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You are here: Home / Articles / Germination of a Failure-Why Does Stuff Really Break Down? – Q&A p2

by Robert (Bob) J. Latino 3 Comments

Germination of a Failure-Why Does Stuff Really Break Down? – Q&A p2

Germination of a Failure-Why Does Stuff Really Break Down? – Q&A p2

I recently presented a webinar for SMRP and Empowering Pumps, on the title above. There were several questions, post-presentation, that I felt were worthy of expanding on in the form of a blog.

Question #2 (of a total of 5)

How do you manage a situation where people just decide not to use simple tools like RCFA, just comfortable doing things same way? Even when you keep driving it.

Response: I think we can all relate to this question (and this practice). If there is no RCA policy and/or procedure outlining the specific expectations of what is required by leadership, than analysts will naturally migrate to the minimal requirements (boundaries).

This often results in being ‘compliant’ which does not necessarily ensure a bottom-line benefit. I see this often where success is to meet some minimum regulatory requirement and not to yield a measurable benefit to the organization (i.e. – production increases, injury reductions, maintenance cost reductions, inventory reductions, etc.).

I don’t blame as much the analysts for producing poor RCA’s as I do those who accept them. If I perform a ‘shallow cause analysis’ (SCA) where I just met the minimal requirements of some standard, and the powers that be accept it…then they have lowered the standard themselves.

This is often referred to as Normalization of Deviation. We are often time-pressured, so we take a short cut in our RCA efforts. As a result, when there is no negative consequence, that short cut becomes the new normal. This reiterative process continues until we have a catastrophe and then only in hindsight, it becomes clear. This drifting, or gradual decline of our standards promotes a culture of ‘forgetting to be afraid‘.

In Figure 1 I show a chart I often use, I call it the ‘hourglass’ view of RCA. In the orange, deductive phase of RCA we continually ask ‘How Could?’ the previous node have occurred, and we use our evidence to prove or disprove it. Inevitably, we will find some type of physical root cause (the physics portion of the analysis) which is tangible.

Figure 1. Root Cause v Shallow Cause Analysis

If we continue to drill down with our questioning, we will eventually get to a human root cause or decision error. This will either be an error of omission or commission, but normally this is a decision made with the best of intentions. It is not important ‘who’ made the inappropriate decision, but why they thought it was the right decision at that time, is really what is important.

When we get to decision errors our questions shift from deductive (How Could?) to inductive, using ‘Why?’ I don’t want to know ‘how could’ someone have made such a decision error, I want to know ‘Why’. We have to understand their reasoning because they did not intend on that outcome, they felt the decision was correct. Why did they think that?

Drilling down beneath the decision-maker will start to yield the true contributions to inappropriate decisions…our latent roots or management system deficiencies, cultural norms and socio-technical contributors. These are the inputs into the human mind that were helping form the decisions made. This is much easier to discern in hindsight, but much more difficult to do proactively when looking at potential risks.

When looking at this spectrum of ‘where to stop’, we can ask ourselves these questions:

  1. If we stop at some physical level (which is Root Cause Failure Analysis or RCFA) and just replace a broken part or change the vendor, will the problem go away? NO
  2. If we stop at the decision-maker and discipline them, will the problem go away? NO
  3. If we address the latent root causes, the system inputs to human reasoning, are we more likely to get an appropriate decision next time? YES

So to answer the original question, if we permit analysts to use less than appropriate tools for the failure at hand, than we are part of the problem. If Figure 1, we show the spectrum of analysis where if we just stop at replacing parts, that is shallow cause analysis. If we look at RCA as a comprehensive and critical system we will not only seek the true latent causes, but we will seek to collect, aggregate and leverage that learning in the form of a corporate RCA knowledge base! In the long run, such raw logic can be used in internal Artificial Intelligence (AI) and IIoT (Industrial Internet of Things) efforts.

I thank SMRP and Empowering Pumps for the opportunity to present to their participants and more importantly, I thank the participants for their time and interest.

I will follow up this series with Question #3 soon.

FYI. For access to this webinar, it is apparently free to SMRP members and there is a $35 fee for non-SMRP members: https://portal.smrp.org/eweb/shopping/shopping.aspx?site=smrp&webcode=shopping&shopsearch=germ&prd_key=bf7268ce-edcd-4e7a-b1a2-daf53a5f8069

Filed Under: Articles, on Systems Thinking, The RCA

About Robert (Bob) J. Latino

Robert Latino is currently a Principal at Prelical Solutions, LLC, along with his brother Ken Latino. Bob was a Founder and CEO of Reliability Center, Inc. (RCI), until it was acquired in 2019. RCI is a 50-year-old Reliability Consulting firm specializing in improving Equipment, Process and Human Reliability. Mr. Latino received his Bachelor’s degree in Business Administration and Management from Virginia Commonwealth University. For any questions, please contact Bob at blatino@prelical.com

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Comments

  1. Greg Hutchins says

    February 10, 2022 at 9:02 AM

    Very nice piece. Thanks for sharing RCA.

    Reply
    • Bob Latino says

      February 10, 2022 at 9:13 AM

      Thx Greg, let me know if you have any or would ever like to discuss these concepts.

      Have a great weekend!

      Reply
  2. JD Solomon says

    February 11, 2022 at 9:35 AM

    Bob,

    I missed your webinar but will access it via SMRP. Good post.

    Reply

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