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Driving Cost Savings

Transport requires vehicles and these require maintenance. It is very important to have good levels of maintenance in order to prevent delays and disruption to service. Using the vast quantities of data that fleets of vehicles generate, logistic companies can deploy predictive maintenance strategies to reduce costs.

Operational Efficiency

Delivery routes heavily influence the cost of fuel. Fortunately, algorithms can be used to cut this cost. It is also possible to construct market models that can predict demand from a set of indicators and which can therefore help with planning capacity and opening new routes.

Dynamic Pricing

The cost of providing transport can alter very quickly depending on fuel prices and currency fluctuations and it is very important to be able to react to these changes rapidly. An intelligent pricing model, not only passes on cost fluctuations to the end user, but can consider asset utilization.

The costs of a journey become fixed as soon as it starts.  It is important to maximize utilization of the vehicle up until the point of departure. This requires sophisticated matching of supply and demand to maximize the overall revenue that can be derived from the asset, including strategies for last-minute price cuts to ensure greater load factors.

Frequently Asked Questions

Do you really make data speak?

Do we make data speak? Well, not literally of course! All data of a certain size has a story to tell. It will have trends, sudden movements, be able to show cause and effect interactions and perhaps explain human behaviour. It is not always easy to discover the stories that the data can tell, but we have over 20 years’ experience in doing exactly that. That is why we say, with confidence, that we make data speak.

If you would like to know some more then read about How JTA The Data Scientists does its work or have a look at some other FAQs.

You could also explore our case studies or whitepapers.

Related Case Studies

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