Using Location Intelligence to Ease the Supply Chain Crisis

Soaring pandemic demand  disruption of trade flows (including port closures in China)  along with a shortage of drivers and other labour have combined to create a global supply chain crisis with many retailers running low on stocks. Mainland Europe in particular is experiencing an estimated 400 000 lorry driver shortage with the map below highlighting unsatisfied demand in various regions around the world.

Graphic showing the shortage of drivers across Mainland Europe
Source: todotransporte.com

In the UK the situation is further exacerbated by post Brexit checks and immigration rules which have resulted in restaurant chains and fast food outlets running out of key ingredients (e.g.  Nandos  McDonald’s  KFC  and Greggs)  gaps on supermarket shelves (e.g.  ASDA  Sainsbury's  and Morrisons)  disruptions to retailer’s entire product lines and fuel shortages.

So what can be done to mitigate this crisis and avoid empty shelves in the run-up to Christmas? Forbes suggests that “supply chain workers should organize and design systems to move past Just In Time.” They go on to say that “we need inventory management and procurement systems that prioritize anti-fragility  sustainability  access and equity instead of narrowly defined productivity and profit goals.”

 

Demand Modeling

Surging demand is putting strain on container groups  suppliers  and logistics companies with one Maersk executive calling for either lower or differently spread out growth to give the supply chain time to catch up and end the ‘vicious circle’. Given consumer demand is expected to continue to rise and with concerns about more disruption in the run up to the peak shopping season it is clear that more accurate demand modeling will help logistics managers with better visibility into the different areas of the supply chain and improve maneuverability when issues occur.

Spatial models can be used to simulate demand and can be enriched with data streams relating to events (such as port closures and labour shortages) or weather  providing insights to predict & test future demand scenarios.

Map showing an example of Demand Modeling

Route Optimization

For a relatively small number of deliveries (say 60 to 70 parcels per day) there are trillions of possible routes. The vehicle routing problem (VRP) isn’t just about finding shorter routes or less routes  it’s a strategic way to reduce costs and the carbon footprint.