A points system for existing assets be a huge asset in times of supply shortages.
As operations return to ‘normal’ after two years of unprecedented challenges, we can breathe a collective sigh of relief, or can we? Fleets may be back to providing the full range of support to operations they were doing pre-pandemic, but they are doing so under conditions that are less than ideal. For many fleets, vehicle replacement slowed or stopped during the pandemic but they are not necessarily in a position to address the backlog in 2022. Two main issues may prevent this:
- Funds needed for fleet capital replacement have been diverted to higher COVID-related priorities and funds are not available.
- Where funds are sufficient, the availability of certain vehicle types has been impacted by a slow or broken supply chain.
Without the expected access to new vehicles, many fleet organizations need to be selective regarding which vehicles get replaced. Systems to prioritize replacement no longer rely on simply age and odometer but combine factors in a point system to ensure scarce replacement dollars are spent wisely.
Point systems for fleet replacement can take into account the traditional measures of age and mileage but often include downtime, maintenance costs (lifetime and last 12 months), condition and even driver preference. Many Fleet Management Information Systems have integrated tools to do this assessment but fleet managers can also create a simple spreadsheet in excel to track priorities for replacement. You might want to start with age and mileage:
| Asset Age – Points Calculation | ||
| % Life Left | Gen Wear | Points |
| 75-100% | Very Good | 1 |
| 50-75% | Good | 2 |
| 25-50% | Fair | 3 |
| 0-25% | At Risk | 4 |
| ≤ 0% | High Risk | 5 |
| Asset Meter – Points Calculation | ||
| % Life Left | Description | Points |
| 75-100% | Km/hrs less than 25% | 1 |
| 50-75% | Km/hrs 25-50% | 2 |
| 25-50% | Km/hrs 50-75% | 3 |
| 0-25% | Km/hrs more than 75% | 4 |
| ≤ 0% | Km/hrs more than 100% | 5 |
From these, move to more refined measures:
| Lifetime Maintenance Costs – Points Calculation | ||
| % Life Left | Main Costs | Points |
| 91-100% | Under 10% of purchase | 1 |
| 81-90% | 10-19% of purchase | 2 |
| 71-80% | 20-29% of purchase | 3 |
| 61-70% | 30-39% of purchase | 4 |
| 51-60% | 40-49% of purchase | 5 |
| 41-50% | 50-59% of purchase | 6 |
| 31-40% | 60-69% of purchase | 7 |
| 21-30% | 70-79% of purchase | 8 |
| 11-20% | 80-89% of purchase | 9 |
| ≤ 10% | More than 90% of purchase | 10 |
| 12-month Maint Costs | ||
| ≤ 10% | 0 | |
| More than 11% | 2 | |
All of the factors shown above are data-driven and can be calculated using data that most fleets track. There may be other factors that require additional input:
| Condition – Points Calculation | ||
| Condition | Definition | Points |
| Excellent | Body and Drivetrain working perfectly | -2 |
| Very Good | No rust, good drivetrain and engine | -1 |
| Good | Expected wear and tear for age | 0 |
| Fair | Minor imperfections, drivetrain working | 1 |
| Poor | Deterioration in body, signs of imminent failure | 2 |
Condition Assessments require a hands-on, slightly subjective evaluation of the asset. Increasingly, fleet organizations start including a condition assessment as part of the annual preventative maintenance schedule as assets near the end of their lifecycles.
Bringing all of this information together enables the organization to quickly identify priorities for replacement. Naturally, the higher the score, the higher the priority and each organization can set limits or thresholds that trigger immediate replacement.
Kate Vigneau, CAFM, is Director (Fleet and Canada) for Matrix Consulting Group. She is responsible for Matrix’s fleet solutions division as well as the lead for expansion in all functional areas related to business in Canada.
