Why do we have poor designs?

We marvel at the design of houses, town planning, and the water & sewage management system of the Indus Valley Civilization, which is at least 3,500 years old. At the same time, we are alarmed by looking at the state of our metros such as Mumbai and Bangalore, shocked by the design of public space crowd management in temples and stadiums causing 100+ deaths last year in the country, and express disbelief at the NEET exam fiasco affecting 20 lakh students. After several thousand years of designing various artefacts, why do we still have poor designs?

Designers have become a dangerous breed: Fifty-five years ago (1971), Victor Papanek began his influential book, “Design for the real world,” with the following observation. “By designing criminally unsafe automobiles that kill or maim nearly one million people around the world each year, by creating whole new species of permanent garbage to clutter up the landscape, and by choosing materials and processes that pollute the air we breathe, designers have become a dangerous breed.” He was talking primarily about industrial designers. However, we can easily extend the “dangerous breed” argument to strategy, policy, intervention designs as well. So, the question is, why do we have poor designs?

Here, I suggest three fundamental causes. Perhaps there are more.

1.       “I know it” syndrome: Outgoing IG(Prisons) at Tihar Jail had advised Kiran Bedi, “There is no work there! I was IG (Prisons) many years ago; I received just two files a day. So, I used to clear them from my home.” Perhaps the biggest challenge for a designer could be overconfidence. When I have decades of experience, why waste time listening to various stakeholders? Kiran Bedi managed to overcome this bias by deciding to go for a round of Prison no. 1 on day one of her posting. It is not easy to listen, but like the title of Kiran Bedi’s book on Tihar Jail experience, “It’s always possible”.

2.       Personal agenda dominates: When Microsoft Co-founder Bill Gates was asked about his association with the convicted sex offender Jeffrey Epstein last June in Congress, he said, “I was so focused on the possibility of raising funds for global health that I allowed that goal to override my better judgment”. Most of us carry several conflicting impulses or agendas simultaneously - make money, generate profit for the company, push a political ideology, accumulate more power or control, help the poor and needy, live sustainably, make the world a better place, etc. During our decision-making, one agenda dominates, without us being aware of it. Jay Forrester, the father of systems dynamics, says, “Sustainable development is an oxymoron.” 

3.       Don’t see the danger: All Indian citizens, including those with a passport and a voter ID, are now doing their best in proving that they are indeed Indian citizens. The Election Commission of India (ECI) initiative to revise the electoral list is called “Special Intensive Revision (SIR)”. Both online and offline submissions are allowed. In Karnataka, India’s one of the most advanced digitalizer state, the online voter registration “has struggled to keep pace, with its rigid interface, resulting in an abysmally low registration rate even among tech-savvy applicants,” noted a Times of India article last month.  Out of more than 1 lakh online registration attempts, only a tiny fraction (0.2%) has successfully sailed through the portal. I know the challenges because I am one of those tiny fractions. Why is SIR enrolment design so poor? I feel one important reason is that the designers don’t see the danger of the poor design. The danger of denying voting rights to some citizens or the danger of designing leak-prone exams.     

Unfortunately, Papanek was spot on more than half a century ago. Designers have indeed become a dangerous breed. Overconfidence bias, personal agendas, and inability to see the real danger make it hard to do good designs. In an AI world where a rogue AI agent is hacking your computer, is there any hope?

image source: frontline.thehindu.com (photo credit: Shashi Shekhar Kashyap)

Journey mapping tips from Tony Fadell, the father of iPod

Journey mapping is one of my favorite tools to capture customer, employee, partner’s experience journey and identify gaps to enhance it further. Tony Fadell, the father of iPod, has given excellent tips on how he and his team at Nest used journey mapping for experience design in his book “Build: An unorthodox guide to making things worth making”. Here is an attempt to capture some of Fadell’s tips related to journey mapping.

