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.
Over the coming years we expect the logistics sector to be one of the top-performing parts of the European real estate market. But with limited room for further yield compression, we expect performance to be driven more by occupier fundamentals than by capital markets. This will make it even more important for us to understand the factors driving the future location decisions of logistics occupiers.
Further increases in e-commerce, expectations for faster delivery and technological improvements such as electric vehicles are likely to shift the focus of logistics fulfilment from distance to time. In the future it will be more appropriate when analysing the fulfilment of online sales to talk about the last hour rather than the last mile of logistics.
But, how do we determine what makes an optimal last-hour location? We had explored this in previous research, but by applying market knowledge rather than quantitative analysis. With the help of CACI, we hoped to provide location recommendations that were far more robust and comprehensive. In this analysis we worked with CACI to fully map the value of online spend taking place within a one-hour drive from any postcode location in the UK and in Germany.
The results were far better than we expected. Indeed, as we went through the data outputs, many of the postcode locations with the highest online spend potential already hosted industrial and logistics sites. Unsurprisingly, one-hour access to online spend in the UK was highest within London; however, the densely populated regions of the West Midlands and the North West also scored well. In the more polycentric German market, North Rhine-Westphalia stood out, with access to online spend almost three times the national average. Beyond this, the federal states of Berlin, Hamburg and Hessen also recorded above-average online sales.
However, in both countries these regional averages hid a huge amount of detail. Within almost every UK region and German federal state there were locations with access to spend well in excess of the national average. Outside London, we found locations such as Denton to the east of Manchester, Leicester, Sutton Coldfield and Huddersfield, where access to spend was almost twice the national average.
It was also important to cross-check the estimated level of online spend against current rents. This is key, both for occupiers looking to optimise their supply chain and for investors seeking locations with the potential for higher-than-average rental growth. It became evident that there are a number of locations in London and the South East, mainly concentrated in and around east London, that look attractive on this measure.
In Barking, east London, access to online spend was just 10% below that of Park Royal in the west of the capital, but prime rent levels were at a 45% discount. Similarly, while one-hour spend potential in Romford and Dagenham was about 20% lower than in Park Royal, prime rents were almost halved. In Germany the relationship between access to online spend and industrial rents was less clear, perhaps reflecting the polycentric structure of the country, its exceptionally high road density and the close proximity between cities in places such as North Rhine-Westphalia.
A weaker relationship did not suggest the analysis was without use. Indeed, the analysis still highlighted locations where rents looked relatively attractive. For example, given the density of population and the road network in and around Cologne and Dusseldorf, we believe less established logistics locations in the area may start to look attractive, particularly if fuel costs fall.
So, what do we do with this research? This analysis was a lot more than an intellectual exercise. We now have at hand information with a clear and executable purpose. And for the retail sector, here is a final thought: the value of many shopping centres and retail parks may be slipping, but the data produced by – and used in support of – these assets has never been worth more. Collect it, use it, be creative, and see what you can find.
