The four most common failures when implementing EAM software
Successful asset management is predicated on a clear understanding of the intention of the system prior to implementation. John Woodhouse points to four main mistakes that businesses make when putting in place EAM software and offers ways to avoid these derailments
When an organisation implements enterprise asset management (EAM) software, it’s a multi-pronged challenge.
You are introducing a system to track assets and manage maintenance work at the same time as enabling – or constraining, for greater consistency – some complex, cross-disciplinary business processes such as planning, resource coordination, performance reporting, and decision-support.
Two levels of thinking are needed:
- The daily mechanics of data models, work orders, and information flows: “What do we want or need to do in the first place?”
- The strategic level: “ How can we use the information system to get better?”
To successfully implement EAM software in line with the full range of asset management activities, you have to address both levels at once.
Any large enterprise software application can be a challenge to implement. But an EAM system, because it affects most of the organisation, is one of the most difficult to deploy effectively.
Here are a few of the most common mistakes that people make when implementing EAM software:
Big is bad, small is good
The chance of failure rises geometrically with the scale of IT projects, especially if they are cross-disciplinary.
If the project gets too big, the truth about its poor cost/benefit ratio is often hidden through embarrassment, vested interests, or a sense of powerlessness to tame the beast.
It is better to go through a prioritised series of smaller, more manageable stages than to try to do it in one big integrated systems project.
Mismatch between IT capability and the organisation’s level of understanding of asset management processes
Underexploited technology is an expensive waste, and insufficient sophistication leads to frustration and disillusionment.
IT innovation occurs at a very different pace to that of organisational maturity or workforce understanding of the technology.
Tied into this common misalignment of “capability versus readiness” is the lure of the flashing lights – the overselling of (and gullible belief in) a fancy technology that will somehow make all the problems go away.
Instead, mistimed or overly-sophisticated technologies can even make problems worse, such as helping you to do the wrong things quicker, or introducing more cost and confusion.
Insufficient investment in training, communications, and engagement
System developers and integrators rarely appreciate the importance and scale of efforts needed to address human factors.
When IT budgets overrun, the training budget is the first to feel the twang of tightening purse strings. Training methods are often naïve and shallow – out of touch with the human factors needed to establish competency and confidence.
Data quality is a moving target
Setting a fixed target such as “I want all data to meet a plus or minus five per cent accuracy” is a completely inappropriate and false hope. A fixed target for data quality is a distraction from reality.
Spurious accuracy is an endemic weakness of most EAM systems, for example, when a system forces you to enter a cost to two decimal places even if the value is only known to +/- 30 per cent.
The common perception that available hard data is either pretty good or total rubbish. Uncertainty and confidence limits, range estimates, and fuzzy knowledge are all areas where EAM systems struggle, yet they are a reality of asset management.
Forcing uncertain information into EAM hard-edged boxes, or believing information just because it is presented in a multiple digit format, leads to loss of long-term credibility and support for the system.