The New Retail Balance Sheet: Why Data is an Asset – and How to Value It

The call to utilize big data is more than five years old now, and retailers are well aware of the huge commercial value in acting on insight. However, the narrative surrounding how to act on this insight hasn’t evolved in that time – and it needs to.

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We’ve moved beyond a world in which retail is driven by supply rather than demand, where the compulsion for retailers to extract value from sales and supply chain data was weak.
Now – as Amazon and other disruptors change the industry, and customers continue to expect more – retailers either lacking certain core data sets, struggle with its quality and structure, or experience problems integrating them to provide a single view of the truth, are running into problems.

Artificial Intelligence: the future is now

The truth is that most retailers already have all the data they need to convert information into value. However, a better way to extract that value is needed – and AI can provide the solution.

While the media chooses to investigate how Artificial Intelligence will enable robots to serve hotel customers, or how robot dogs will make house-to-house deliveries, leading retailers are looking beyond the future-gazing. They are increasingly understanding how AI can solve the everyday problems they’ve been experiencing for many years; notably demand forecasting, for more accurate replenishment based on insight.

AI algorithms enable retailers to predict with extraordinary accuracy what customers will buy next, across every single product, in every single category, through every channel. The results can rapidly optimize performance across the supply chain, reduce back of store stock, move stock faster at the shelf, lower markdowns and reduce waste.

These are all results that will show up in a retailer’s balance sheet, as they can see a growing return on working capital.

The new retail balance sheet

Up until now, it felt as if big data was waiting for a catalyst to convert knowledge into power within retail. It now has this catalyst in AI.

By embracing the processing, predicting and optimization capabilities of Artificial Intelligence, retailers are not only aware of the vast amount of information their business generates, but can use it to drive better business decision-making. In this sense, data becomes not just an object, but a genuine asset.

This change of perspective provides a new hierarchy for valuing data across the business, and gives individual users in every department the ability to create a more meaningful set of KPIs – ones that are rooted in financial improvement, not just performance or efficiency measures.

From this, organizations can build a new retail balance sheet for the new way of doing retail; demand-centric decisions that are able to incorporate the complex data created by multichannel consumers.

The power of AI to extract value cannot be underestimated, and its reach is not restricted to the retail industry. Retailers need to keep their eye on companies outside the sector that are starting to use data as a powerful competitive weapon – in order to take on traditional retailers at their own game. Another reason to stay ahead of the field.

See how Morrisons is using AI to harness big data to drive performance in the grocery sector by reading our latest case study.

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World-class retailers can reduce their out-of-stock rates by as much as 80% and see their revenue and profits improve by more than 5%.