How to implement maintenance indicators step by step (real case)

In one line

Implementing indicators is not about memorizing MTBF or availability formulas: it is about deciding what gets measured, where each piece of data comes from, who enters it, how often it is reviewed and what target you are aiming for. The case of a real industrial workshop shows how to build that complete system with the limited resources of a small or mid-sized business, not a plant with a CMMS and a large budget.

What it is

Most maintenance managers know the formulas for MTBF, MTTR or availability. Few actually have an indicator system up and running. The difference between "knowing the formula" and "implementing it" comes down to four questions that are almost never answered in writing:

• Which record does the data come from? (equipment history sheet, work order, billing)
• Who is responsible for entering it?
• How often is it measured and how often is it reviewed?
• What is the target, and what happens if it is not met?

Without those four answers, an indicator is just a formula in a spreadsheet that nobody updates by the third month.

What it is for

• Moving from managing by gut feeling ("this machine always gives us trouble") to managing with data.
• Prioritizing which equipment and which costs to tackle first, instead of spreading the effort evenly.
• Leaving behind a documented base (equipment history, costs, failures) that lets you compare the plant against itself over time and, where possible, against other companies in the sector.

How it is applied

The thesis documents the design of an indicator system from scratch for a metalworking shop. The process they followed can be generalized to any maintenance area that starts with nothing:

1. Set concrete objectives for the area, not generic ones. It is not "improve maintenance"; it is something measurable: reduce costs, identify improvement opportunities, rank among the top in the sector in customer perception. A vague objective makes it impossible to decide later which indicator serves it.

2. Choose indicators based on what the company can actually collect. The point is not to copy the complete list of possible indicators (there are dozens: operational, economic, equipment, labor), but to filter by the size of the company and the quality of the records that already exist. An indicator that requires data nobody records today is dead on arrival.

3. Formalize each indicator in a data sheet, not just a formula. For each selected indicator: the calculation formula, which document the input data comes from, and which role (a role, not a person) is responsible for producing it. This is what turns a list of formulas into a system you can operate.

4. Assign a measurement frequency and a review frequency. Not all indicators are measured equally often: operational ones (availability, effectiveness) are usually reviewed monthly or quarterly, labor or safety ones can be monthly, and those that depend on longer-term trends (such as mean time between corrective actions) work better in six-month windows.

5. Review the advantages and disadvantages of each indicator before starting. Every indicator has a blind spot. Spotting it before you implement it avoids wrong decisions based on a misread number (there are concrete examples below).

6. Choose the critical equipment first, not the whole fleet at once. With limited resources, it makes sense to measure first the equipment with the heaviest use and no backup (if it breaks, there is no other unit to cover the operation), and leave duplicated or occasional-use equipment for later.

Predictiva21 sums this up with the SMART criterion: a maintenance indicator is worth having if it is specific, measurable, achievable, relevant to the area's objective, and has a defined review deadline. A KPI that fails any of these five points tends to be abandoned within a few months, no matter how well the formula is calculated.

Real example

The case is Taller Industrial ADIFE LTDA, a metalworking company in Cartagena de Indias (Colombia) founded in 1988, which in 2002 went from informal family management to a management run by a mechanical engineer. That is where the indicator project started, with three stated objectives: reduce costs, identify improvement opportunities, and rank among the ten preferred workshops in the industrial sector of the area.

The 14 indicators, grouped by category:

• Operational: equipment availability, quality related to use, effectiveness.
• Economic: maintenance cost as a share of billing, operating cost of availability, operating cost per production, cost components of maintenance, external labor cost, maintenance cost relative to production.
• Equipment: mean time between corrective actions.
• Labor and safety: corrective maintenance jobs, accident frequency rate, accident severity rate, overtime rate.

For each one, the work defined three things in addition to the formula: which record the data comes from (equipment history sheet, work order report, billing for the period), which role is responsible for collecting it (plant supervisor, machine operator, accounting, safety committee), and how often it is measured and reported (monthly for the economic and overtime indicators, quarterly for the operational ones, every six months for mean time between corrective actions and the labor indicators).

As an example of a formula: equipment availability was calculated as (calendar hours − maintenance downtime hours) ÷ calendar hours × 100. Maintenance cost as a share of billing was calculated as total maintenance cost for the period ÷ billing for the same period × 100.

Selection of critical equipment. The workshop had more machines than it could monitor at the outset, so it prioritized seven: three lathes, a 70-ton hydraulic press, an industrial planer and two welding units (TIG and MIG). The criterion was heavier use and no backup — if one of those lathes broke, there was no identical one to absorb the work. Drill presses, threading machines and oxy-fuel cutting equipment were left out of this first stage, because the workshop had several units of each and that redundancy lowered the urgency of measuring them.

The tracking traffic light. To visualize progress against the six-month target, a simple scheme was used: red (far from the target), yellow (close to the target) and green (target reached or exceeded), applied indicator by indicator and equipment by equipment.

An honest note about this case: at the time the thesis was published, the final results table was still blank — it was the template the workshop was going to fill in month by month over the following six months. This is typical of what happens in most small and mid-sized businesses: designing the indicator system is not the hard part; sustaining it with data entered faithfully for months is.

Benefits

• It turns maintenance management into something comparable over time: the same equipment against itself, month by month.
• It leaves a documented archive (equipment history, costs, failures) that serves as a basis for future benchmarking against other companies in the sector, something the thesis itself points to as one of the workshop's medium-term objectives.
• By explicitly defining who enters each piece of data, it moves maintenance away from the "firefighting" mindset and turns it into information that supports decisions (where to invest, which equipment to replace, whether the problem lies in spare parts or in procedure).

Limitations to keep in mind

• Fourteen indicators is ambitious for a small or mid-sized business with no staff dedicated to this: the real risk is that the system gets abandoned if nobody has time assigned to enter the data every month. It is better to start with fewer indicators and add more gradually.
• Several indicators only work well in combination with others: for example, measuring "corrective maintenance jobs" without its preventive counterpart can lead to the wrong conclusion that all maintenance is reactive, when in fact the data on the preventive side is missing.
• The quality of the whole system depends on discipline in records such as the equipment history sheet. If that record is weak or inconsistent, the indicators that depend on it inherit the same problem.

In summary

Implementing maintenance indicators is a process, not a formula: set concrete objectives, choose indicators that match what the company can measure, formalize each one with its data source and owner, define its frequency and target, and start with the critical equipment. The ADIFE workshop case shows this can be done without a CMMS or a large budget — with one condition: someone has to keep up the data entry month after month, or the best-designed system in the world ends up sitting in a folder.