was asked to share with delegates (as well as my appalling jokes) a view on the market at the moment. Rather than focus on technology or data, I shared 3 concerns I regularly hear from leaders I work with:

• How to deliver actionable insights faster
• How to scale from pilots to implement in wider business
• How to prove ROI of delivery, to extend influence (& perhaps budget)

I was pleased to see that each of these concerns was addressed by the programme for the rest of this event. So, awaited with interest what speakers had to share…

The blueprint for a data-driven business (BMW)

Dr Stefan Meinzer, Head of Advanced Analytics (EMEA) at BMW, shared these tips:

• You need to achieve trust with business & customers (through simplicity & convenience – as smart phones have done)
• One key way to achieve this with analytics outputs is effective data visualisation
• When you are a global business, data provides opportunity of a common language

Question: How could you build trust in your stakeholders by presenting your outputs in simpler & more convenient data visualizations?

How to future-proof a Data Science capability for your business (Sainsburys)

Dr Enda Ridge, Head of Data Science & Algorithms at Sainsburys, shared these tips:

• Design processes to embed both Scientific Method & engineering principles
• Learn how to do that flexibly in a fast changing business (c.f. his book ‘Guerilla Analytics‘ should help you)
• Focus on ensuring flexibility in tools used, people hired & opportunities worked on

Question: How can you ensure flexibility, to respond to changing needs, rather than rigid processes?

Learning from creating a data science in an old company (M&G Prudential)

Priyank Patwa, Head of AI & Machine Learning at M&G Prudential, shared these tips:

• Data Science is not just about building models, a huge value is in creating / finding the right data
• Don’t obsess about model accuracy – it’s more important that you empower decision makers to take action
• Apply Machine Learning where it is really needed – a simple regression can solve some problems

Question: Where can you start? Does business comes to you with problems or you go to them?

Panel debate (Productionising Data Models at speed)

For this very entertaining debate, I was joined by:

Harry Powell, Head of Corporate Analytics at Jaguar Land Rover

Ryan den Rooijen, Global Director of Data Services at Dyson

Kshitij Kumar, VP of Data Infrastructure at Zalando

Keith Graham, Senior VP of Sales at WANdisco

We had a great debate about how well data models or data frameworks enable businesses to get value from data quicker. A few ideas that were shared included:

• Be business-problem centred, need should drive data model, not the other way around
• There may be a need for more than one cloud solution, different platforms have different strengths for analytics
• Aim to execute analytics close to the data, there may be more flexibility in an API-led data environment, rather than aiming for one platform

Question: Do you have the data model/framework and platform that your business needs? (Over 70% of our audience said they didn’t yet)

Seperating hype from reality to leverage big data insights (Telefonica)

Elena Gill, Global Big Data Director at Telefonica, shared these tips:

• Achieving Digital Transformation is not cheap (over 45m Euros for Telefonica) and may need Big Data & AI to enable new business processes
• The Big Data that will help you most may well be currently unused internal data
• As well as evolving your data platforms, work through the phases of exploration, transformation, data-driven & then AI applications

Question: Are you ready for AI applications? Would you realise more business value through exploring data or transforming processes first?

Ground Control to Major Tom (European Space Agency)

As a refreshing change of sector, at the end of the day we heard from Pierre-Philippe Mathieu. Pierre-Philippe is an Earth Observation Data Scientist for the Europeqan Space Agency. He shared some amazing visualisations of environmental data & these tips:

• The ESA publishes over 50 petabytes of free data, available for analysts or data scientists to use for analytics (data on earth & our environment)
• The ESA is also encouraging a wide range of innovation using this data to add value, across so many sectors from agriculture to insurance
• The funded forward plan for more intelligent satellites to study our environment is impressive – a truly ‘digital twin’ of the earth to enable experimentation

Question: How could your business use this data? What role does the weather or environment play in your value chain? Data is available at a granular level and over time – how could you innovate given this is freely available?

A great first day, which promises even more for day two. I hope those contacts & content are useful for you. Even more was shared at this Data Leaders Summit Europe 2018 in breakout workshops. Plus, a Dragon’s Den session, with a winning start-up focused on smart recycling.

Day two debrief coming soon! 🙂