Catalyzing innovation stamina, design thinking, and mindfulness
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Saturday, March 31, 2018
Tuesday, March 20, 2018
A journey from resistance to acceptance of “what is” in the short film “Afterglow”
Many times we are resisting the current situation. Perhaps something has changed; we have lost something we are fond of. Or thought has imagined a scenario where we are likely to lose something and we don’t like this imagined scenario. Or someone said something to us which has hurt us etc. This resistance to “what is” manifests itself in different forms – sadness, anxiety, fear, blame, guilt etc. This continues for a while until the resistance drops off. Perhaps the changed or imagined situation is no longer that threatening. This is also referred to as acceptance.
The award-winning short film “Afterglow” directed by Kaushal Oza beautifully depicts this journey from resistance to acceptance. The story involves a widow coping with the death of her loving husband. It uses two symbols through which this transition from resistance to acceptance unfolds – paaghri (groom’s headgear) and the lamp which is welcoming the departed soul.
Sometimes a question gets raised, “Does acceptance mean inaction?” That’s not how I understand it. Acceptance involves dropping off of inner resistance. In Afterglow, there was an inner resistance to letting go of the paaghri. And then at one point, it drops off and that results in an act of giving the paaghri away to someone who would find it useful.
Sunday, March 11, 2018
Rango's "Who am I?" journey from "I could be anyone" to "I'm nobody"
I have been fascinated by the concept of self-deception. I feel understanding self-deception is at the heart of mindfulness. Hence, I keep looking for metaphors depicting self-deception. This is one of my favorites.
Rango is a lonely lizard. However, he likes to imagine himself surrounded by friends and he always plays the hero. As luck would have it, Rango accidentally kills a hawk and actually becomes a hero. The town makes him sheriff and Rango begins to enjoy playing the real hero.
Luck favors him for some time and Rango begins to believe that he is successful due to his effort and talent - a classic case of self-deception. Until one day his coward self is exposed by Rattlesnake Jake and Rango is asked to leave the town. This is a turning point for Rango and it triggers a process of awakening for him.
I don't know about you but I have been in situations where people around you start calling you successful. And it is so tempting to attribute the so-called success to oneself. Hence, to carry an awareness and, like Rango, see that "I am nobody" is difficult. However, that awareness is an essential part of being mindful.
Wednesday, March 7, 2018
Does “fail fast” contradict with “first time right”?
“Fail fast” is one of the principles I champion in my workshops on innovation and design thinking. “First time right” has been popularized by the quality movement, especially by the Six Sigma methodology. Hence, it is not uncommon to get the question: Does “fail fast” contradict with “first time right”?
To explore this question, it would help to understand “fail fast” and “first time right” better. Let’s start with “fail fast”. Does “fail fast” imply failing in any kind of way? No. To understand this better, let’s see the difference between a failure due to checklist-oversight and a negative result during hypothesis testing. Let’s borrow an example from Jeff Bezos of Amazon. In an interview, he said that if Amazon goofs up the opening of 19th fulfillment center where an operational history exists, then that would be poor execution. Let’s call this checklist oversight failure. It means a prior learning has been consolidated into a checklist and the failure occurred because the checklist was not followed rigorously. “First time right” uses all the available past data in constructing the process to be followed for delivery of a solution.
In contrast, let’s look at the following hypothetical assumption: Amazon will be able to deliver a book size packet reliably on the terrace of a ten storied building in Bangalore via drone delivery. Let’s assume Amazon has experience of this kind of delivery in countries like the US but not in India. And if the first attempt at doing this delivery fails, then it would be a failure of the second kind – hypothesis test failure. Note that this failure would result in some learning which can be incorporated in the second attempt and so on. Depending upon the difficulty encountered, the cost of each experiment and the importance of this use-case for Amazon, more attempts would be made to learn more about this use-case.
When I say “fail fast” I mean fast testing of the assumptions associated with an idea. Now, we can see that “fail fast” is quite complementary with “first time right”. If Amazon were to launch the drone delivery on the terrace and get it right the first time, then it would help to do as many tests in different contexts – weather conditions, building locations, different building structures etc. Thus it would help to fail fast to get it right the first time you go live.
“Fail fast” assumes that there are certain unknowns / risks associated with achieving the goal. If all the steps in achieving the goal are well understood, then “fail fast” would not be required.
In short, “fail fast” helps you deliver “first time right”. The riskier your project, i.e. the higher the cost of getting it wrong the first time, the more important it becomes to “fail fast” in order to get it “first time right”.
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