I'm always amazed at the fleet professionals that spend thousands of dollars to capture vehicle data and yet fail to use the data effectively. You would think this is a no brainer! There are a number of fleet professionals that I speak with who have lots of data but have no idea how to put it to good use. Below are some tips to consider:
First, determine what data you have available. The easiest way to think about the data you have available is to divide into manageable segments. For example, you might consider using these four elementary categories as a starting point: 1. Inventory data, 2. Maintenance data, 3. Fuel data, and 4. Mileage data. These four data components allow you to create the following thirteen core metrics which are useful to begin benchmarking your fleet - at a high level - against industry, peers, and most importantly your own organization.
1. Total vehicles
2. Total fuel cost
3. Total Maintenance cost
4. Total fuel gallons
5. Total miles per period (i.e. month, year, life, etc.)
6. Percent use versus set utilization standards or expectations (i.e. 12,000 miles a year, etc)
7. Cost per mile fuel
8. Cost per month fuel (Useful if you fleet mileage is problematic)
9. Cost per mile maintenance
10. Cost per month maintenance
11. Fuel miles per gallon
12. Combined cost per mile (fuel and maintenance)
13. Combined cost per month
Obviously there are numerous other metrics useful in managing a fleet operation,but without core metrics you cannot even begin to start benchmarking your fleet performance.
Second, review each of the vehicles in your "inventory" and determine which vehicles have the other three components (i.e. maintenance, fuel and mileage). During this initial stage keep in mind the capture of any data is good. I like to tell people that bad data is better than no data! You can always improve bad data but you can't improve data you don't capture.
Third, organize the data by user departments, agencies or cost centers to evaluate and determine where gaps exist. I have found that some departments, users and agencies are better than others when it comes to data entry and capture. If you use an outsource maintenance and/or fuel contractor - and have an automated interface - this may or may not be an issue. Especially if the data is downloaded to your Fleet Management Information System (FMIS) on a routine basis. I recommend you determine the percent of vehicles with data by cost center. For example, if an agency has 10 vehicles and they all have fuel data then they have 100% of fuel data, etc. Obviously this is not absolutely empirical but it stands to reason if a vehicle has some data that the agency is making an effort to capture this data.
Fourth, create a data profile using a spreadsheet and color code or grade the data so you can determine where gaps exist. Personally, I prefer using a color coding scheme where green is "Acceptable", "yellow" equals "needs improvement" and red means "unacceptable". This way you can determine at a glance where to begin the continuous improvement process. Then by systematically working on the "red" data you can begin improving the quality and quantity of your data. Your goal is obviously to get 100% data compliance in all four categories by working on the worse to first.
Finally, once you organize the data into manageable categories you can easily convert your spreadsheet into pivot tables and better analyze how each of the metrics shape up to begin looking at comparisons. Placing metrics in this format allows you to easily compare your metrics to known benchmarking publications for comparison.
Give this a try. More to come...
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