Our Director of Strategy Greg Mattes recently attended The Work Truck Show in Indianapolis this March. He got a lot value from the conference, including the session Integrating Multiple Data Streams to Enhance Fleet Decision Making.
Large datasets can be overwhelming, and it can be difficult to determine where to start. As technology allows fleets to collect more and more data points from vehicles, this information becomes increasingly applicable.
For those who couldn’t attend this Work Truck Show lecture, we’ve distilled the information to help you start taking advantage of the opportunities data provides.
More data, better stories
The more data points you have, the better stories you can develop about your fleet. This could mean collecting data over longer time periods, including more locations or more fleet tasks.
Data aggregation can initially be overwhelming, but it does not have to be hard. Consider all of the information to determine (1) what has been done (2) what should you be doing?
Start with dollars
When you start crunching numbers, focus on cost or data with dollars first because this is what has the greatest impact on your bottom line. Key data in this category include maintenance and service, fuel and insurance.
Then, add on contextual information to interpret the data correctly. Useful context includes location, mapping and routing and additional information outside of your fleet like weather, road construction, etc.
Take a step back
If you are not seeing a pattern in your results, sometimes you need to take a different approach. If looking at all the data at once doesn’t reveal anything, consider looking at what isn’t there, in other words, the holes in the data.
Capitalize on data integration
Data integration enables information to funnel from its source to a database and helps eliminate manual entry. Not having to rekey information saves times, permits scalability and allows your to focus on your core business.
If your telematic system or fleet maintenance software offers an Application Program Interface (API), take advantage of it.
Pay attention to the outliers
Trends are tidy and can provide a clear picture into fleet operations. However, sometimes the most valuable information comes from data points that do not follow the trends—outliers.
Outlier reporting is crucial to pinpointing anomalies and determining the greatest opportunities for improvement.
An ideal data process involves the following steps:
- Data manipulation and readiness - Gather data and information - Perform data prep - Establish baseline for comparison - Select criteria for assessment
- Progress measurement - Document the baseline and initial conditions - Compute and compare performance data - Document results of progress measurements - Determine course of action - Note change in assessment criteria and collect survey data
- Predictive modeling - Evaluate process and record results - Conduct trend analysis
The best thing you can do when it comes to using fleet data is to start. Start small, wherever you feel comfortable, and expand from there.