For the second time this summer, we hosted a roundtable discussion with senior data leaders from leading UK businesses. For this edition, we focused on tech and AI businesses and we were joined by companies including Sitecore and Kortical. In this article, I am sharing our main observations as we discussed:
Ways of working
Observation 1: Agile has moved beyond the tech function
Since its birth in 2001, the agile methodology has become the most widely used way of working in software development and engineering teams. Enabling an iterative way of working that drives pace and frequent delivery, agile is making its way into the data and business intelligence teams. The benefits are clear:
Delivering immediate value to the business
Driving learning at pace by breaking problems into smaller chunks
Observation 2: Cross-functional alignment is the main barrier to high-impact insights
The common denominator for companies delivering high-value business insights continuously seems to be cross-functional alignment: by that, we mean pulling together multiple functions to improve outcomes, minimise wasted time and get clarity on what the newly gained insights can achieve. What businesses tend to experience in this way of working are skills gaps driven by the lack of critical thinking and business understanding.
Observation 3: Paired working might be a thing for data teams
Again, ‘borrowed’ from software development, a discussion is arising around the benefits of paired working and if the concept applies to data science/analytics. Some data bloggers write about the opportunity of accumulated knowledge and its ability to accelerate the acquisition of ‘pattern recognition’. If you are reading this and have strong views, please share!
Observation 4: There’s a role for a Data Business Analyst
If you extrapolate the paired working concept, and recognise the need for a role that is halfway between the data folks, and the business folks, then we might need to consider a Data Business Analyst. Effectively, they are translating and guiding the discussion between one side and the other. They can spot patterns, and recognise the value that needs to be driven. At CambridgeData, our coaches often play this role both internally (between cross-functional teams), and externally (between client stakeholders and external data analytics functions
Delivering customer value – the ultimate principle
At CambridgeData, we often talk about ‘random acts of analysis’ and how easy it is to lose focus on the bigger picture: Insights that ultimately deliver value to the customer.
Mark Brand, Data Strategy Director at Thoughtworks, our guest speaker at the roundtable, stressed the importance of breaking down the big questions into smaller, impactful chunks and starting to work through these with a cross-functional team and laser-sharp focus on the end goal.
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