Something I’ve started to hear more and more lately is “just use common sense in your decision making”. Well, the problem is, you’d be surprised at how much gap there is between different people’s definition of common sense.

So here’s an example. I spilled some juice on the counter the other day and I went to clean it up. I was suddenly paralyzed with indecision on whether I should use a paper towel or a rag. There are pros and cons of each, but the reality is I don’t know the actual scope and scale of these pros and cons.

Paper towel: Does using them waste trees, and thus harm the environment? Am I creating more garbage for landfills by using non-renewable materials? And how much does a single paper towel cost, anyways?

Rag: How much does a rag cost, and compared to a paper towel how long can I use that rag to clean up an equivalent number of juice spills? But the rag is also made from materials, probably a lot more than the paper towels, so I’m using more resources to purchase a rag. Also the rag has to be washed, which uses up water and soap and also creates a sewage problem.

“Just use common sense!” Well, as you can see, it ain’t that simple. No matter which way you want to go, someone can stand there and create an entire strawman argument on why you should do Option X. But……without hard data to dive into each of those items I mentioned, its all useless. Asserting “washing a rag wastes more resources than making a paper towel” doesn’t make it true without the data to back it up.

Now think about all the other strategic decisions that come across a leader’s desk, and how they can be over-analyzed to death:

• Electric cars vs gas cars
• Part time vs full time employees
• Solar power vs coal/oil vs nuclear
• Work-from-home vs return-to-office

If you read my blogs you’ll see I’m not a proponent of over-reliance on KPIs and metrics. But alternatively I do not believe you should just take strawman arguments at face value. You have to figure out what you are optimizing for (impact on the environment vs cost-per-spill-cleanup), and then find the right data to make the right decision. And recognize that you’ll rarely be able to optimize for all the goals, so you will need to prioritize.