“You should be able to map out and visualize exactly how a customer discovers, considers, installs, uses, fixes, and even returns your product. It all matters,” Fadell says in the book. When people come to him to show a new product they have built, he asks, “Tell me what’s so special about the customer journey”. If the customer journey is that important, why does it get ignored? Fadell points to the cognitive bias we tend to carry – “We’re wired to focus our attention on tangible things that we can see and touch to the point that we overlook the importance of intangible experiences and feelings.”

Before we look at 3 examples of how journey mapping was used for Nest, let’s look at a journey map template Fadell gives along with possible touchpoints in each stage:

Fadell’s point is that we tend to focus on the “product design” stage at the cost of the other stages. Here are three examples from the Nest learning thermostat design.

The app: In the early days of Nest, everyone was focused on perfecting the thermostat. It involved getting the design, AI, electronics, mechanics, colors, textures, right. The installation, feeling of turning the dial, the glow when you walk past, all this was thought through. Fadell points out that in Nest journey, 10% was website-ads-packaging-in-store display, 10% was installation, 10% was looking-and-touching the device and 70% was monitoring and control on phone-laptop. After the thermostat was installed and working, majority of touchpoints were through the app. And the team had lost track of the app. They had done initial prototypes when the project began but thought it to be the easy stuff they can come back to later. And it got pushed to the end. Fadell admits he became “really loud” to bring team’s attention to the app.

The box: “You should be prototyping your marketing long before you have anything to market,” says Fadell. And that is what they did at Nest. The cardboard box, its packaging, the product name, the tagline, the top features, their priority order – all these were printed on a cardboard box and constantly tweaked and revised. Two personas were created one tech-savvy husband and his wife, the decision maker, dictated what made into the house and what got returned. Nest team was asking questions like, “Why would they pick up the box? What would they want to know? What was most important to them?” There was no thermostat isle in Best Buy, Nest’s first retail partner. Thermostats were not bought by homeowners directly. Best Buy was not going to create a thermostat isle either. So, they collaborated with Best Buy and invented a Connected-Home isle.

The screw-driver: When prototypes of the actual thermostat were ready, they were sent out to people to test. Self-installation was potentially a major anxiety generator. Hence, it was a crucial test. Testers reported that the installation was smooth. Everything is up and running. But it took about an hour to install. That was way more than what the team thought. So they started digging into the installation experience and see where things are taking time. It turned out that the installation itself was not the culprit. The testers spent twenty minutes locating the right tools like the screwdriver. So Nest team decided to include a little screwdriver in the installation kit. And, to their surprise, the screwdriver served the purpose of a marketing tool because people had to use it more often than the actual thermostat.

In short, the app, the box, and the screwdriver are excellent examples of how journey mapping can be used to enhance the intangible touchpoints in a customer’s journey.

Related articles:

Journey mapping illustrated through Dunzo’s order-tracking experience

Image sources:

Nest screwdriver image source: https://bmak.substack.com/p/nest-screwdriver

Nest app and thermostat image source: youtube.com

Journey mapping: illustrated through Dunzo’s order-tracking experience

Whether you are eating, sleeping, gaming, commuting, or working, you are having an experience. And designing richer experiences is the core objective design thinking. Journey mapping is a tool that can be used to map the current experience and imagine an enhanced one. In this article, I would like to present journey mapping process using an example of Dunzo’s order-tracking experience. I will use the blog “Revamping Dunzo’s order tracking experience” by Divyanshu Nandwani as input to build the journey map. Divyanshu has nicely captured the thoughts and emotions of Dunzo’s customers from the time they place an order to receiving it. And he also presents how the experience was enhanced subsequently.

We will look at journey mapping as a 5-step process: (1) Gather customer inputs (2) identify journey stages (3) map customer experience (4) identify dark and bright spots, and (5) frame the challenge.

