How we drive our conclusions and decisions


This morning I have received an email from one of the establishments I have been attending in the past.
The message reads:
---
Dear valued client:
Please note that unfortunately our internet is down
and we are doing everything we can to
get it up and running.
In the mean time, we have signed on with
a new provider which will prove to be
far more reliable.
---
My pet peeve is not about a small business losing the Internet connection and switching providers - it is too trivial occurrence to get excited about.
What caught my attention was the last paragraph:
"... signed on with a new provider which will prove to be far more reliable..."
That reminded me of how we make the decisions and reach conclusions:
  • we buy into an unverified premise as long as it promises a quick solution to a problem
  • we don't fact check whether the new provider, in this case, has a proven higher reliability record
  • we tend to accept the opinion of an "expert" such as a salesperson, a biased technician, a person wearing a white coat, a workplace superior or any other authoritative figure in our life
What do we get on the outcome of such a method?
Often, a disappointment. And yet, we will pursue the same decision process in the future.
Given, no one has the resources to verify every claim made around us: "the best pizza in town", "the only 5 stars safety rating pickup truck", and so on.
The bothersome part, to me, is that enterprise and start-up decisions are often made using the same principals:
  • biased comparative analysis: the VP of infrastructure has concluded that public cloud storage is too expensive than in-house NAS system she has been deploying for the past 3 years
  • baseless claims: as a senior security architect I am telling you that public cloud networking is not as secure
  • cognitive bias: I have designed and built, single-handed, a new in-house framework that is, by far, superior to open-source frameworks with lots of contributors and commercially available alternatives
Where is the silver lining?
How about a simple approach:
  • ask for verifiable evidence and industry references to counter opinions and beliefs
  • run a third party comparative analysis to counter cognitive bias
  • establish the requirements and acceptance criteria before going into the evaluation and falling-in-love with a product or a technology