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Vlad Jiman, Director of Data, N Brown

Describe your career to date

At 31 years old, I’m super lucky to have had a whirlwind of a career to date, with the last 6 focused exclusively on data. I have worked for small and large, slow and crazy, thriving and struggling organisations, met exceptional people, had amazing mentors, and learned a lot from them. 

 

I joined THG as a customer scientist when there was no data strategy, data infrastructure or centralised data function to support this type of work. Over three years, I centralised, attracted, structured, and led a global workforce of 40+ colleagues across machine learning, experimentation, data engineering and BI as the head of data science. This team commercialised data products like anomaly and cyber-attack detection, micro-segmentation and personalisation, product and customer embeddings, advanced image search, fraud detection and natural language processing.

 

I then moved from the science to the engineering side, joining Pets at Home in 2019 as the group head of analytics platform and data engineering. Here, I established the data platform, engineering and visualisation capabilities as part of the group’s wider “petcare analytics for all” vision. This new 45-plus strong function delivered a transformation programme, including a best-in-class cloud-native analytics platform serving an internal audience of over 15,000, associated CRM and customer service tooling, and the technical capabilities and data-driven processes required to power the organisation’s award-winning VIP loyalty scheme. 

 

This uncommon mix of strategic, analytics and engineering expertise allowed me to join N Brown as the director of data in May 2022, reporting directly to the CEO, to lead and deliver the PLC and executive-board’s mission to “establish data as an asset to win”.

What stage has your organisation reached on its data maturity journey?

N Brown has been getting value out of data for over 150 years, but it was only recently that data has been elevated from an “enabler” to one of the company’s five strategic pillars. We now have a data strategy outlining how we will “establish data as an asset to win”, and we are at the start of this exciting transformation. 

 

Tell us about the data and analytics resources you are responsible for

As part of the target operating model pillar of our data strategy, we have formed a central group data function spanning five core disciplines: data management, engineering, science, analytics and visualisation. This function sits alongside the rest of the C-suite (operations, finance etc), and the majority of our capacity (50-plus UK-based colleagues, with material growth planned through centralisation and new hires over the next three years) is spread across data-driven or data-enabled agile “squads”, with the heads of the respective disciplines acting as “chapter leads”. While people are central to our strategy, the significant financial and political capital required to deliver the planned transformation are also very important.

What challenges do you see for data in the year ahead that will have an impact on your organisation and on the industry as a whole?

The increasing speed with which the data ecosystem, industry and best practices evolve means this is still one of the most exciting fields to work in, despite the challenging macro-economic environment. Following significant over-investment (and subsequent disappointment) in data science over the last few years, most companies are shifting investment into engineering, governance, and architecture (hopefully in a more balanced way) – there will be a focus on DataOps, analytics engineering, and distributed, accessible and automated data governance. Companies will also find better ways to commercialise machine learning through autoML, and through the increasing commoditisation and democratisation of powerful algorithms and associated data products.

Have you set out a vision for data? If so, what is it aiming for and does it embrace the whole organisation or just the data function?

Everything we do in data is based on our data strategy, which outlines the landing zone, direction of travel, and steps required to leverage the awesome but not-yet-fully-tapped potential of our data and analytics, which will help us enrich every customer experience, optimise every business decision, and empower every colleague. This is a holistic, comprehensive, principles-based strategy that revolves around three key pillars: operating model, analytics platform, and data culture.

 

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

This is a key deliverable of our upcoming transformation programme, and in line with one of the key challenges and data trends mentioned above: distributed, accessible and automated data governance. Given that we’re positioning this transformation as “near-greenfield”, we are able to adopt best in class ecosystems and practices, which should also allow us to outpace our competition.

Vlad Jiman
has been included in:
  • 100 Brands 2023 (EMEA)

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