RS’ Richard Jeffers explains how to develop effective KPIs to evaluate your maintenance performance for MRO
All organisations are under pressure to continuously boost their capabilities to create value for customers and improve the cost effectiveness of their operations.
This has led to a number of key changes impacting the maintenance function:
- The maintenance outsourcing industry has gained in maturity, leading to an increasing separation of the asset owner from the supporting maintenance function as organisations outsource maintenance for a perceived cost saving
- Industry has become more capital and less labour intensive, leading to an increase in the absolute cost of maintenance – this makes it a larger target for top-down, arbitrary cost cutting
- The maintenance of capital assets, once thought of as a necessary evil, is increasingly being seen as critical to creating value for an organisation and not just as a cost centre as organisations look to increase the flexibility of the assets and defer capital expenditure
- Maintenance management has matured from a focus on breakdown and time-based scheduled restoration with world class organisations focused increasingly on predictive tools and on implementation strategies such as condition-based maintenance, remote-maintenance, e-maintenance, reliability centred maintenance and Total Productive Maintenance (TPM) to preserve the functions of assets and mitigate the impact of component failure
- Failures in safety and environmental systems need to be managed as low as reasonably practicable with many safety systems exhibiting hidden failure modes, necessitating intelligent testing and maintenance of these systems, which will only be required when multiple failures occur together
As a result of these, and other developments, the challenges facing organisations are to choose the most efficient and cost-effective maintenance strategies to minimise not just the maintenance cost, but the total life cycle cost of production assets, while ensuring that all asset related risks are effectively managed. This requires the maintenance function to have the same business wide view of key performance indicators (KPIs) through a balanced scorecard as other, historically more commercial focused, parts of the organisation have held. Here, I don’t want to talk about how to develop a balanced scorecard, but rather to focus on suitable performance indicators to monitor maintenance effectiveness. However, the development of a maintenance scorecard should follow the key stages for development of any balanced scorecard:
- Translating the vision into operational goals and expressing it in terms that can guide action at local level
- Communicating the vision and linking it to individual performance
- Business planning: integrating operational plans with financial plans
- Feedback and learning, and adjusting the strategy accordingly
Like other elements of the Management Control and Reporting System (MCRS) in an organisation, the maintenance KPIs should drive decisions at multiple levels: strategic, operational and tactical, with a timeframe of review based in months or years at the strategic level, down to daily or less at the tactical level. They should also have a blend of lagging indicators, measuring the past, and leading indicators – giving an indication of change in the future.
A suitable hierarchy of maintenance KPIs could be:
Goal | Keeping operational assets fit for purpose in the hands of the user at best cost |
|---|---|
Strategic KPIs | Maintenance related safety & environmental Incidents Site / department OEE (overall equipment effectiveness) Maintenance cost / Replacement Asset Value Maintenance cost / Total conversion cost |
Operational KPIs | MTBF (Mean Time Between Failures) MTTR (Mean Time To Repair) MTBA (Mean Time Between Assists) Ratio: Planned / Corrective Work Ratio: scheduled / total downtime Right First Time on failure analysis / loss eradication Budget adherence Spare parts valuation by category Line / Area OEE Shutdown effectiveness |
Tactical KPIs | Labour productivity / saturation Maintenance back log / Work Order completion rates Labour planning accuracy Stock accuracy / obsolescence Asset OEE PM day effectiveness / Scheduling effectiveness Failure analysis completion |
The split into the different levels of KPIs is important:
Strategic
At this layer we are looking to manage risk down and reduce the cost of managing that risk. We want to understand if our failure rate is reducing and ensure we are doing that at a sustainable cost. Once we are in control of the risks, we can start to look at driving down the cost of the risk mitigation.
Operational
At this layer we are measuring the specific indicators that tell us we are heading the right way. Our MTBF is increasing whilst our MTTR reduces. These, together, drive a reduction in the OEE losses. By ensuring that we are completing our failure analysis right first time, and putting in place the right countermeasures, we are slowly eradicating the losses.
Tactical
At this layer we are focusing on specific day-to-day activity around effective resource management, work order completion, stock management and rigorously completing failure analysis. It is vital when implementing maintenance KPIs that the number of indicators implemented at the start are commensurate with the ability of the team to use them to drive meaningful actions, and in line with the strategic drivers of the organisation. In a previous organisation I worked with, we implemented a whole suite of KPIs in the management of engineering spares, despite the fact that we were broadly in control of spares – but the effectiveness of our problem-solving needed enhancement. A lot of time and energy can be spent arguing over KPI definitions. Where possible, use standard definitions, such as those in BS EN 15341 – Maintenance KPIs:
- Maintenance managers can rely on a single set of predefined indicators supported by a glossary of terms and definitions
- The use of common indicators makes it easier to compare maintenance and reliability performance across sites or organisations
- Effort can go into the value creation process of generating the balanced scorecard, not on generating definitions
- Generic KPIs are often supported in the Computerised Maintenance Management System (CMMS) without additional coding
- The need for discussion and debate on indicator definitions is ended and uncertainties are eliminated
Definition of “world class” results for maintenance indicators is notoriously very difficult. At another organisation I worked with in the past, we generated a complex analysis tool that correlated internal labour, external labour and spares usage to OEE over 20 high speed beverage lines on four sites. The conclusion the data suggested was that a lower maintenance spend equated to a higher OEE. It was only when we factored in a measure of operator engagement in maintenance, which wasn’t shown in the maintenance budget, that the real story became clear: high levels of operator engagement drive higher OEE and lower expenditure on spares and contractors.
The table below is drawn from the relevant sources referenced below. All the cost numbers are based on maintaining the assets at their ‘basic conditions’. They do not include additional funding to restore asset degradation. The cost ratios are based on full cost: spares plus external and internal labour.
Worst performers | Best Performers | |
|---|---|---|
Spares / Replacement Asset Value (%) | >1.3% | <0.3% |
Maintenance / Total operating costs (%) Manufacturing Processing Fabrication | >15% >15% >5% | <5% <3% <3% |
Maintenance Cost / Replacement Asset Valuation (RAV) (%) Discrete Batch processing Continuous processing | >5% >3.5% >4.8% | <2% <2.4% <2.5% |
Availability Discrete Batch processing Continuous processing | <78% <72% <85% | >91% >90% >95% |
Technician tool time | <31% | >52% |
% planned work | <65% | >95% |
Schedule compliance | <15% | >70% |
PM % by Operators | 0% | >25% |
Stores stock turn | <0.5 | >1.2 |
Sources: Campbell & Reyes-Picknell – Uptime; Kaplan & Norton (HBR) - Using the Balanced Scorecard as a Strategic Management System; Kumar, Galar, Parida, Stenström & Berges - Maintenance Performance Metrics: A State of the Art Review; Levitt – Complete Guide to Preventative and Predictive Maintenance; Mowbray – Maintenance Management: A New Paradigm; Parida & Kumar - Maintenance Productivity & Performance Measurement; Sondelini – Useful Key Performance Indicators for Maintenance; Wireman – Benchmarking Best Practices in Maintenance; Various Articles – Maintenance & Engineering magazine
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