Making big data manageable
Connectivity is totally changing the way in which fleets operate. Real-time visibility on the likes of assets and remote equipment, wireless engine software revisions, instantaneous customer-service feedback, dynamic routing and scheduling is having a fundamental impact on how organisations drive efficiencies and deliver compelling customer experiences. And this is just the tip of the iceberg for what connectivity can bring.
At the centre of all this is the need to harness the data being created. Those embracing the power of data are gaining a competitive edge – they join the thousands of other fleets around the globe that are mining it for intel that can help boost the bottom line of their business.
The challenge created by connectivity is no longer implementation of hardware and software that suits your fleet. Intuitive, platform-based approaches have made choosing, fitting and onboarding telematics and connected business intelligence systems easy.
The real challenge comes in the ability to analyse, merge and action the volume of data churned out by these sophisticated platforms that are at the heart of connected vehicles, and then to apply them to the real time or the future running of a fleet.
So what are the practical hurdles that need to be overcome with the application of Big Data to businesses that run commercial vehicles?
Firstly, to achieve the maximum business value from Big Data, there needs to be a cultural shift amongst employees. Big data sounds complex; it sounds like another obstacle in an already complex logistics operation. It shouldn’t be. Teaching drivers and managers how to make use of reports from telematics and business intelligence data is an important first step. But educating staff on the value data can drive is the main task – fuel efficiency, driver safety, supply chain benefits, smart routing and ultimately, more profit within the business, or for your customers.
To do this, map a timeline of integration and implementation of data into the business. This should involve input from individuals with existing skills in data, as well as the business owners. Once this education piece has been achieved, you will have an organisation that is focused on getting the maximum value out of data and it will be much easier to gain insights from various processes throughout a business.
Secondly, even small fleets have the potential to generate a huge amount of data. The data created by big fleets can be overwhelming at first. To give an idea of scale, Telogis connected mobile business software is currently processing more than 350 million data points for fleets around the globe every day. So you have to have a method of sifting through, capturing and understanding the data.
The first point of call is to be clear on what you want to achieve. What are the insights that will help your fleet run more profitably? Is it better segmentation of the customer base? Is it driver data, such as idling time or acceleration information? Is it working schedules? Or is it real-time traffic info and the ability to pass this on to drivers to avoid congestion? Good platforms will help you visualise, report on and action these parameters.
The second point of call is to make sure that what you are tracking and analysing supports the broader company strategy, goals and objectives. Determine what is most important to your particular business strategy and current objectives, and allow that to drive the metrics you will track.
Thirdly, it’s vital to remember the key rule of Big Data - correlation does not mean causation. Just because there is a relationship between two trends does not mean that one influences the other. This means it’s vital to have an experienced team analysing and evaluating the data. Analytics are only effective when technical and statistical understanding is matched with industry experience.
Finally, work against industry benchmarks. It can be tempting to consider fleet data in the vacuum of your own organisation. Instead, managers should look more broadly to other organisations, in different sectors, globally. Fleets are complex and while managers can be trained to effectively analyse their own data, without insights and benchmarks to compare against, they might be working toward the wrong goals.
Companies that are able to derive the right insights from such a vast amount and variety of data will be able to create new and significant value for their own and for customers’ businesses. If managers follow these simple steps, they will be able to turn fleet management on its head and also drive significant impact on the bottom line of the business.