The Four Most Common Failures When Implementing Enterprise Asset Management Software ( Getting Ready for ISO 55000 – Part 9 of 12 )
[ Insights from the “Asset Management for the 21st Century—Getting Ready for ISO 55000” Seminar, May 2013, Calgary (Part 9 of 12): This blog is based on a series of interviews with John Woodhouse from the Woodhouse Partnership (TWPL), who delivered this well-received seminar. It is part of a blog series brought to you by Norm Poynter and Paul Kurchina, designed to inspire and educate by sharing experiences with the SAP Enterprise Asset Management Community. ]
When an organization implements EAM software, it’s a challenge because 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. So two levels of thinking are needed—the daily mechanics of data models, work orders, and information flows, as well as the more strategic level: “What do we want or need to do in the first place, and how can we use the information system to get better at it?”
To successfully implement EAM software in line with the full range of asset management activities (and not just maintenance management), 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 organization, is one of the most difficult to effectively deploy. Here are a few of the most common mistakes that people make when implementing enterprise asset management 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. And 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’s better to go through a prioritized series of smaller, more manageable stages than to try to do it in one big integrated systems project.
Mismatch between IT capability and the organization’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 organizational 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, and when IT budgets overrun (not unusual!), the training budget often gets raided. And training methods are often naive 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 5% 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 (e.g., the system forcing you to enter a cost to 2 decimal places even if the value is only known to +/- 30%). So too is 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.
For more information, here’s a post with all of the links to the published blogs in this series.