Welcome to the fifth season of the Future Trends Blog. As in previous years, our intention is to share with our readers new and interesting developments that help us to understand the future better (and then invest in it), on a roughly weekly basis. Since our very first ever thematic piece of work in 2011 was on data, it seems only appropriate to begin the year with a novel perspective on this topic.
We recently had the opportunity to catch up with the Head of Data Enablement at Specsavers, one of the UK’s largest private companies. Similar to your author, Robbie Priddle is a keen oenophile. Wine is also a relevant metaphor when it comes to considering data in the sense that both terms are misleadingly broad. Just as a bottle of fine Bordeaux is very different to a supermarket Californian plonk, so data management needs to be considered as a very different skill set to data science, data visualisation or data engineering. Big organisations such as Specsavers need to employ people across all these disciplines and part of Robbie’s role is to ensure that data and analytics is a “collaborative team sport.” This is a lesson other businesses should heed.
Good businesses need the right data tools. Robbie highlighted emphatically that “if you’re not in the cloud then you’ll be left behind.” We concur. With only about 20% of all workloads globally currently in cloud environments (per IBM), the runway ahead is significant, in our view. When it comes to artificial intelligence, Robbie noted that it was a “most over-used term… thrown at almost any data science use case.” More important, in Robbie’s view, is machine learning. This discipline is critical for building any predictive model, whether it be for forecasting or generating a propensity score (how likely might a customer be to buy a product). Needless to say, the larger your dataset, the better the outputs.
When asked where the biggest areas of growth for analytics lay, Robbie highlighted retail and people. To return to datasets, Specsavers is hoping to leverage its insights in order to improve the clinical and shopping experience in its stores; how, for example, can you optimise layout in order to improve satisfaction and efficiency? For many businesses, staffing constitutes probably the biggest variable cost. With better analytics based, say, around employee activities and engagement, it’s possible to begin to predict which employee may be most susceptible to churn and potentially to pre-empt this. Underpinning both these topics, however, is a consideration of data ethics and privacy. This was a topic we first discussed last year but expect only to grow in importance in 2023.
The above does not constitute investment advice and is the sole opinion of the author at the time of publication. Past performance is no guide to future performance and the value of investments and income from them can fall as well as rise.
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Alex Gunz, Fund Manager
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