Whatever tomorrow may bring, we know it will definitely not look like today, or yesterday. Retail is a granular business where planning relies largely on the past, by the week and by the day. Perhaps the greatest challenge of all facing leadership teams right now is the rear view mirror becoming almost irrelevant. What will demand look like and therefore, what stock in what quantities should you buy? And as it percolates through the supply chain, how should you allocate between stores and online, and then by store type and location?
Retail leadership has always been a combination of art and science, and it isn’t either or – the latter needs to inform the former, allowing better outcomes based on decision-critical insight and intel. And steady state retail management, based largely on repeating past year's trading stance, is finished. It simply won't work because everything is topsy turvy.
Data is not and cannot ever be power on its own. Retail businesses generate vast mountains of data but turning this into actionable intelligence to directly drive the operating and trading model requires customised tools. Data science and AI allow complex relationships to be identified to facilitate optimisation in critical areas like range planning, full price architecture, mark down management, stock allocation and availability.
We all know that demand patterns have changed dramatically, not merely as a whole but by product type. So too has the relationship between channels. And so too has it shifted by location. Reacting to this effectively requires levels of agility few retailers had pre-pandemic.
We are supporting retailers in all these areas daily. You cannot save to success - cost cutting misses the point. It's your top line that needs to be driven more effectively with the necessary tools to ensure maximum returns from those sales. Leveraging your data isn't a nice to have - it will increasingly be the difference between life and death.
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