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Is your fleet ready for big data & advanced analytics?

Fleet management presents a complex set of logistical challenges and hurdles to overcome.

As many fleet managers know, the key to streamlining operations and increasing efficiency is having greater visibility and enhancing data collection within the vehicles under your management, as well as the performance of every driver.

Adopting a data-driven approach to fleet management is the most effective way to get the visibility you need. Data highlights potential issues before they become a problem and will also help you identify new opportunities. Best of all, it’s completely customisable so you can track and report on the metrics that matter most to your business.

While your fleet management system might be able to help you identify immediate obstacles, imagine if you could predict and prevent the next breakdown. While you might have a general view of how safely your operators are driving, what if you could stop a potentially dangerous accident from happening?

The impact of big data and advanced analytics on fleet management can be truly transformative for your business, helping you to increase efficiency, enhance productivity, improve safety, and reduce costs.

What is big data?

Big data – categorically one of the most popular buzzwords in the business world – refers to extremely large and complex sets of data that are too massive to be easily managed, processed, or analysed using traditional data processing tools or methods.

In the context of fleet management and telematics, big data refers to the data generated by the operation of a fleet of vehicles or mobile assets, which includes data from various sources such as GPS devices, sensors, telematics systems, and more.

What is big data analytics?

Big data analytics is the complex process of examining big data to uncover information, such as hidden patterns, correlations, trends and driver preferences. Doing so can help fleet managers make informed business decisions to take productivity, efficiency, and safety to a whole new level.

The importance of big data in fleet management

Big data revolutionises how fleet managers manage their fleets and instantly provides them with information about their drivers, trucks and trailers through an on-board computer, telematics devices and connected software solutions. In simpler terms, they collect all the information about your fleet, process and analyse it.

The result is practical information on issues such as:

  • Driver performance
  • Fuel consumption
  • Profitable routes
  • Operational costs
  • Maintenance

Through all this data, you can easily prepare reports for shareholders, detect problems and plan training actions to combat any problems.

How does big data fleet management work?

How does big data fleet management work?

Managing your fleet using big data is a relatively simple process, if you are equipped with the right tools. Integrated fleet management platforms connect with a vehicle’s telematics unit or on-board computer to collect and transmit all the essential information.

Rather than being presented with mountains of data, the software sorts and tabulates the information in a variety of ways that make it easy to digest. It is presented in a user-friendly format, such as graphs and charts, to enable you to easily view fleet and driver performance information, prepare reports and adjust accordingly.

You can sort and filter the data, so you analyse only that which is relevant to your needs. The software itself can be customised and personalised to the needs of the fleet manager.


How to implement fleet management analytics in your business

Implementing fleet management analytics successfully requires buy-in across your entire business. Drivers, operations managers, and health & safety managers must all commit to the same goal: greater data visibility to improve safety and efficiency. The technology must also be widely adopted to be the most effective.

Analytics is about collecting and utilising data to solve business challenges and optimise current processes.

To avoid feeling overwhelmed by the amount of data that can be collected, rather focus on the areas that will have the most significant impact on your business if optimised. For example, accidents create considerable costs for businesses, so safety will be a key priority for most, if not all material handling businesses. Downtime is another key cost worth pursuing since this contributes significantly towards your total cost of ownership.

Integrating analytics into daily fleet operations for long-term success

To build an intelligent fleet management system, digital transformation isn’t optional, it’s a requirement for long-term success.

Staying competitive in the transportation industry while delivering better business outcomes will take a forward-looking strategy. It’s time to go digital now, so you’re ready for new technologies that are on the horizon. Data analytics and solutions are the foundation on which you’ll build the next wave of integrated fleet management solutions.

Building on your company’s data analytics capabilities will be essential to mitigating challenges and making the most of newer technologies now and into the future.

What you need to get started with data analytics

Based on our experience with data analytics for fleet management, we’ve identified five focus areas:

  1. Develop the right data infrastructure strategy for your business

Begin by determining what fleet data you require, how you will gather it, how you will analyse and implement findings and your scalability plans. Practically speaking, it means deciding on the type of telematics tracking you want to implement for your fleet, whether you want real-time or delayed data, who will be responsible for managing the platform, etc.

This underscores the importance of concentrating on attaining precise insights through analytics for your business. This might involve identifying the remaining operational life of each asset in your fleet, implementing predictive maintenance to extend their longevity, or ensuring that root cause analysis is integrated into guided repair procedures.

  1. Focus on what will be critical as you move forward

Think about what will make an impact on your business not just now, but into the future. There’s a lot of new technology out there, but does it solve any of your problems? Does it have a positive effect on your bottom line? What does it enable? And, a question that is often overlooked, what new revenue growth opportunities will these new insights produce?

As you develop your strategy and define your KPIs, you’ll be able to align your fleet imperatives with your technology to fully integrate analytics with specific operations, improving performance and directly impacting your bottom line.

  1. Prepare for organisational changes

Creating a forward-looking strategy that moves from a reactive model to a proactive model will inevitably create change across your company. For example, you’ll probably change the way you manage your fleet or adjust the way maintenance is done. Traditionally, for instance, a technician will make the rounds every day, find what’s broken and fix it – a reactive approach. With predictive data analytics for fleet maintenance and repair, your approach becomes proactive.

Predictive maintenance delivers insights about fleet repairs and health to your technicians. The technicians need to determine why they are getting a prediction, how to validate it, and how to proceed. This shifts the knowledge base and gives your business the agility you need to move quickly when requirements or conditions change.

  1. Prepare for changes in the workforce

The evolution in fleet management will not only affect processes but the people responsible for operating those fleets. Human capital is a limited resource, and organisations need an intelligent strategy to navigate these transitions. To attract and retain workers, it’s critical to give employees an opportunity to focus on the areas in which they have interest and expertise while minimising the time they spend on related but less rewarding activities.

Artificial intelligence, big data and autonomy are decreasing the need for humans to perform routine tasks. At the same time, these advances are increasing the amount of work in other areas, from planning and logistics to tracking, tracing and maintenance.

This means that fleet operators will need people with new kinds of expertise and operational skills. Even with increased automation and predictive analytics, certain tasks such as fleet maintenance and repair will not disappear. With the right approach, organisations can apply the benefits of AI to their fleet management systems and free up employees to focus on what they do best, or even take on new tasks that are more strategic.

  1. Focus on your business, and let data analytics experts focus on IT

It’s important to hire the appropriate people for the job who can understand the data insights. For example, fleet managers should be hired based on the fleet experience they have to understand what the system data means.

Taking advantage of the data analytics requires a lot of data management and expertise. You’re in the fleet business, not the IT business. Many organisations have turned to third-party partners to manage the IT. The best partner is one that understands your business down to the level of processes and operations, but that is also an experienced IT organisation. With the right partner, your day-to-day operations will run smoothly, and you’ll have the data structure in place to take your business to the next level.

In Summary

Fleet management is evolving rapidly, necessitating a data-driven approach for success. Big data in fleet management encompasses vast datasets generated by vehicles, including GPS, telematics, and sensor data.

Big data analytics unlocks hidden patterns and trends, enabling informed decision-making and improvements in various aspects of fleet management.

Implementing these analytics demands organisational commitment from drivers, managers, and safety personnel. Furthermore, finding skilled talent or partners with data management expertise streamlines the process, ensuring efficient data handling and freeing fleet managers to concentrate on core operations.

The question is, is your business ready?

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