“May-be” – PM’s Favorite phrase!
Could you think of a case where the tentativeness, indecisiveness could ever act as an advantage? It is fascinating how that can prove and add-up to being a TAUTOLOGY (always true).
A path -> a course -> a direction!
Have you ever tried teaching a child / toddler to identify with an object by “name”?
Mull over it for a second. What would you do?
You’d hold up the object so that it is clearly visible and say its name out loud a few times in an expectation that the child would reciprocate and recite until and unless you’re sure to an extent that it has been conveyed clearly.
The next time if you pop the same question with the same object after a long gap, the answer may come with a bout of hesitation. Keep asking that question again at regular intervals with a bit of an appreciation for a right answer and some correction for a wrong one and you may have taught something worthwhile and rest assured that the child may have learnt something valuable ultimately leading to a bit of confidence thus adding up to the success of the whole exercise.
For all those of you who are into AI / ML this may sound pretty familiar as this is the skeletal concept underpinning the core of reinforcement learning.
But, when the child has no memory of its own and is in the process of building it all starting out from ZERO, there could be a lot of tentativeness, indecisiveness in its approach until it reaches a certain degree of familiarity, and of course the decision-making logic comes much later.
But, the course / the path taken does indeed set it out in the right direction to reach that goal over a period of time.
What seems a very simple logic over making decisions isn’t really that simple after all when you are referring to some real-world situations or even generally speaking in the parlance of the human brain.
Course of Action
In a broader sense of the word “being sure” / “decisive” could only mean “yes” / “no” and that is more often than not expected to lead someone to be able to choose one clear path over the wide array of choices available. But, in actuality it is a whole lot more than just those binary options - “yes” / “no”.
The final choice could be the end of the tunnel so to speak, but what takes superlative precedence is how one arrives at the final choice and what options matter as opposed to the ones that have been considered, pondered, debated over iteratively before prioritizing / picking one of them.
For ex: think of a mundane question (which am sure you’d have asked yourself too at some point in your day-to-day life) like:
- “is it going to rain today?”
When someone with no prior knowledge about a certain place - say tourists quote:
“no, I don’t think it’s going to rain”
as opposed to a local resident who says:
“yes, it will rain heavily in all certainty today”
they may only be half correct as they may both be guessing it all, at best.
Because just as much as a tourist doesn’t have any detailed information about a place he has visited and its idiosyncrasies, there is also no way a permanent resident could be sure of it raining heavily on a certain day at a certain hour. The only thing one could do is predict it to some level of accuracy.
And that prediction may have its roots in the behavioral patterns as much as it could be based on some hardcore facts, figures that they have at their disposal.
Delving a little deeper, one could go into varied depths stripping down each of those parameters to its elements covering them in granular detail. So, going by the complexity it could all be mathematically represented as a fuzzy set.
REVISITING the question now:
- “Is it going to rain?”
these options may fit in as logical reasoning representing the course of action behind the final inferences.
well, may be!
because it was overcast yesterday as well and I really don’t know how it poured cats and dogs just like it has been behaving so puzzlingly over a week or so now, so going by that I am saying it could rain
It all boils down to the grading patterned mathematical outcome of fuzzy logic.
People who understand the fuzzy sets and its application to such practical situations would change the question itself to:
- “Is it likely to rain today?”
The answer could now be graded to:
highly likely
likely
moderately likely
neither likely nor unlikely
moderately unlikely
unlikely
highly unlikely
So, based on the outcome of that prediction right there, one can now take a precise action as to whether there is a need to wear layered or minimal clothing or take evasive action against the rain.
Splitting down the possibilities and exploring those outcomes over planning the exact steps in being prepared to some extent if not totally, does make a lot of sense for anyone who is a product person irrespective of the level or hierarchy one is operating in.
“Maybe” – A PM’s favorite!
The word phrase “May-be” is touted to be a favorite phrase amongst PMs, leaders and product people in general and there have been many memes and jokes about this aspect too.
But, it is actually no surprise that the statement is only partially true.
Just saying “maybe” again might not serve any great purpose as that isn’t quite an answer and quite rightly it shouldn’t stop there either. If anything, it has to be the opening that leads to a large unexplored pathways filled with possibilities to ponder over, analyze, weigh out options in order to eliminate the ones that don’t closely match or align with the required outcomes and to discern the ones that may be ideal ones to tread on.
And, common knowledge / experience of the world is worth its weight in gold and has no chief substitute. The more knowledge one has about all variables, parameters that could affect the result / outcome of a certain event, the more one would want to be very careful and warned about taking sides based on a whim or assumptions that aren’t quite validated and can’t really be data-backed.
For instance, Fish-bone analysis aka Ishikawa / Fishikawa.
It is all to a cause and the concerning effects. You’ve got a problem representation on the far right and the categories and causes on either side of the center. By doing these boards up one explores multiple possibilities / solution routes getting into the nitty gritty of identifying, analyzing parameters that could affect / impact / lead to solving a problem.
But talking of the product management, development & the product life cycle’s parlance, there is obviously a right place and a time to ask these questions and put those thoughts forward. Else, the same exercise could turn out to be futile, wasting a lot of time, effort & resources.
FACT: I believe we all stand testimony to the fact that when we are listing out those points filling up various sections of the Fishbone as shown above, one would not only have something concrete to work with in the definition and correlation to the central problem, it could also help identify a few crucial pointers that one may have missed out. It is also a great tool for brainstorming sessions with teams and has been used industry wide.
NOTE: The cost of operations for mending and correcting any mistakes would increase as the product moves over to the next stage as it may mean a lot of revamping & rework.
FACT: The reason why processes like LEAN for instance evangelize rapid prototyping to build what may be called smaller working versions that offer the main functionality of the end product and subject it cycles of testing with the audience (users) of the real world in an aim to gain constant feedback and also not have any emotional preferences and to fail and fail fast if it has to intern leading to improving the overall product offering.
To Conclude:
“May-be” is not the answer to any question and can never ever be. But, if anything it could be a trigger to invoking thoughts branching them out into various depths leading one to explore the pros and cons in an aim to clear out the clutter and find one path over numerous other possibilities that may appear great on the first look.
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