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Author: Krishna Padmanabhan
It’s a common response, and it’s not without reason. Many ambitious projects have failed. People have been blamed. Budgets have been blown. Once burned, twice shy.
A second key factor is scale. Many ideas carry big investments and even bigger expectations. When optimistic timelines or ambitious budgets aren’t met, trust erodes, and the costs of recovery – financial and cultural – can be massive.
Knowledge and insight that comes only from experience are critical assets in today’s competitive retail landscape, but it often comes with risk aversion. The fear of repeating past mistakes can stifle innovation. Despite a deep recognition of the crucial role of innovation in staying ahead, when we speak to retailers, we hear the same recurring challenges are holding them back:
But here’s the good news: we have more tools than ever before to solve these problems. Technology and data analytics have made quantum leaps. We now have the ability to deeply understand both commercial and customer performance and to build highly targeted strategies that align with evolving customer needs.
Even Magnus Carlsen, the greatest chess player of all time, recently admitted he has “no chance” against a modern chess engine. There’s a parallel here: in retail, we still lean heavily on human decision-making for complex problems like range, space, and promotions, instead of leveraging AI and optimisation engines to do the heavy lifting. The key is not to replace human judgment, but to augment it.
In the early 2000s, self-service checkouts faced significant challenges. Retailers like Albertsons, CVS, Big Y, and IKEA began removing self-checkout terminals due to issues with customer service, shrinkage, and unreliable technology. Fastforward to today, the absence of self-checkout options would come at a considerable cost to retailers. The same evolution can be seen in areas like virtual try-on technology, subscription service models, and click-and-collect services. These innovations have dramatically transformed the shopping experience, making it more convenient, personalised and efficient.
And importantly, you don’t have to overhaul everything at once. Start small. Test in a small subset of stores. Learn. Adjust. The cost is comparatively low – in resourcing, time and budget – and the upside is high. Senior leaders are hungry for clear data points, measurable outcomes, and replicable results. The retailers that succeed will be those who embrace experimentation, who aren’t afraid to fail, and who keep learning.
Because in retail, while ‘everything may have been done before’ not everything has been done right, or at the right time, or with the right tools and people involved.
So, next time you’re told, “We’ve tried this before, and it didn’t work,” first ask why? Then ask, why not now?
Get in touch to learn how we can help benchmark, optimise, and unlock the full value of your retail spaces through a low-risk proof of concept.