1. Gather customer inputs: The journey map needs customer or stakeholder inputs. In the case of order tracking, you will need what customers are thinking, at what stage of the journey, with what emotion, and with what kind of emotional intensity. You may use interviews, observations, input from the customer support department, data available through apps, etc. In the case of Dunzo, they got the inputs from support tickets, research interviews, and by looking at the data. Since customers reached out to the delivery partner directly, delivery partners also become an important source of input. If you are launching a new product or service, your input will come from your potential customers’ existing journey that you are planning to enhance. Here is what Dunzo folks have gathered as mentioned in the blog:
2. Identify journey stages: It helps to divide the journey into a few stages. For example, the order tracking journey can be divided into the following milestones: (1) Order received (2) Order accepted by the outlet (3) Partner assigned (4) Partner at the outlet (5) Parcel picked (6) Parcel delivered. These six milestones divide the journey into five stages. We could have made this into a 4-stage or an 8-stage journey by reducing/adding stages. 

The vertical axis of this journey map corresponds to the emotional intensity associated with the observation. The middle line denotes neural emotion. We place observations with positive emotions in the upper half and observations with negative emotions in the lower half of the map. When an observation has high intensity of positive emotion, say the customer is extremely happy, the observation will be placed on the top of the map. Conversely, when the customer is extremely annoyed, it will be placed towards the bottom of the map.

3. Map customer experience:  Once we have observations/thoughts gathered from customers and the stages of the journey ready, we can start placing the observations on the map. For example, observation 2 “Why hasn’t a partner been assigned yet?” is placed in stage-2 where the order is accepted by the outlet but the partner is not assigned yet. Since the customer is likely to be anxious while raising this question, the observation has been placed in the lower half. I have assumed that the anxiety is medium (not very low and not acute). Likewise, I have placed most of the observations listed in step-1 on the map below.

Note that map building can be an ongoing process and is best done by a team rather than an individual. It can be built over a period, say a month, and then looked at for patterns, particularly dark and bright spots.

4. Identify dark and bright spots: Bright spots are those observations where the customer is really happy/excited etc. They are located in the upper half of the journey map, especially towards the top side. For example, observation-13 “Oh yes! The partner is moving” is a bright spot. In contrast, observation-16 “Why is it taking time at the store?” is a dark spot. 

5. Frame the challenge:  The primary objective of journey mapping is problem discovery. Journey map offers multiple options for framing a challenge. For example,

• Focus on one stage where you want to enhance the experience (e.g. it could be stage-4 in the journey map above which has two dark spots)
• Focus on dark spots and ask, “How do we reduce/eliminate the anxiety of our customers?”
• Focus on bright spots and ask, “How to replicate the joy across other stages?”
• Frame a challenge around end-to-end experience?  For example, the dunzo blog presents following end-to-end experience framing, “How do we show that the order status is coming from the partner and not from the machine? How do we give a human vibe to the order status updates?”

It helps to identify a concrete metaphor or analogy while framing the challenge. For dunzo, the inspiration came from our friendly chat messages. They framed the challenge as “How do we deliver status updates as personalized messages coming from the partner in first person?” This was supplemented by adding animations.

Journey mapping is useful irrespective of whether you are in a B2B, B2C, or D2C business, whether you are offering a product, a service, or a solution. Hope you get to try it out.

Design Thinking: articles at a glance

In this table, I have tried to organize my blogs according to various topics associated with design thinking. Hope this is helpful.

