FRIDAY JOKE: Return On Investment – Don’t Be Fooled!
I’m always looking for ways to calculate the return on the investment in a good root cause analysis. That’s why I thought one web site was extremely interesting (and also qualifies as the Friday Joke).
The web site claimed an “average” investigation saved between $11,000 and $75,000.
The web site claimed to produce an average return on investment of 4,900% when using a particular root cause analysis tool.
Wow! I had to know more…
I dug through the depths of the web site.
In a distant page, I found the method they used to calculate “return-on-investment.”
First, they put a price on the cost of the incident. For this example, let’s say the incident cost $50,000 in damage and $50,000 in lost production. A total cost of $100,000.
Next they found the cost of the time used to do the investigation and the cost of the corrective actions. For this example, let’s say that 5 people spent 10 hours and the value of their time was $100 per hour each. Thus their time cost $5,000. And let’s say that the corrective action they invented cost $5,000 to implement. Thus, the total investigation/corrective action “investment” is $10,000.
Now how did they calculate the ROI? Simple. They divided the cost of the accident by the cost of the investigation.
For this example, the equation is: $100,000 ÷ $10,000 = 1000%.
A 1000% ROI seems pretty good to me, but it’s almost a factor of 5 less than the “average.”
Let’s look at these numbers more closely.
What is the “return” they are taking credit for?
The return in their equation is the cost of the incident.
How can a “cost” be a return?
That’s a question that I can’t answer.
They only way this would make sense is if you assumed that without your corrective action, the same incident would happen again and in a fairly short period of time.
The equation makes the “assumption” that the future saving will occur because you did an investigation and the saving will be the same as the cost of the accident you investigated.
Here’s the double-talk that really appears on the web site I was reading:
“Problems force us to spend money, and as such are like forced investments. But we get to decide whether or not we earn a return. As long as people remain imperfect, we are going to encounter problems with the systems we create – there is no way around it.”
“So we are left with a choice. We can choose to systematically identify and eliminate causes of problems with the ****** method. Or we can continue doing what we’ve always done and hope the problem doesn’t happen again.”
Ah, yes … The old “false choice” argument. (There are more than two choices available – but only let the reader choose between your product and failure. Thus, unless the reader is really stupid and wants to fail, there is no choice but to buy the product!)
Even with this “logic” there is still a big problem with their calculations.
The bigger the incident cost (in $$$$) and the less you spend to investigate and fix it, the bigger the ROI.
So if we could make a mistake that cost $1,000,000 and we only spent $10 investigating and fixing it, we could get a 10,000,000% ROI!
Nowhere in their calculations are the effectiveness of the corrective actions questioned. The effectiveness is just assumed. They don’t mention how one would verify effectiveness or how long one would have to wait before taking credit for the magical, unproven savings.
By this theory, to maximize your ROI, all you would need to do is have major, costly problems frequently and spend very little investigating and fixing them. This would even guarantee more problems – and more “saving” – in the future!
With this logic you can save your company right into bankruptcy!
By now you have probably decided … this makes NO SENSE!
What should you do if you are presented with this crafty, deceiving argument? Here is my suggestion:
If somebody touts a system that seems to produce magical results with easy, simple investigations, don’t be fooled.
Start asking questions.
Ask to see the math.
Find out the scientific basis of their claims.
Dig into how a “simple” answer will be doing anything different than what you have already tried in the past – your already existing knowledge.
How does the simple process lead investigators beyond their current knowledge?
What expert systems are built into their process?
What help does their system provide developing corrective actions?
How does their system lead investigators to human performance and equipment reliability best practices that aren’t being used at your plant?
Then say, “Thanks, but No Thanks.”
You will have just avoided a mistake that could cost you your job when people don’t fix problems because the system being sold is based on faulty logic.
Remember, if they can’t even calculate a simple ROI correctly, how will they ever create an advanced root cause analysis system to help you solve your problems.
And that’s why this ROI calculation qualifies as a FRIDAY JOKE!