Monday, February 15, 2021

My 4 takeways from Dr. Pavan Soni’s “Design your thinking”

Dr. Pavan Soni is a friend and I have seen his journey from innovation evangelist at Wipro to IIMB Ph.D. program to an accomplished consulting career. I am happy to see Pavan adding yet another feather to his colorful cap with the book “Design your thinking: The mindsets, toolsets and skillsets for creative problem solving”.  The book is packed with inspirational stories – several of them from India and suffused with the optimism that Pavan embodies. The book also helped me question some of my deeply held assumptions. And sometimes the questions are more valuable than the examples. Here are my 4 takeaways.

First two are stories in the book that stood out for me.

Power of metaphors: In the “Inspire” chapter Pavan invokes Aristotle’s quote “To be a master of metaphor is a sign of genius” and cites several examples to illustrate it. One of them is Mahindra XUV500. A market survey of a couple of thousand customers across the world got translated into a design brief – to build a car that offers aggressive styling, muscular looks and a macho stance. And then the team adopted the metaphor of cheetah indicating speed, agility, aggression, and muscle. The design team visited Masai Mara, Kenya to watch the beast in the wild terrain. So much to internalize the metaphor!  The design cycle also involved testing 250 prototypes across half a dozen terrains in the world.

Perils of “just do it”: Pavan is also careful to bring out stories from innovative organizations that highlight leadership admitting to mistakes. For example, he illustrates the principle that “just do it” without an appropriate pilot or prototype can hurt badly with two big decisions from Flipkart that backfired. In the first case, Flipkart went for a Big Billion Day sale in October 2014 without doing any prototyping. The site couldn’t withstand the heavy traffic and became dysfunctional for some time. In the second case, leadership decided to take Flipkart towards app-only mode by forgoing desktop customers without any pilot. They had to revert the decision after backlash from employees and customers.

Now we turn to questions that got raised in my mind that rubbed some of my long-held beliefs. It means I need to explore them further. 

Can empathy be engineered? Pavan suggests in the chapter “Empathy and define” that empathy can be engineered. This section builds on the work of several reputed thinkers like Daniel Goleman (self-awareness), Thich Nhat Hanh, and Dalai Lama (mindfulness). And then suggests that with the tools like mind mapping, stakeholder map, and customer journey mapping, empathy can be engineered. If listening with openness and deferring judgment are important for empathy then it is not clear how using tools will cultivate empathy. “Engineering” carries a sense of control and precision in the design process and I don’t know how empathy can be controlled. But maybe I am seeing engineering and empathy in a narrow sense.

Can biases be overcome? Citing research from Francesca Gino, Pavan mentions that confirmation bias can be overcome through curiosity. The solution is hiring and cultivating curiosity. My limited understanding of biases is that they are deep-rooted and extremely hard to overcome. Daniel Kahneman who has researched biases for fifty years keeps saying in the interviews that it is difficult to overcome biases at an individual level. After writing the bestseller “Thinking, fast and slow” Kahneman feels he hasn’t changed much and he is still overconfident. It is possible that the study of Kahneman’s work has biased me. So I need to study this further.

The book contains a comprehensive collection of toolsets associated with creative problem-solving. Personally, it has helped me learn new examples and raise/revive basic questions related to design thinking. I wish Pavan and the book a great success.


Book image:

Daniel Kahneman’s quote “I don’t think my intuitions have significantly improved and I am very overconfident,” see his interview with Sam Harris, March 2019 (18:57-20:25)

Friday, January 29, 2021

Innovation maturity, level 4 challenge and sandbox hesitancy hypothesis

My co-author Prof Rishikesha Krishnan and I have been presenting the innovation maturity mirror (see the picture above) to executives for close to 8 years. We feel many organizations that begin their innovation journey reach level 3 and then struggle during the next leg – to reach level 4. In this article, I would like to first spell out what the level 4 challenge looks like through the innovation maturity mirror. And then propose a hypothesis that hesitation to build a sandbox in a strategic opportunity area could be at the heart of the challenge.

