We have worked with logistics companies such as rail operators and parcel delivery companies to help them drive operational improvements using analytics. Logistics companies typically collect vast amounts of data as a byproduct of their daily operations that can be used to understand the system in detail. For example by tracking each individual delivery from start to finish, and building the analysis model from millions of deliveries, we can analyse what factors predict for example delays, cost overruns or customer complaints.

We have also enabled our customers to understand on a detailed level how their assets are used and where they operate in the network, where investments bring the most value, and how different maintenance programs compare to each other and how they affect lifetime costs of assets and overall operating costs and efficiency.

As an example, few questions that can be answered with our analyses are:

  • • Looking at all the deliveries in our logistics network, what are the best predictors for a delivery to be late, and how can we change our processes to eliminate those causes?
  • • Where are our assets moving and waiting over time, how much empty movements there are? How do those locations correlate to our service and maintenance depots? 
  • • How significant differences there are in the energy consumption of our assets, and when comparing those differences to different maintenance maintenance programs in use, can we see differences in cost effectiveness and outcomes of maintenance?


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