For a long time, companies have primarily relied on experience, intuition, and impressions. While these methods have certainly proven effective over the years, they show their limits when a key person leaves the organization. In a way, we tend to value the data held by these key people. When it comes to retirement, a knowledge transfer plan is often put in place to gather as much information as possible. However, when the departure is unexpected, the situation becomes more complex and can leave the company in a delicate position.
Data is science. It provides you with objective truth, independent of external influences. No matter the mood of your dispatcher or the issues they faced last week, data remains impartial. Of course, it needs to be interpreted and contextualized, but it is an incredibly valuable source of information. We would be foolish to do without it.
Dashboards
In the daily operations of a business, decisions are often made quickly, with little supporting information. One might turn to the company’s “old hand” and ask, “Have you experienced this before?” I’m not suggesting that this approach is useless. No one has time to pull up a graph to analyze trends from the past few weeks before making a decision. However, a good dashboard, providing a clear snapshot at a glance every morning, can greatly facilitate decision-making throughout the day.
One of the biggest pitfalls when it comes to dashboards is including too many indicators. When we first discover the potential of these tools, we often flood everyone with reports and data. It’s essential to understand the needs and mission of the department in order to target the most relevant indicators. The question I often asked my manager when setting up the indicators was: “What should I see, in a single glance, to know if we are aligned with the goals?” This seems simple, but it’s actually more complex than it seems. I won’t go into detail on the indicators, as I encourage you to read the article “How to Make Your Performance Indicators Effective” on this blog.
Transport Data, Now More Accessible Than Ever
The arrival and deployment of telematics have made data access easier than ever. How can you manage a driver’s habits without being in the vehicle with them every day? How can you determine the cause of an accident if you have to rely solely on the testimonies of the parties involved? Telematics becomes a valuable ally in managing the operations of transport companies. And I’m not even talking about adding artificial intelligence to the equation, which makes the tool even more powerful and efficient. But how does it work?
Most telematics companies offer a data stream based on a time interval. For example, every 30 seconds, you receive new data. In 30 seconds, a lot can happen on the road, such as an accident. If it happens between two data updates, the information is lost. If you choose a shorter interval, say, every second, the volume of data becomes enormous, as do the associated hosting costs.
The difference with Geotab lies in its Curve algorithm. This algorithm identifies key points in the data stream, providing reliable and accurate information in a continuous and well-controlled flow. You can watch a video where Neil Cawse, Geotab’s president, explains this in detail here.
In my opinion, this is an extremely important competitive advantage, but unfortunately, it is not well-known. The quantity and quality of data are essential for making good decisions. If you communicate information based on inaccurate data, your employees will be quick to point it out. And then, the question will always come back: “Are you sure about your numbers this time?” We want to avoid this kind of situation at all costs, believe me.
Examples of Using Data
There are many examples to illustrate the importance of data, but here are two particularly relevant ones:
- Safety and Compliance: Thanks to data, it’s easy to reconstruct an accident as if we were there. Even without a dash cam, it is possible to determine the vehicle’s speed, whether the driver braked, and the nature of the collision (head-on, side impact, etc.). Data transforms into a story that can defend us in case of an unjust accusation. In committee, this information carries significant weight.
- Maintenance: I use data extensively for preventive maintenance, but we are seeing more and more initiatives in predictive maintenance. The difference lies in the trigger for repairs. In preventive maintenance, we rely on a time interval or mileage, whereas in predictive maintenance, we focus on anomalies, such as a sensor sending unusual values. For example, if we frequently replace thermostats on our vehicles, we can analyze the data from the past years to identify their useful life. If thermostats fail between 40,000 and 50,000 kilometers, we need to decide whether it’s better to replace them proactively at 39,000 kilometers or accept the risk of failure due to the low severity and wide range, making it difficult to establish a clear trend.
IN SUMMARY
In conclusion, I believe that data is a key element that distinguishes successful companies from those that excel. It’s thanks to this tool that you can stop constantly reacting and start better anticipating upcoming challenges. Data allows you to make informed and relevant decisions. How many times have I discussed with clients who didn’t think they had vehicles suitable for electrification, but after analyzing usage data from the past years, they discovered they had more than ten?
Facts are always more telling than rumors or impressions, which have served us well for years. In a context where competitiveness is constantly increasing, it is essential to leverage this often underutilized wealth. Take the time to understand your data, seek support to establish a solid structure, and choose a reliable and secure data source. This way, you’ll ensure that you don’t miss anything in your operations and guarantee your success.
