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Russell Barton, EMEA Data Governance Manager, Starbucks

Describe your career to date

 

I have been at Starbucks for nearly two years, having been offered the opportunity to take on the newly created role of EMEA Data Governance Manager. 

 

As with any new role, the purpose and scope has evolved over that period, but working at such a well-recognised and high-performing brand has more than lived up to my expectations. As I have become established in my role, I have been able to work with the different business teams to not only improve their data quality and governance, but also to look at the business processes that create and transfer that data.

Prior to joining Starbucks, I worked for Barclays for over 30 years, where I had the benefit of being able to have three distinctly different career phases, but all with the same organisation. Initially, my role was what could be described as a traditional retail banking role, encompassing areas such as cashiering, through securities and mortgages, and on to business banking support.

Needing a change, I took a chance and applied for a project management role, which led to my career as a Project and then Programme Manager. I covered a wide range of projects, from organisational restructures and HR delivery to new tech platform implementation and regulatory reporting. My role gradually became more focused on data-centred projects, including a large programme covering data quality and remediation.

This led to the last part of my career, looking at how data was used and supporting the development of new data-based products and services. This included the development of customer-facing materials to support the introduction of general data protection regulation and culminated in the design and implementation of an award-winning data ethics framework for use with new analytics and insight projects.

Data literacy is a key enabler of the value and impact from data. How are you approaching this within your organisation?

 

For me, data literacy is an integral part of the data strategy of the business and has a strong part to play in ensuring successful data governance. When I designed the data governance framework for the organisation, I ensured that data literacy spanned all of the deliverables and was seen as a core enabler to becoming a data-driven business.

To help inform the work that would be required to build an enduring data literacy programme, as well as to provide other opportunities for success, I introduced DataIQ to Starbucks, working with them to refine and deliver our first DataIQ Data Literacy Assessment. Analysis of the results showed that trust in the data was a fundamental first step, but also that our partners (employees) were not necessarily engaged with, or making the best use of, the data that was available.

To help our partners to understand and communicate not only the data itself, but also the benefits and insights that can be gained from using it in new ways, we are in the process of building a delivering a data literacy programme that will be available to all support centre (head office) partners, which will recognise the different needs of partners throughout the organisation. From novice data analysts to influential data guardians, we will deliver content that covers a range of data personas. 

 

A key tool within this will be our EMEA data university, which will be a portal for delivering bronze, gold, and platinum levels of skills and knowledge, and will help to foster a community of passionate and data literate partners who can support and develop each other.

Have you been able to fix the data foundations of your organisation, particularly with regard to data quality?

Fix is maybe too strong a word. What we have been able to do is to establish the foundations, set out a path for how this can be achieved, and start to bring our partners on the journey towards becoming a data-driven organisation.

Our data governance framework starts with data principles, a map of the data lifecycle, and an adopted data RACI model. From here we move on to setting data policies and standards, defining data KPIs, and setting out data usage action plans. This leads to the development of our data culture, ethics, and strategy, which is all underpinned by our data literacy plans.

On the subject of data quality specifically, it has been important to understand that each different type of data has to have its own set of agreed tolerances. As part of the work on the data governance framework, we have begun to define data owners for each particular data source and then work with those owners to understand the data quality parameters. We have also documented a set of data quality principles and standards, which we will continue to refer to as more sources of data are ingested and used in the future.

Russell Barton
has been included in:
  • 100 Brands 2019 (EMEA)
  • 100 Brands 2020 (EMEA)
  • 100 Brands 2023 (EMEA)
  • 100 Brands 2024 (EMEA)

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