Insight
Why Ask Why? Thinking Deeply About What Drives Us to Maintain Assets
We've put together a list of "whys" every operations supervisor ought to ask of his or her equipment.
You walk into your kitchen, open the refrigerator and stand there staring at the illuminated contents for a few seconds, maybe a minute or two. For a while your mind is empty, then you start having those thoughts: Why did I come into the kitchen? Why did I open the fridge? Am I hungry? Thirsty? No? Then why am I in here?
Most of us would chalk it up to creeping senility, a sign we're losing touch. Truth be told, whatever impulse drives you to question rote, unconscious actions is a valuable tool when assessing your current asset management program. Every action pertaining to the equipment in your facility or facilities – whether it's maintenance, standard manual operation or routine diagnostics – requires the occasional and penetrative inquiry into exactly why it's done and in this particular way.
The answer should align with greater business goals, but a deeper probe may reveal only more mystery. We perform machine changeover in this manner because it's the most efficient way to do it. Yes, but how much more efficient? How are you grading efficiency? How was this efficiency tested? How does this efficiency rank among competitors or other equipment models? Would a machine upgrade or replacement be more cost-effective than settling for your highest standard? Call it root cause analysis for your analysis.
When was the last time you dived into the metaphysics of your asset management strategies? We've put together a list of "whys" every operations supervisor ought to ask of his or her equipment.
"Have you recently examined the metric by which you gauge 'need'?"
Why are we maintaining this?
Obvious answer: Because we paid for it and we need it, otherwise we wouldn't have paid for it. Fair enough, but have you recently examined the metric by which you gauge "need?" Needs change as businesses evolve, and your asset management system must account for that.
Let's say a plumbing fixture manufacturer sought to increase production on low-flow faucet heads because consumer demand called for it. In turn, all related production equipment rose in importance. Their uptime is now imperative. But what about tomorrow? What about a month from then?
When compared to the proactive, data-rich enterprise asset management practices of today, reactive maintenance is practically medieval. Yet many organizations still forget to weigh asset value against criticality; it's not enough to scrutinize crucial assets and preempt failure, but we must also ask why it's maintained now when other work orders sit unattended in a maintenance professional's docket.
Furthermore, businesses cannot fully utilize criticality rankings without flexible asset management technology that allows for immediate realignment from the top down. As the direction of the organization shifts, asset maintenance shifts with it. In industries with capital-intensive machinery and processes heavily reliant on asset reliability, there can be no other way.
"Too many companies store an abundance of stagnant data."
Why are we collecting this data?
According to risk management research from Deloitte, many asset overseers predominantly collect "static asset data" as opposed to more granular information like incident reports, environmental conditions or root cause analysis. Total data for nearly 7 out of 10 respondents consists of between 71 and 95 percent "static" data. In short, too many companies store an abundance of stagnant data.
What does Deloitte mean by "static?" Things like an asset's model number, who made it, where it's located, etc. Nobody will tell you this information isn't important at times, or that its inclusion in an enterprise asset management system is unjustified. That said, this type of data will not help make asset management strategies and proactive maintenance programs more actionable. Moreover, the volume of static data when compared to other dynamic data is far too high and too commonplace.
Without getting too far into it, Deloitte's survey also revealed the antiquated means by which companies capture and condition data. More than half still log on paper and the quality of the registered data, by the respondent's own admission, appears abysmal at worst and passable at best, indicating a lack of data integration capabilities commensurate with the move to big data.
If asset management is to progress, how we acquire the information to protect its upward trajectory must follow suit. We must know, and be able to apply, the following:
- How has equipment performed in the past?
- How is it expected to perform in the near future?
- Are there mechanical conditions operators and maintenance pros need a bead on?
- How will downtime impact finances at any given moment?
- When would be best to schedule downtime for equipment?
- What came of root cause analysis for past incidents?
The list goes on and on, but let us be clear: Although we may stress the importance of these questions here, business leaders must ultimately decide which key performance indicators to track and when based on historical data. Face facts: When IBM estimates the world produces 2.5 quintillion bytes of data every single day, businesses ought to understand they cannot track everything. If they try to, they'll almost certainly risk stretching themselves too thin, overspending on technological resources like storage and missing what's truly important to their survival when most crucial.
Why move to enterprise asset management at all?
If no process, asset or managerial style evades scrutiny in this data-driven age, then what about disciplines like enterprise asset management? Shouldn't we throw it under the microscope as well?
Of course you should, and you should be sure you run a careful eye over the reasons you adopted EAM strategies to begin with. What problems needed solving? Has EAM helped find resolutions to those problems? What's holding your organization back from implementing full EAM?
Proactive asset management and maintenance programs have the potential to fortify uptime, increase the life of valuable equipment, reduce repetitive tasks among highly skilled laborers, correct recurring inimical behavior in "bad actors," optimize MRO inventory, etc., all of which are but one degree of separation from maximized throughput, lower operational costs and less uncertainty on the production line. But it would be wrong to assume any EAM solution provides all this out of the box. Like it is a poor craftsman who blames his tools, it is a foolish one who believes tools create without hands to guide them.
Almost always, EAM adoption starts as a fix to a specific issue and then permeates the organization once adopters realize its limitless application potential. But it all starts with one question: Why aren't we doing anything about this problem?