This article was originally published in January 2020.
It was always about the last mile, but tech is shifting the emphasis to time. So what makes an optimal last-hour location?
Earlier this year I was invited by the International Council of Shopping Centers to give a talk on the outlook for logistics. Not the natural audience for a chat about sheds, but with e-commerce players snapping up warehouse space the synergy between the sectors was actually fairly clear. As I regaled the audience with stories of record high take-up, rental growth, yield compression and double-digit returns, the mood darkened. It’s easy to forget that retail was once the glamour boy of real estate. No more. The glamorous boy has become a sick man.
In stark contrast, logistics had been viewed by many as dull. A cog in the machine, a necessary but dreary part of the supply chain, logistics dwelled deep in the shadow of the world of retail. And now here I was, reminding the audience that the sector they loved was being replaced in prominence by a part of the market many of them had rarely given a thought.
Looking for a way to end on a positive note, I gave the suggestion that retail landlords should try to benefit from logistics, whether it be click and collect, conversions or finding other uses for their customer data. It was this final point that laid the foundations for an exciting piece of research – research that has identified locations in the UK and Germany where logistics operators can optimally service e-commerce customers while also unearthing markets with the potential for outsized rental growth.
In the audience that day was John Platt from the location and customer analytics specialist CACI. We at DWS have worked with John and CACI many times, using their analysis to appraise our retail. Often we would ask CACI to undertake a catchment analysis: this is a way of understanding the whereabouts and socio-demographics of the people living in the areas surrounding a retail location.
As he and I talked, it became increasingly clear that this sort of analysis could easily be re-engineered for use in the logistics sector. What we needed was a reverse catchment analysis. Rather than how much spend we could attract to a location, we could find out how much customer spend we could deliver direct from a warehouse.