What’s the main difference between level 3 and level 4? Level 3 indicates that the organization is engaged in experiments and reviews. 1 in 10 ideas get prototyped, incubation pipeline gets reviewed quarterly and 1 in 3 employees participate in innovation activities. That is, if you walk around the corridors or shop floor, innovation is palpable. Level 4 indicates that, in addition to the above things, the organization now has a balanced portfolio of small, medium, and large impact ideas. On average, the organization generates 1 idea per employee per year, and projected impact of the big idea pipeline is greater than 10% of the revenue and there is at least one operational innovation sandbox.

The run rate of 1 idea per employee per person is not easy to sustain. However, with the momentum of the experimentation and challenge campaigns, it is achievable. It is also not difficult to generate big impact ideas. Ask this question in a leadership meeting and you could get a few ideas. Your favorite search engine could also help you get a few. Things get tricky when the rubber meets the road for the big ideas – a champion, typically a CXO, taking a strategic bet, allocating resources, building experimentation infrastructure, put a dedicated team around a focus area. Sandbox hesitancy hypothesis says that organizations either hesitate to set up a sandbox or don’t give enough attention to it.

Organizations tend to be secretive about their sandbox setup and that is understandable. Amazon was secretive about the Kindle effort and Apple was secretive about iPhone. But many times organizations end up acquiring new resources – people/technology to build the sandbox. For example, in 2007 Google acqui-hired a team for starting its self-driving car sandbox which eventually became Waymo. The VueTool team was working on a digital mapping project and some of its members had won 2005 DARPA Grand Challenge related to robotic self-driving cars. Mahindra acquired Reva to strengthen the electric automobiles sandbox and Flipkart acquired an AR/VR company Scapic last November. In all these cases, in all likelihood, there was a champion at the top level (Bezos for Kindle, Sergey Brin for self-driving car, etc.)  

Is innovation sandbox applicable only for large companies? I don’t think so. I feel that even an SME would need to build a sandbox with all its characteristics – a champion, focussed challenge area, experimentation infrastructure, dedicated team, and failure protection.

If the sandbox hesitancy hypothesis has any merit, then a number of questions can be asked. Why do organizations hesitate to build an innovation sandbox? Is it a lack of ideas? Or lack of confidence? Or lack of clarity on the strategic bet? Or lack of resources? Or lack of urgency? Or lack of sandbox management experience?

I and Rishi hope to explore these questions in the coming months. If you feel you have some useful input, please let us know.

Wednesday, December 30, 2020

No man can walk out on his own story

I watched this scene from one of my favorite animation films “Rango” perhaps for the 15th time (see the video clip below). The scene ends with Rango getting a piece of advice from the Spirit of the West – No man can walk out on his own story. What does it mean? Here is an attempt.

Rango, the protagonist, is a lonely lizard. He knows how to cook stories about his past adventures to impress people around him. Rango accidentally kills a hawk, becomes a hero, and eventually the sheriff. But deep down he knows that he was really scared during those heroic stunts and luck played a huge role in his survival. But the act of self-deception keeps the game going. Until one day, Rattlesnake Jake exposes Rango’s phony nature in front of everybody in the village. And Rango is asked to leave.

“I am nobody”, Rango admits to himself for the first time in his life. And finally arrives at a place where he meets the Spirit of the West. Here is the dialogue between the two in the scene:

Rango: I am a fraud, I am a phony. My friends believed in me. But they need some kind of a hero.

Spirit: Then be a hero.

Rango: Oh, no, no. You don’t understand. I am not even supposed to be here.

Spirit: That’s right. You came a long way to find something that isn’t out here. Don’t you see? It’s not about you, it’s about them.

Rango: But I can’t go back.

Spirit: Don’t know that you got a choice, son. No man can walk out on his own story.