Process step	Links
Empathy (Listening, observation)	Design Thinking resources #2: Empathy My 4 takeways from ""Getting people to talk: an ethnography and interviewing primer" Is "design thinking" old wine in a new bottle?  Empathy as accessing 3 kinds of ignorance Empathy tips from Kahneman's "Adversarial collaboration" Empathy as understanding the assumptions behind the rigid reflexes Can we empathize through data without face-to-face interaction? Dr. Kiran Bedi's first day at Tihar Jail
Define	How to build curiosity stamina? Three sources of curiosity: pain, wave, and waste 3 characteristics of a good challenge statement 5 ways of framing a challenge 3 ways a metaphor helps in challenge framing
Ideate	Four approaches to problem-solving Problem-solving approaches: clock-fixing vs cloud-fixing Do ideas float in the air? Could listening be the biggest source of ideas?
Prototype & test	Prototyping to clarify requirements: a 747 experience Rapid prototyping: 1-hour, 1-day, 1-week prototypes Before-and-after storyboard: A simple template My 3 takeaways from Ken Kocienda's "Creative selection" at Apple Story of how Google's AdSense almost got killed
Idea communication, Pitching your idea	An idea presentation template based on Steve Jobs' iPod launch speech in 2001 An idea presentation template based on a 2-minute pitch by The Wand Company founders How smart guys pitched their ideas to Steve Jobs, prickly perfectionist Idea communication: The Edison way
Fail fast, learn fast	Does "fail fast" contradict "first time right"? 2 ways of learning to fail with comfort My 3 takeaways from Scott Adams' "How to fail at almost everything and still win big" Doing the last experiment first: illustrated through Alex Honnold's El Capitan free-solo

Can we empathize through data without face-to-face interaction?

As a facilitator of design thinking workshops, I have held a view that face-to-face observation and listening are essential elements of empathy. Our body language sends powerful ques about our state of being, our approvals, disapprovals, comforts, discomforts, etc. And it is very difficult to capture these through data, graphs, analytics, etc. However, this belief is being shaken up over the past few years. Can we empathize through data alone? In this article, I present a few examples that have made me ambivalent.

Last year I read Brad Stones’ “Amazon unbound: Jeff Bezos and the invention of a global empire”. It is a story of Amazon’s transformation from a powerful force into the Giant over the past decade. The book highlights the data obsession at Amazon led by Jeff Bezos and percolated throughout the company. Decisions about whether to launch a new product such as Alexa, which private label products to launch and the locations of the warehouses were all based on data. Stones sometimes calls this “cold, hard data”. Given the size of Amazon’s customer base and its nature of ecommerce business where except delivery everything else happens online, it is understandable that Amazon doesn’t need face-to-face observation of customers. It is possible that the ecommerce business focuses on the 3 core customer needs, low prices, vast selection and fast delivery which don’t change much. Perhaps all other customer insights come through data without any face-to-face observation.

I thought the situation may be different for Alexa, the AI-enabled conversational device as well as a technology platform Amazon sells because building empathy is an important goal. It turns out the kind of effort that is being put in making Alexa socially relevant in a conversation, involves gathering a large amount of customer conversations with Alexa. This seems to be more of device-to-face interaction rather than face-to-face interaction. Customers who are helping Amazon evaluate newer ways of conversing with customers as part of Alexa Prize competition are interacting with the device and giving a rating on how likely they would be to converse with this “friend” again. No face-to-face interaction.

One would expect that face-to-face interaction is necessary in emergency psychiatry. However, Karl Deisseroth, a psychiatrist and neuroscientist at Stanford, tells in the book “Connections: the new science of emotion”, how his belief has changed over the years and got further validated during Covid pandemic. He says, “Emergency psychiatry, I saw again and again, though it somehow surprised me each time, can be carried out with precision even over phone, through that lonely single line.” He feels, “Psychiatry and medicine broadly – though still constructed around interpersonal communication – can survive and operate well with much less social information than the traditional face-to-face interview provides.”

Earlier this year, I read Kazuo Ishiguro’s novel “Klara and the sun”. The protagonist of this story is an artificial friend, Klara. And one of the reviewers has aptly called this book “an absolute master class in empathy.” Ishiguro in his subtle and slow-moving style creates various scenes in which Klara, the robot, learns about human anxieties and aspirations through observation and conversation. If this fiction work is any indication of what could become a reality, then perhaps outsourcing empathizing to a robot is not too farfetched.

