Assumptions and data: never get tired to question them

Let me play a little game with you, just to introduce the subject of this post.

Solve this very easy riddle. 

“Hi, 

I am a very big mammal. 

I am an herbivorous.

I have a grey thick skin.

You can find me in Africa but I have cousins in Asia.

I have been (and I am still) hunted by humans because of something that grows near my mouth.

Who am I?

If you want to meet me follow the link.”

Are you surprised?

Did you expect to meet this other African friend?

Well...you are not totally wrong...or more precisely...you are right...too.

From the data at your disposal both the answers were right. Both these animals are big herbivorous mammals with a grey thick skin. Both of them are present in Asia and have been hunted almost to extinction because of something that grows on their muzzle...and yes...nose and mouth are quite near.

Almost everyone indicates the elephant as a solution for this riddle, probably because elephants are more ubiquitous than rhinos on television, cartoons, books, tales...

What your brain does

The fact is that you have been provided with true but incomplete data and your brain automatically tried to fill the gaps in the best way it could. It tried to interpolate data where informations were lacking.

This capability is something wonderful and amazing at the same time. Your brain, starting from some provided data and past stored knowledge, suggests you answers when you have to take decisions. This same capability is what comes at your help when you have to make an educated guess about some event in the future.

I value this as one of the most important characteristics of human beings.

Take it easy

Please, do not have fear, in this specific case is not your brain that have deceived you...but the other way round...you probably have not provided him with enough time to give a well crafted answer to the riddle I proposed you.

Probably if you had waited a little, if you had just taken your time before trying to give the answer it would have come to your mind that the riddle would have been satisfied by at least two answers. The problem was that everything seemed so perfect, the data seemed so accurate, so precise that you jumped directly to your conclusion. 

This happens in day to day life and in project management too, whenever we have to deal with data and/or assumptions to take decisions.

Sometimes we trust too much the data we have been provided with or the assumptions we have accepted as true, especially when data seem so well crafted and our first answers seem to fit so magically...in this cases sometime we are driven to rush headlong to conclusions.

What we have to deal with

In Figure1 we can see a pictographic representation of a two dimensional data  space, where data and assumptions are placed using their degree of completeness and reliability. Above the yellow line we have data and assumptions more reliable than complete. This is the same situation we have faced with the riddle.

Below the yellow line we can find data and assumptions more complete than reliable.
Both situations are critical.

Figure1.

In the first situation efforts have to be made to collect more data and to refrain from giving the answer too quickly. Take your time. If it is too good to be true...probably it is not true. So try to collect fresh informations and evaluate alternatives to your decision.

In the second one efforts have to be made to verify and validate data and assumptions, discarding corrupted ones. The problem is...how do we know that our data are not reliable or our assumptions are fault? 

Well...the only answer I can offer is to never get tired to analyze, check, question and validate.

Always perform data and assumptions sanity checks, base your analysis on literature, consult with the team, consult with the stakeholders, consult with other project managers and with your project management office... Check lessons learned related to other similar projects if you can access them.

...So

Maintain these behaviors for all the project life. Never get tired to evaluate alternatives and to question and check your data and/or assumptions...or you run the risk to mistake an elephant with a rhino...or even worse...an assumption with a million dollars gamble. 

Thank you for reading.

Bye.

Quest' opera è distribuita con licenza Creative Commons Attribuzione - Non commerciale - Non opere derivate 3.0 Unported.