intelligent machines: steering retail planners through crisis

By Andrew Fowkes
Andrew Fowkes, Head of Retail Centre of Excellence, SAS UK & Ireland, on how intelligent machine can steer retail planners through the current crisi...

Andrew Fowkes, Head of Retail Centre of Excellence, SAS UK & Ireland, on how intelligent machine can steer retail planners through the current crisis.

Retail planning is tough at the best of times. When the online and physical realms of retail are bustling with activity, head office must factor a huge number of variables into the equation: everything from stock ordering and product performance to customer expectations and market share.

But as healthcare workers battle the virus and the retail industry retreats to online stores and fluctuating demand, planning has become exponentially more difficult for European retailers. The path to success is no longer as simple as studying past performance. With staffing, stock levels and trends all in limbo, retail planners now need to quickly analyse an even greater volume of data than usual. For many, it will seem impossible to make the right decisions at the right time.

Analytics and intelligent machines can be the answer these retail planners are searching for in these challenging times. As an extra member of the team, this technology gives planners the ability to understand what the data is telling them about their business. At the same time, they guide teams to see what the data means from a bird’s eye view. The ability to report and visualise data in the right way means that retail managers are afforded more time to make decisions, with more scope to plan for particular goals. Even more powerful is using  advanced analytics, where AI and machine learning can greatly enhance the capabilities of a retail planning team to make accurate predictions and steer their company through this crisis.

What differences will it inspire?

Outwardly, this system could look very similar. But underneath, it is likely to improve the customer experience significantly. I certainly think there will be no adverse effects for customers. You may recall the initial fears that RFID technology would affect customers and their data, but its use is now standard, and greatly improves customer convenience. Our customers confirmed that it really does not matter to them whether the selection of goods, pricing or advertising are chosen by machine or a human buyer. Except that machines drawing on data may have a better idea of what customers want! 

However, increased use of machines will minimise HQ functions and roles. This is already happening, driven by rising costs and squeezed margins. It will also mean faster decisions and changes in the ranges on offer.

Effective retail planning is changing the game

Again, this is already happening. In Manchester, the online fashion retailer ‘In The Style’ has a full new range every two weeks, with a 75% sell-through. The increasing number of convenience-sized units means that a higher proportion of ranges change more frequently. Aldi and Lidl have shown the way, with their weekly specials and smaller range (3,500 SKUs vs. 25,000 in an average supermarket), resulting in a smaller average basket but high footfall.

The use of machines should also mean more personalised offers and range. A good example of this is the Very group, an internet shop with personalised assortments and offers tailored to individual preferences and delivered to mobile devices to improve conversion.

Finally, we should also see retail becoming more sustainable, with less waste resulting from mistakes and markdowns. Historically we have seen higher margins to enable businesses to afford the waste and markdowns. Will we now see a consumer tolerance measure, or even new legislation?

What will drive adoption, and what are the risks?

There are a number of pressures driving retail towards the use of machines and analytics. These include competition, customer demands and the resulting profit squeeze. It seems unlikely that changes in retail will be driven simply by availability and capability of technology. Generally, there needs to be a better reason. Adoption may, however, be driven by results, especially if the technology starts to perform better than its human equivalent, or – more likely in my opinion – in combination with people.

It seems unlikely that people will ever be removed completely from the equation. History tells us that a hybrid approach, combining people and machines, is usually stronger than either alone. However, we may see a shift in creativity from the retailer back up the supply chain to manufacturers and producers. We may also see the differences between offers and ranges shrink – but perhaps that is where the human input will become more important. After all, nobody wants to look exactly like everyone else.

There are also risks that the model will degrade over time. This will mean that customers gradually start to see less that they like. As always, machine learning and modelling will require maintenance and checks for bias. Over time, though, I think we may well see retailers becoming technology companies. Arguably Amazon has shown us the way, and this may be where many others are heading.

AI could take the weight off planners

Modernising your retail planning capabilities could vastly increase your organisation’s ability to reach customers with the product they want, at the moment they want it: an indicator of top-notch customer service. However, the added bonus is that retail planning welcomes intelligent technologies as part of the team. This means it can take the strain when difficult decisions must be made, especially in times of considerable uncertainty. With the ability to understand the existing data on a deeper level than ever before, intelligent machines can augment the abilities of the team around them and inspire decisions which keep retailers at the top of their game. 


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