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Why retail still doesn’t understand its data challenge

Retailers are failing to embrace big data at their peril, writes Narbeh Yousefian.

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The rise of digital commerce and big data should have made it easier than ever to engage with customers, especially in retail. Instead, we’ve been distracted by the promise of algorithms, chatbots and the need to become ever-more client focused.

Businesses of all kinds have been trying to become more “customer-centric” for as long as anyone can remember – well before the phrase first appeared in the early 2000s. In fact, the logic of putting customers first is as old as commerce itself. In today’s environment however, retailers will struggle to become closer to their customers without doing some internal reflection first.

Why is it so hard to “put the customer first” today?

Data creates as many problems for retailers as it solves.

Companies have more information than anyone could have imagined but the sheer abundance can make it harder to handle.

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At the same time, technological change has reordered the business landscape. There’s a dramatic increase in competition and new threats of disruption from the likes of Amazon and Apple; corporate behemoths with vast resources whose primary business is not even retail but technology itself.

Many existing retail businesses are stuck with static systems and processes that don’t match the inherently fluid nature of data challenges they face.

As a result, information tends to clog in the arteries, instead of flowing freely to the places it’s needed.

Specialists hired to manage data end up trying to free these blockages, leaving little time left to generate the businesses intelligence their employers actually wanted in the first place.

How should retail approach data?

As one of the first industries to be affected by the internet, retail has been at the frontline of innovation for decades, so its use of technology is relatively mature.

Nobody doubts there is more change to come as online sales continue to grow and competition continues to increase.

The latest Pitney Bowes Parcel Shipping Index shows parcel volume increased another 8 per cent in Australia last year to reach 841 million deliveries.

Revenue increased to $9.2 billion from $8.6 billion in 2016, and Australia looks set to pass the billion parcel mark sometime in 2021.

In this digital environment, the biggest challenge for many retailers is restoring good old-fashioned, personalised service.

Rather than just establishing a generic website, they want to tailor an individual experience. This isn’t surprising – many of these businesses thrived on their ability to provide a superior service to their customers. Traditionally, retailers were people-centred businesses, not tech-centred distributors of goods.

Despite years of trying, however, achieving that online equivalency has proved frustratingly difficult. A lot of why this is the case has to do with the way humans within a retail business approach the data the business naturally generates.

Before we accuse retail execs of being luddites, it’s important to realise that decision makers in retail can be quite rightfully wary of grand new innovation projects. The sector has been bombarded with new platforms and new applications to augment everything from their sales to their supply chain management – chatbots as a sales channel is just the latest example.

But what retailers really need, over and above a new widget, is to be able to take the various touchpoints that create data (EDMs, shopping carts etc.) and then make quick, accurate and cohesive business decisions. This is both a tech challenge and a human one.

Workflows, analytics and the boring stuff that underpins customer service

There is no singular, plug-and-play solution that a retailer can deploy to suddenly make sense of all the data they’ve created and then get to the right decision and provide amazing customer service as a result. If there was, we’d all be using it. So how do we get from where we are to the promised land?

We try to answer that by first understanding how human interactions and formal processes within an organisation affect its ability to use data. Then we design workflows that better match the goals.

Personally, I am fascinated by the intricate mechanics of information flow; how it starts in one part of a company and ends up in another, before flowing into the decision making and eventually back to the consumer experience.

I acknowledge, however, that not everyone shares this passion within the retail industry.

That’s why data analytic companies exist: to take care of the “boring” background issues so organisations can get on with finding out what their customers want and how to provide it.

The right data delivered to the right person

Data governance is a key concern, and an important outcome for retailers is peace of mind. At the end of the process, they should be confident their data is not only optimised but also collected and stored appropriately.

Data sharing, clearly, is another preoccupation. Getting the right systems and processes in place means staff in all parts of the businesses can monitor data easily, often in real time.

As well as highlighting potential opportunities, this can generate huge savings by alerting staff to problems as they emerge.

Errors in pricing algorithms, for example, can wind up costing millions but proper data flow makes them visible in a matter of minutes, rather than days or even weeks.

To make this work, data needs to become a communication stream, a shared service within a company that everyone can access.

My experience with retail clients like Catch Group shows it often pays to start small with individual teams, allowing staff to see the benefits for themselves.

While the idea of sharing information and insight across organisations isn’t new, data flow and actual decision making has not kept pace.

There is no single answer and no single endpoint because markets and technology are in constant flux.

Machine learning, artificial intelligence and all those fun algorithms offered by the big cloud providers are great, but they are commodity services.

The real value is not in the algorithms but the data that feeds them. In order to feed the algorithms the right data, the business must first reflect upon its processes and understand where data must flow from, and to. Competitive advantage now sits within a retail business and it is this understanding of data that will set the winners apart.

By Narbeh Yousefian, CEO and Co-Founder at Poplin Data