“Retail’s not complicated. We buy something for 50p and sell it for £1.”

Retail’s not complicated. We buy something for 50p and sell it for £1.

Who would be a retailer? The pressure is enormous and disruption is constant.

Volume is static – it’s estimated that total retail volumes will only return to 2021 levels by 2028 and the average operating margin across Europe has declined from 6.9% in 2012 to 5.8% 2020 and reached 4.8% in 2024.

So we’re running hard to keep still, or at least not go backwards quite so quickly.

We have to work harder and smarter as well as cutting costs, automate and reduce heads, but at the same time be more responsive, more tailored and offer a more personalised service to our customers. And the skills required today, mostly involving agentic AI, require an army of experts not traditionally found in a High Street retailer.

Sir Stuart Rose once said “We buy something for 50p and sell it for a pound – it’s not complicated”. Oh but it is.

Retailers are good at buying and selling stuff, but not the technology that it now takes to bring a product to market. One answer is to hire talent from other sectors, but then you run the risk of tissue rejection and anyway the technology is moving so fast and is so multifaceted that multiple experts are required to cover all the bases. That’s why most large retailers now engage an army of external consultants and a suite of third-party platforms right across the value chain.

As one leading high street fashion retailer said, ‘Human instinct and product innovation are not enough anymore to have the best range. How efficiently you integrate with your suppliers and what systems you use to connect with them is key. UK retail used to be just UK brands, but now we’re trading globally in stores and online and via third parties. It’s very complex. How can we keep it all running in tandem? AI is critical to get into the detail faster – it saves both time and resource. We can’t afford to work with legacy systems; today the top 10 retailers Capex is spent on tech, SC and stores, in that order. We have to rely on our 3rd party partners to constantly update the tools we need – the fact is better systems pay back faster.’

Tony Buffin, Chair of the Tecsa Group agrees; ‘Retail has become extremely complex due to the vast amount of data and multiple expert inputs involved. The ability to gather, analyse and act on date with precision and speed is becoming a key competitive advantage.’

Customer data is collected across loyalty programmes, online tracking via device ID, emails and payment methods and then attributes such as age, affluence, purchase history and behavioural patterns enable precise segmentation and personalised marketing. What the experts call longitudinal customer data tracks repeat purchase behaviour and evolving preferences over time, enhancing targeting accuracy. This enables personalised marketing offers to be sent to small, well-defined customer segments, significantly increasing conversion rates and repeat purchases.

The complexity is mind-blowing. It’s a long way from comp shopping in New York, a bit of trend agency input and buyer’s intuition! Martin Newman, Board Advisor and author of ROI Reimagined is concerned about the direction of travel:

‘Today’s retail ecosystem is incredibly complex, with technology underpinning decision making across every facet of the business from demand forecasting and inventory management to AI-driven personalisation, avatar try-ons, returns optimisation and customer analytics. Solutions like Manhattan Associates, Blue Yonder, Salesforce, Quantum Metric and Stylitics have become integral to how retailers operate and serve customers.

But the challenge is that in outsourcing these capabilities, some retailers are also outsourcing their thinking. Technology should enable better decision making, not replace it. The smartest retailers are using these tools as co-pilots, not autopilots. They retain control of strategy, storytelling and the customer relationship, recognising that it’s human insight, empathy and commercial instinct that turn analytics into meaningful action and that’s still where competitive advantage lies’.

At present AI serves as a tool to enhance human decision making, rather than replacing human judgement, but it’s evolutionary and will have significant impact on teams and organisational structures over the next 10-20 years. AI will automate junior tasks, but increase the demand for skilled data engineers, scientists and other specialists, so the total number of roles may rise in the short term before then rapidly decreasing.

The dystopian scenario is one of full automation, but that would mean no jobs and no purchasing power – no one to buy something for 50p or sell it for £1!