Walking out on one’s own story is so tempting. Walking out of relationship, out of a job, leaving everything and going to Himalayas. Isn’t that a good recipe for a bestseller? But, what about the story? I am a hero, a phony, a consultant, an author, a mindfulness guru? How do you walk out of your story?

I like what Nisargadatta Maharaj told a visitor – “The dream is not your problem. Your problem is that you like one part of the dream and not another. Love all, or none of it, and stop complaining. When you have seen the dream as a dream, you have done all that needs to be done.”

An attempt to walk out of the story just changes the characters and scenery. So long as the story is seen as real, so long as the story is taken seriously, not much changes. There is no need to go anywhere, just investigate whether the story is real.

Image source:

Nisargadatta Maharaj quote is from “I am that” chapter 29 titled “Living is life’s only purpose”, page 117 of third printing.

Tuesday, December 29, 2020

Perception as prediction error minimization

Perception is not just a kind of prediction but “prediction error minimization is all the brain ever does” says Jakob Hohwy in the book “The predictive mind”. The predictive processing paradigm inverts the traditional sandwich perspective of perception-cognition-action by bringing prediction to the center stage. And Hohwy’s book gives an excellent introduction to various dimensions of the predictive processing paradigm. In this article, we first look at perception as Bayesian inference. And then explore the question – what is prediction error minimization? We will use Hohwy’s favorite example – binocular rivalry to illustrate the concept.

Perception as Bayesian inference: How do we perceive the world? According to this framework, we keep a model of the world that predicts the generation of observable data. Based on this model, we have prior hypotheses about the causes of our sensory input. As we receive new sensory input, the brain computes the posterior using the Bayes rule – posterior is proportional to likelihood times prior. The winner, the hypothesis with the maximum posterior, is declared as the cause of the sensory input. Thus perceptual inference involves updating the internal model of the world consisting of a set of prior beliefs based on incoming sensory information. See 3Blue1Brown and Veritasium videos for more details on Bayes theorem. Now, let’s see what happens when we try to trick the brain.

Perceptual inference in binocular rivalry: Binocular rivalry is a phenomenon that has been documented for over four hundred years. If you show two different images to the left and the right eye – say a face and a house – then you don’t see a mixture of the two images say a face-house. Instead, you either see a face or a house. Moreover, what you see keeps alternating even when the images are held constant. The following picture from the book gives a possible explanation of this phenomenon using perception as predictive error minimization.

The likelihood of face+house (F+H) sending such sensory input is higher than just face or just house hypothesis. However, the prior probability of F+H i.e. we ever seeing such a thing as a mixture of a face and a house is very low. Hence, when you multiply the two – i.e. prior and likelihood – the face-only or house-only hypothesis wins over the face-house hypothesis. And that’s what you see.

Now, how do you explain the alternating images in the binocular rivalry? As you see one of the two images, say the face, the prediction error resulting from the sensory input from the house is explained-away. Over time, the prediction error builds up and the brain is not able to explain it away. And the brain chooses the competing hypothesis which is the house-only image. This is a hand-wavy explanation. It is heavy-duty mathematics at play. If you are curious, check out Hohwy’s paper “Predictive coding explains binocular rivalry”.

What if you are able to bias the prior in favor of one of the images? Hohwy talks about a variant of the binocular rivalry experiment in his book where one eye is shown text markers and the other eye is shown roses. Then olfactory evidence was added and participants smell roses. As predicted by the Bayesian rule, the participants consequently spent more time perceiving the role image. 

Isn't perception just one of the processes at play in the brain? What about action, attention, learning? And what about various biases? Well, the book shows that the predictive error minimization framework is quite ambitious in its goal and does a good job of attempting to explain various phenomena using the framework. 

To understand the free-energy principle, the core principle behind prediction error minimization, in its full depth, one would need to go into statistical mechanics, self-organization, dynamical systems theory, information theory. However, the book lays a good ground for the curious. And the theory is in its infancy and an active area of research right now.    

