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Chris Bannocks, chief data officer, Danone

Chris Bannocks, chief data officer, Danone

How is your organisation using data and analytics to support the corporate vision and purpose?

 

We are diving for sustainable profitable growth while supporting our important vision of “One planet, one health”. The process of creating sustainable profitable growth means focusing in on the data transformations that are game-changing and yield the best opportunities for the business. We work across these dimensions to assess and support the prioritised set of analytics use cases, while building out new scalable foundations for Danone that will allow future delivery of analytics to be more scalable and hence sustainable. On “One planet, one health”, we support the business in determining our food supply chains, and use analytics to support this with data products.

 

2020 was a year like no other - how did it impact on your planned activities and what unplanned ones did you have to introduce?

 

We had to introduce and move quickly to review how Covid-19 would impact our projects, both those inflight and those in minimum viable product phase. Covid-19 shifted our ability to predict, as we didn’t have the models in place to support this scenario. Additionally of course, we have had to shift to remote working and this impacts the natural flow of information and collaboration, some of our plans have slowed down while others have accelerated. Essentially, we have seen a re-balance of the portfolio.

 

Further, we have seen a shift in ways of working, with remote being the main operating model, we have had to create new spaces for people to connect and communicate and new tools to support this.

Looking forward to 2021, what are your expectations for data and analytics within your organisation?

 

Remembering that data and analytics as an organisation at Danone is still relatively young, we see continued growth and business adoption. Specifically, we see the data marketplace development really starting to become a user engagement tool where Danoners can connect to the data that’s available in the organisation. We also see a transformation in master data management and a significant increase in the use of analytics to drive both simple and advanced analytical models.

 

Is data for good part of your personal or business agenda for 2021? If so, what form will it take?

 

Yes, it is. We have ongoing conversations with Universities at the forefront of the thinking around data for good, and we have a specific model to allow our data science teams to focus a portion of their time in this domain which we will look to extend to other teams in 2021. Of course, we have a very close connection to data for good given we have a mission around “One planet, one health” and all of our projects there. We also have a close collaboration with Microsoft in the AI for good space.

What has been your path to power?

 

I would like to think of this as a path to influence and empower. Power is not so important - the collective power of a team is greater than a single person.

 

I began my data career in the late 90s fixing problems with processing around master data and customer data, in the pursuit of better straight-through processing rates and Know your customer. I really enjoyed developing and delivering data products for Thomson Reuters for six years, where market data was the key in delivering innovation to our customers.

 

I then consolidated data capabilities at Nomura across enterprise data management, bringing together market data, customer and reference data to create a single group, just as chief data officers were coming to the forefront as BCBS239 created a huge demand from banks for data knowledge. After Nomura, I went to Barclays to do a similar role, but as part of that I moved to India.

 

When I returned, I set up chief data offices for three London-based financial services companies and then went to do the same in The Netherlands for ING, where I was for four great years. Now, I am with Danone, a real shift in industry which is hugely challenging and enjoyable, deploying data management and analytics capabilities in FMCG.

 

What is the proudest achievement of your career to date?

 

I am proud of so many things that me and my teams have achieved over the years, dating back to data scope select at Thomson Reuters to the data Lake infrastructure and ING Esperanto at ING and many achievements in between. I would say, though, that my proudest achievements have been my teams, the people I have worked with and who have been gracious enough to let me lead them through the data journey.

 

Tell us about a career goal or a purpose for your organisation that you are pursuing?

 

The purpose is to enable all Danoners to make better decisions using data. That’s around 100,000 people we have to connect to and communicate with, to train and to empower. Danone’s journey is not one of a single chief data office - it’s quickly leapfrogging towards a more federated and empowered organisation.

 

In 2021, our data marketplace needs to be front and centre, coupled with MDM transformation, continuing to build our data scientist organisation and our data academy. These are the levers that will propel us towards that outcome.

How closely aligned to the business are data and analytics both within your own organisation and at an industry level? What helps to bring the two closer together?

 

There is tremendous demand for data and analytics across the business, and they need our support to get that done. We are aligned behind a common goal and objective to support our stakeholders, our customers, consumers, shareholders and the beneficiaries of our mission. It’s the common purpose that binds us.

 

What is your view on how to develop a data culture in an organisation, building out data literacy and creating a data-first mindset?

 

I wouldn’t necessarily support a data-first mindset, as I am not sure that’s what we are aiming for. We need a data-enabled culture, but we need to maintain our human-centric culture. We need to be driven first by our purpose and where data can support that then it should.

 

For decision-making, we should use data wherever we can and to do this we need people to understand the disciplines required to make good decisions, for them to understand data excellence and quality, and to be ready to ensure they know that their data is from a good source.

 

We use a number of strategies to do this. First, we engage directly with the business, with empathy and without confusing them with the complexities of the subject. We also communicate more broadly, across the whole organisation, via established internal channels, to ensure data is a consistent topic of discussion and discovery. Then, we build an education and enablement system to ensure people without skills can gain them, people without knowledge can build that knowledge, and those with knowledge and skills can continue to develop them.

 

There are then more culture shifts that need to take place to ensure leadership is insisting on data to make decisions and that we move from Powerpoint decisions to data review decisions.

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