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    Home»Shopping»How real-time data can drive ROI in the retail industry
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    How real-time data can drive ROI in the retail industry

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    My first proper job was in electricity distribution, where real-time data was typically applied to control systems that needed to respond within milliseconds (i.e. “real-time”) in order to avoid killing someone, often including me. Performance mattered and we designed and built our data management systems accordingly, although calculating the ROI on saving lives was a little awkward.

    The stakes aren’t quite as high in retail, however the need to accommodate, and leverage, real-time data is increasing as fast as the volume of data itself. In fact, from a customer perspective, one could argue that the very act of purchase is the classic example of a real-time transaction. Every aspect of the retailer’s value chain, from sourcing through to point-of-sale, comes together to create the best possible offer to the customer. This (real-time) moment of truth with the customer defines the retail experience.

    That said, the retail landscape and customer experience has changed dramatically in recent years. Foreshadowed by digital transformation, COVID-19 has permanently altered buyer behaviour and brutally exposed the fragility of our “optimised” supply chains. Likewise, macroeconomic forces such as inflation and fears of a global recession, have increased pressure on pricing and promotions effectiveness.

    So, what does this have to do with real-time data? And more importantly, how can real-time data drive business impact and greater return on organisation’s IT investments?

    If we accept the undisputed assertion that data is a critical and growing business asset, how then does real-time data change the retail equation? Several influences come to mind, including:

    1. Trust: Real-time data, by its very nature, is generated or captured in an automated way, often from retail sources such as a POS system or even IoT sensors in a warehouse. While not foolproof, this process lends itself to increased accuracy, with the immediacy of the data leading to more trust and confidence from the business, as well as partners and suppliers. As any online retailer, from Amazon to JB HiFi will confirm, customer trust in real-time inventory, product availability, and shipping is paramount.

    2. Granularity: The availability of real-time data is often accompanied by a large increase in corresponding data volumes. This increase in volume is another result of the automated capture process which can source data at far greater frequency and across a much broader range of inputs. This granularity feeds Artificial Intelligence and Machine Learning models that deliver previously unattainable insights and predictive analytics.

    3. Sensitivity: Obviously enough, the frequency and timing of real-time data streams allows the business to analyse, and most importantly, act on the data immediately. Without having to wait for complex off-line analyses or batch processing, data can be put to work when and where it matters (i.e. to better support the customer moment of truth). Likewise, the retail business can itself respond in real-time to competitors or market forces as they happen. We have seen many examples of this situation in the last few years where supermarkets like Coles and Woolworths have had to pivot their businesses (repeatedly) in response to frequent and completely unexpected stock shortages.

    4. Consequences: Finally, real-time data eliminates the traditional lag between analyses and processing, and business action (which may have previously been measured in days or weeks). This means that category and brand managers can now innovate more often and receive market feedback immediately. Having timely and direct clarity on the consequences of their business actions allows retailers to manage change more effectively and increase the resilience of their product lines. The organisation’s ability to rapidly test-and-learn reduces cycle times and execution costs.

    So where does this leave us? In today’s world of omnichannel retail, personalised customer engagement, and recuperating supply chains, real-time data has become a fundamental asset in the retailer’s toolkit. Furthermore, real-time data is not just an operational capability – its very existence allows retailers to develop new products and services at a much faster rate, and that are more closely aligned to customer needs. Retail has always been about the magic of commerce and individual customer interactions – it would be foolish not to use real-time data to support that, “in the moment”.

    Brad Kasell is principal technology strategist at Domo Asia Pacific.



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