The changing needs of warehouse locations in the online era

It is no surprise that infrastructure and demographics play a major role in answering these questions. On the other hand, as in any supply and demand scenario, the most favourable locations are likely to come with the highest price tag and supply is also likely to be limited. For the purposes of our Model, this general scenario is adapted to factor in specific requirements fuelled by online shopping trends, general technological changes, current stock and price levels.

Model Inputs

Consumer Demand

One of the major trends that is changing the industrial business model is ongoing growth in online shopping and, as a knock-on effect, the transition to a B2C model. Where previously industrial sites were located near to suppliers, or strategically located in the middle of the country or by major transport hubs, the parcel carriers carrying out the last-mile want to be closer to an ever-more demanding consumer, which is drastically changing the requirements for floorspace. In our Model we have included the % of high propensity online shoppers living in any given location, as well as neighbouring locations.

Labour Supply

The loss of labour in the retail sector is widely discussed in the media, with many headlines focussing on major redundancies. However, total retail spend is still growing and since part of the total spend is transferring to the online side of the retailers, labour needs might simply transfer rather than disappear completely. The chart below shows these changing trends. Wholesale trade, manufacturing and warehousing transportation activities are slowly back to or above pre-2008 levels. In contrast, while retail jobs are experiencing a second slowdown since 2008 – one right after the financial crisis and the second one as a result of fall-out/CVAs since 2016.

Changing labour markets

Besides general needs for a large labour market, specific skill requirements are changing. Due to the increasingly exacting demands of consumers, industrial occupiers are pushed towards more efficiency to keep up. Technology plays a major role in achieving efficiency gains, but requires, over and above new technologies, a different, more specialised, skilled worker.

Additionally, although low unemployment rates are generally seen as a good thing on a macro level, to have a healthy labour market, some level of unemployment is beneficial for companies in need of workers on a more micro level. Logistics occupiers tend to favour locations with a higher unemployment rate to have a workforce to tap into. To cover all these bases, in the Model we include total working population, unemployment rates and the number of special skilled workers.

Accessibility

For most online and multi-channel players, fulfilment and distribution services are outsourced to one of the major 3PL players, such as Wincanton and Clipper. Parcel carriers benefit from being in close proximity to these large fulfilment centers. Additionally, due to the growing importance of automation and general digital transformation, speed of internet is becoming increasingly important. Both access to distribution centres and access to ultrafast internet are accounted for in our Model.

Affordability

Industrial rents have picked up since the financial crisis in 2008, exceeding pre-2008 levels since 2015. With growing demand and limited available stock, further upwards pressure on rental values will continue for the foreseeable future. However, rental levels are unequally divided between regions and individual locations and this is reflected in the Model to incorporate the search not only for available sites, but also for space that is affordable.

Average Prime Industrial Rents 2000 - 2018

Supply

Lastly, the Model factors in levels of available stock. Floorspace in popular locations competes for land with other sectors, including home builders. Limited stock will negatively influence the attractiveness of the location in our Model. We acknowledge that limited stock can be both a positive as well as a negative criteria, depending on the stakeholder, but for the sake of our Model, we have looked at stock as a positive element. As this exercise is not aimed at one specific stakeholder, but is instead developed to look at the best location from a holistic standpoint, this seems to be the most appropriate way to incorporate supply into the Model. For customised work, we can change the direction and meaning of the input, to fit the requirements of the stakeholder.