Retail innovation: Words to the wise
The last few years have hit the retail industry hard, from social and economic upsets to the huge impact of ecommerce and the proliferation of consumer technology. The playing field is no longer level, the playbook has been rewritten and the rules redefined.
Nowhere is this more evident than in the field of innovation – what it used to mean even a couple of years ago and what it means now are two entirely different things.
When CIOs were first challenged with revitalising the retail experience in line with increasingly demanding customer expectations, many gave in to the temptation to equate ‘innovation’ with ‘new tech’. Budgets were allocated to VR, AR and other high-concept experiences – while some of them, such as AI and machine learning, evolved and continue to play an important part in encouraging customers to visit physical stores, others, such as facial recognition, proved to be expensive mistakes.
A few years on, CIOs who have been closely observing the state of play have come to realise that a much more useful and strategic definition of innovation is not to buy something new, but to use what they already have in a new way. What they already have, and it’s a resource that’s growing all the time, is data.
Go big or go home?
It’s another term which has been redefined over the years, yet some retailers still believe that ‘big data’= ‘big problem’ and ‘big investment’. It’s understandable – ‘big data’ sounds alarming, unmanageable and expensive. As a result, while most retailers have recognised the importance of keeping up with consumer technology, there’s an ongoing disconnect between the physical provision of tech-enabled customer experiences and making use of the wealth of information which can be gathered from these activities.
A better term might be ‘knowledge bank’ – innovation in this case means reframing the concept to recognise its power to drive change. Once you see the endless stream of facts, figures and stats as keys to personalisation, clienteling and connecting online with offline, ‘big data’ becomes ‘big opportunity’.
You don’t have to disrupt to innovate
Disruption is a word which has been overused to such an extent that many retailers believe you can’t innovate without introducing a concept so cutting edge it turns your whole operation on its head. But the real skill lies in recognising data as a powerhouse of actionable knowledge that frees you up to be truly innovative with the information at your fingertips without overhauling the entire business.
As the highly successful serial innovator Richard Branson says, it’s about ABCD – Always Be Connecting Dots. The true mark of a pioneer is not how much knowledge you have, but how you connect it together in ways no-one has thought of before. Given the wealth of information available, the best retail strategies will facilitate connections which add real value for customers at the same time as creating efficiencies for store operations. Take the ‘haircast’ initiative from hair product manufacturer Pantene and US pharmacy giant Walgreens, who teamed up with the Weather Channel – their combined data anticipated when humidity in the air would be at its highest, enabled stores to stock relevant hair care products and sent personalised alerts to customers with previous purchase records to seek out a product at their local drugstore. The result of this smart, connected, collaborative use of knowledge was a 10% increase in sales of Pantene and a rise of 4% across the entire hair care range at Walgreens.
Low-cost, low-hassle, high-impact initiatives like this, coupled with more fundamental data-based process enhancements from Nike’s automated warehousing to Sainsbury’s on-demand delivery , are the innovations which will secure the future of retail, using data to bring digital and physical elements together in a frictionless customer journey.
Real-world issues with innovation
While the evidence is clearly stacking up for investing in data management to deliver new, engaging and profitable customer experiences, research into major UK and US retailers, conducted by retail technology analysts RSR and sponsored by Red Ant and IBM, reveals the extent to which retailers remain in the grip of the traditional concept of ‘innovation’:
- 67% said it was a priority to provide information to customers to help them make lifestyle choices and use information to develop new offerings
- 62% believed that the key priority for achieving innovation goals is to deliver technology-enabled solutions that help customers to better enjoy the products they sell
- However, just 28% saw the benefit of using information in new and innovative ways to help internal resources, and only 17% in using it to drive new insights into business performance
It’s understandable that retailers take this approach. It’s much easier to make the case for investment in tangible, attention-grabbing entities – apps which you can see on your phone, devices which you can issue to staff, in-store screens which can be programmed to display the latest offers – than in ‘invisible’, often nebulous cross-business information which can seem tricky to extract from a variety of different systems not built to ‘talk’ to each other.
Feel the fear…
According to the research, there are several reasons behind retailers’ reluctance to involve themselves in data-dependent innovation. A number are held back by past under-investment in technology solutions, as they find the pace of change only increasing:
- While they know that ‘understanding customers on a truly one-to-one basis’ is vital for success (72%), they still face internal obstacles when it comes to implementation
- 61% believe that their existing tech infrastructure is preventing them from moving forward
- 67% believe that IT projects are never delivered on time, in scope or on budget, and that too much time is spent on maintenance rather than innovation
- Among less successful retailers (those with less than 4.5% growth a year), the issue is even more acute, with 60% stating that their company does not have a focus on understanding or tracking innovations
Others are still trying to grasp data intensive technologies such as predictive analytics and machine learning. Many of them express a high degree of optimism about the importance of advance tech such as enterprise API management (81%) and cognitive computing (72%) – but they don’t necessarily know what this might involve.
…and do it anyway
It should come as something of a relief to CIOs who are under constant pressure to deliver business transformation quickly, cost-effectively and with minimal upheaval that all three are possible without installing the latest piece of ‘disruptive’ kit and all the associated risks of obsolescence, incompatibility and user disinterest. In a post-channel era, the first step towards meaningful innovation does not depend on deep understanding of the technology behind AI and other complex developments – it lies in recognising the value of connecting data in new business- and customer-positive ways and building digital store strategies based on the resulting knowledge and insight.
InnoValeur Conseil | Data Science | Smart Data | Machine Learning | AI