Image source

book image is from, the binocular rivalry image is from Hohwy’s paper Predictive coding explains binocular rivalry” and it is very similar to the image in the book.


Thursday, December 24, 2020

Doing the last experiment first: illustrated through Alex Honnold’s El Capitan free-solo

Last month, Reserve Bank of India issued an order to HDBC Bank stopping all launches of the digital business generating activities planned under its program Digital 2.0 and sourcing of new credit card customers. Reason? HDBC Bank suffered major outages in Internet banking and payment system due to a power failure in the primary data centre. These are temporary restrictions but such incidents could damage company’s brand. Question is: are such data outages avoidable? And could “doing the last experiment first” be helpful in such situations? Let’s explore these questions in this article.

“Doing the last experiment first” is one of my favourite levers of building margin of safety. We have mentioned the concept in our book “8 steps to innovation” and we borrowed the term from A. G. Lafley, ex-CEO of P&G. Doing the last experiment first involves validating the leap-of-faith assumption associated with an idea. What is a leap-of-faith assumption? An assumption that is (a) critical to the success of the idea, and (b) there is very little evidence available to support it. How does Alex Honnold’s El Capitan free-solo illustrate this concept? Let’s look at it next.

Alex Honnold is an American rock-climber. In 2017, he became the first rock climber in the world to free solo 3000-foot wall of El Capitan in California. If you want to get a feel of what that means, check out this 5-minutes video showing Alex’s free-solo climbing scenes. To us Alex’s endeavour appears almost like a suicide attempt. And Alex says the same thing in his TED talk, “Seems scary? Yeah, it is” (1:13). However, he says something strange immediately after, “But on the day that video was taken (i.e. his free-solo), it didn’t feel scary at all. It felt as comfortable and natural as a walk in the park.” Walk in the park? Was Alex serious or joking?

Alex explains in the TED talk his years of systematic effort in preparing for such a climb. But the part that is of interest to us is related to what Alex calls the most difficult part of the climb – the Boulder problem (8:06).  “It was about 2000-feet off the ground and consisted of the hardest physical moves of the whole route. (It involved) long pulls between poor handholds and with very small, slippery feet.” This manoeuvre culminated in a karate kick with left foot over to the inside of an adjacent corner. This required “high degree of precision and flexibility”. Alex had been doing a nightly stretching routine for this move for over a year (8:35).

Ability to navigate the boulder problem including the karate kick comfortably is an example of the leap-of-faith assumption in Alex’s climb. If he didn’t want to be a lucky climber, then he had to master the solution of the boulder problem. In this video, “What if he falls? The terrifying reality behind filming free-solo”, we see Alex practicing on the Boulder problem (6:00). And we see him practicing with a rope and actually falling in the process (6:07). What that means is that Alex would have experimented with his ideas to navigate the Boulder problem with rope first. And he would have failed in many of these attempts and learned valuable lessons on what may work. This is an example of doing the last experiment first.

Can Boulder problem be re-created in an indoor environment? Yes. You can see how an indoor wall climbing center VauxWall recreated the Boulder problem in this video. And see how Alex’s climb feels like a graceful dance on the wall here (10:50). I don’t know if Alex actually practiced in an indoor setup like this. But the point is it is possible to re-create a difficult situation in a controlled environment so that one can practice more easily, more often and at lower cost.

What would “doing the last experiment first” mean in the context of data centre outages in HDFC Bank? We can get a clue from what Dr. Werner Vogels, Amazon CTO says they do at Amazon. They started what was later called “Game days” where they pulled the plug from a data centre and see how their site held on. And like the indoor gym recreating the Boulder problem perhaps such experiments can be performed in a more controlled environment as well. At least it is worth considering it because the consequences of failure could be grim.

image source:

Tuesday, December 15, 2020

My 4 takeaways from “Getting people to talk: An ethnography and interviewing primer”

Getting people to talk: An ethnography and interviewing primer” is a 30-min-long video created by two students, Gabriel Biller and Kristy Scovel, of IIT Institute of Design, Chicago, USA. For a student of design thinking, it gives a good perspective on what empathic interviewing means. Here are my key takeaways from the video. The timestamps give a reference in the video.

