Big Data: Uses and Challenges In Logistics
Uses and challenges of big data within logistics are explored in this in-depth blog by Chris Griffiths, Account Director at Triangle Information Management.
Big Data has been around for a while now, and to de-mystify what that actually means – it’s basically augmenting external data sources with your traditional internal data sources to have a positive impact on your organisation. You will have some form of onboard telematics to measure the amount of drops, the trip time, and speedometer details of the trip, and the drop details already.
Internal & External Data
All of the standard data that you record with telematics is your internal data. You can use this data for measuring the success rate of your drops, and to measure the average distance traveled and time taken.
But what if you could start to bring in external data sources too – like weather data for instance?
How could weather impact your business, and what are the positive impacts that understanding weather patterns could play in planning your resource levels and scheduling your supply chain?
On average, there are over 5,748,000 vehicle crashes each year. Approximately 22% of these crashes – nearly 1,259,000 – are weather-related.
Rain and fog have a major impact on driving conditions and can have a debilitating effect on your senses. It effects your perception of distance, increases distractions because of windscreen wipers, and even road markings and road signs and signals are much more difficult to understand. The statistics for driving in fog and the chain reaction crashes that happen are enough to put anyone off from driving on these conditions.
When it rains traffic moves on average at up to 20% slower.
In Logistics you don’t have the luxury of not driving in these conditions. Your supply chain, drop SLA’s and customer experience is critical to your business success. You could use weather records for the past 50 years and apply this data analysis to your business and the standard journeys your fleet make. Predicting the weather forecast and conditions and planning accordingly is also a very real possibility. What if you could have weather data accurate to 500m Sq and plan to avoid an area altogether? Having historic and real-time traffic data could help you predict traffic patterns or hot spots to avoid.
The benefits of big data in logistics are:
- Increased safety of your staff.
- Reducing the maintenance and repair costs of your fleet.
- Help avoid late drop offs and stock loss.
- Increase customer satisfaction and experience ratings.
Have you thought about your Social profile? What are your customers are saying about you to the world?
The good news is that all of the external data sources mentioned above are available and are being used to benefit distribution and logistics companies. The entry point into working with a specialist partner and receiving external data is more cost effective than you think. I am working with a couple of industry leading logistics companies currently, looking at the benefits of big data.
Save time, increase safety , lower your fuel cost and fleet maintenance costs, increase customer satisfaction.
Which logistics company doesn’t want to do all those things?
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