Data Is Essential For The Post-Pandemic Success In Retail. Successful Digital Transformation Requires Data More Than Ever — How Does Your Business Size Up?
As governmental lockdown restrictions proceed, many shoppers have embraced to go online for everything from groceries, to personal care, to ‘DIY kits’ from their favourite restaurants and bars. The demand landscape has shifted significantly over to online services due to the pandemic and will continue to do so as every country enters a new phase of localized lockdowns, forcing high-street retailers to once again close their doors with little to no heads up.
Consumers want faster, more immediate, and personalized experience, all at a competitive cost. Retailers want to get a holistic view of their customers, their supply chain, and engage with their customers in order to respond to changing demand and stay relevant and top-of-mind to boost sales, online and off.
To succeed in the new normal still ahead of us, retail must adapt their mindset. Businesses must embed data analytics for operational efficiencies to uncover the much-needed hidden insights needed to ultimately reposition themselves and create a competitive edge.
Contrary to popular belief, retail is, in fact, one of the most data-savvy sectors today, accumulating large quantities of data for decades. Online and physical retailers are all too aware of the money hiding within this asset. Many are already putting this asset to work by using data to improve merchandising, evaluate new locations for store placement, and even guide brand expansion into new customer segments or territories. But as market conditions toughen, the cracks are beginning to show.
What has become apparent is that while some retailers may be data-savvy, very few are effectively using analytics to weather the storm. Demand forecasting is the perfect example of this. Despite a whole host of predictive analytics and automation tools being readily available to retailers, the traditional process is still very much in action — retailers spending hours reviewing spreadsheets and using their past sales to anticipate future demand. While data plays a role in guiding this process and can provide a higher percentage of accuracy, retailers could not only improve accuracy further still but also look to gain huge efficiency savings by simply introducing predictive analytics into this process.
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