1.      Different types of interviews: The primer differentiates between different types of interviews – ethnographic interview, hypothesis-driven interview, extreme user interview, and expert interview. The key attribute of an ethnographic interview is – (5:51) – “Whatever knowledge I am going to gain from people, I am going to try to understand and represent it from other people’s perspective.” Sometimes you carry a framework or a hypothesis with you while interviewing. In which case, “The way I represent that (knowledge) is not from their perspective.” (6:50). I would call this hypothesis-driven interview and it would be relevant in validating your ideas.

In an ethnographic interview, the focus is not so much on what people are saying but who they are (8:45), their attitudes, behaviors, environments, artifacts that exist around (9:16).

An extreme user interview is a lot more about observing the extreme users doing stuff (10:25). You try to become an invisible observer, like a fly on the wall. An expert interview, on the other hand, is more verbal, sometimes happens even through emails. Here what the expert knows is more important than who they are (12:10).

2.      How do we actually do it? “It is not about asking the questions on your list, it is about the rapport that you establish.” (18:25) For example, check if they are comfortable with audio/video recording (13:50). The recording could be intimidating (15:00). Choose an appropriate location – ask them which location is comfortable (15:22). It helps if one is talking about jeans surrounded by jeans (16:00). In an environment with lots of artifacts related to the person being interviewed, you can ask questions related to the artifacts – “Tell me about your grandkid” (16:25). In such an environment, they are showing you stuff 80% of the time (16:35).

It is important that you are genuinely interested in what they are saying (18:31). It is about listening to 12 different levels so that they are going to answer you at least 8 of those 12. (18:38).

3.      What makes a good interview (24:30): In a good interview, good stories come out. They become open and carefree (25:10). They say, “Never told anyone that before”. Sometimes they are literally whistling and singing. Sometimes they get emotional – at a deep level, cry, narrate horrible stories (28:00). They get a feeling, “They can sing for you and not going to be judged.” (28:25).

“If you convey to that person that the moment that you are standing there, sitting there, interacting with them is the most important moment in the world, that makes everything happen.” (28:50)

4.      Common mistakes (19:00):  Showing a big surprise e.g. “You are 24?” (10:10) can be distracting. Nodding too much and saying phrases like “Aha, Yeah, Thanks a lot, That was great” could be distracting (23:10). Asking leading questions or compound questions are common mistakes (23:30).

I have watched this video at least half a dozen times and I have learned something new each time I watched. I highly recommend it for anyone interested in design thinking and learning empathic interviewing.

Saturday, December 12, 2020

Mindfulness on the go: Webinar series Sept 26 to Nov 14, 2020

I got an opportunity to collaborate with a number of friends to offer a webinar series "Mindfulness on the go" from September 26 to November 14, 2020. In each of the 8 sessions, I and my co-host discussed one of the 8 chapters from my book "Mindfulness: connecting with the real you". Video recordings of all 8 sessions are available on YouTube. Here is the playlist. Link to an individual session can be found in the table below.



Session (videos)



Sept 26

Balancing the bicycle of life (PDF of the first chapter)

Shalini Goel


Oct 3

Listening to the mental shotgun

Gauri Dabholkar


Oct 10

Stepping out of the train of thought

Dr. Kavita Desai


Oct 17

Recognizing wasteful thoughts

Vipul Mathur


Oct 24

Watching the dance of necessities

Vivek Dabholkar


Oct 31

Investigating the shooting game

Nitin Desai


Nov 7

Searching for the real hero

Ashwin Patil


Nov 14

Dying to self-image every moment

Padmaja Parulkar