A few months ago, I joined a team of senior managers at an offsite in the outskirts of Bangalore. The team members have been working with each other for years and were meeting online throughout the pandemic. However, they were very happy with the face-to-face interaction and it came up multiple times during the conversations.  Video calls were dry and to the point. The physical presence, jokes, fun cooking activity, eating together in a relaxed atmosphere was no match to innumerable video calls.

Now you get some idea about my ambivalence. Can we empathize through data without face-to-face interaction? The answer seems to be a ‘yes’ at least in some contexts. But, can we eliminate face-to-face interaction in most contexts? I am doubtful but now open to the possibility.

Sources:

For Alexa related discussion, check out

Laura Stevens, “Alexa, can you be empathetic, all-knowing and funny?”, Wall Street Journal, March 7, 2019

“Rohit Prasad: Amazon, Alexa and Conversational AI”, interview of Rohit Prasad, Head Scientist, Alexa by Lex Fridman, Dec 14, 2019.

Is design thinking right-brain centric?

“Is design thinking a right-brain specialization?” or “Am I a left-brain person?” Questions of these sorts are not uncommon in my design thinking workshop. However, I have been unsure of my response to this topic so far. My ambivalence has been influenced by the literature that points to the myths associated with creative-left vs analytical-right brain classification (also check this article). But then popular authors like Daniel Pink have argued that abilities like design are right-brain abilities (Check his video 53:00). My friend and collaborator Prof. Ganesh Prabhu has been presenting this Daniel Pink view in our joint program at IIM Bangalore for the past few years. That kept on nudging me to look for more evidence one way or the other. Recently, I came across Iain McGilchrist's book “The master and his emissary: the divided brain and the making of the Western world” which has shed some light on this confusion. In this article, I would like to present my learnings from this book related to this left-vs-right brain topic.

Let me begin with a process view of design thinking and associated competencies that I present in my workshops. Note that this is not the only process view of design thinking and is borrowed from the Stanford Design School framework. The competency view is not exhaustive either. But it is useful for our purpose.

Now, let’s turn to McGlichrist's book “The master and his emissary”. McGilchrist is suggesting in this book that left (LH) and right hemispheres (RH) are different in not what they do but how they see or pay attention to the world. The LH sees the world through a map of objects it constructs separate from itself and its primary objective is to secure a better future by manipulating the world. In contrast, the RH sees the world as fresh, living, ever-flowing whole not separate from itself. LH sees parts first while RH sees the whole first. Originally, the RH was the master and the LH was a helper to carry out repetitive tasks. However, over the centuries, the map has become extremely sophisticated and the helper or the emissary has become the dominant master and it has made RH a subservient helper. Through the nerve fibres connecting LH and RH (corpus collosum), LH mostly sends the message to RH, “I don’t need you”. As the map gets solidified, one becomes more intolerant of alternate worldviews. The map begins to get treated as the territory and that creates all kinds of conflicts.

When LH becomes dominant, McGilchrist argues, certain functions where RH plays an important role weaken. He mentions many but here is a list relevant for us: empathy, metaphoric thinking, capacity for insight, and holding ambiguous possibilities in suspension. Here are a few quotes from the book on each of them:

Empathy: Self-awareness, empathy, identification with others, and more generally inter-subjective processes are largely dependent upon…right hemisphere resources. (pg 57, 2019 new expanded edition)

Metaphoric thinking: Metaphoric thinking is fundamental to our understanding of the world because it is the only way in which understanding can reach outside the system of signs to life itself. It is what links language to life…Only the right hemisphere has the capacity to understand metaphor. (pg 115)

Insight: Insight, whether mathematical or verbal, is the sort of problem-solving that happens when we, precisely, not concentrating on it, is associated with activation in the right hemisphere. (pg 65)

Holding uncertainty: The left hemisphere needs certainty and needs to be right. The right hemisphere makes it possible to hold several ambiguous possibilities in suspension together without premature closure on one outcome. (pg 82)

While empathy and metaphoric thinking map directly onto the process view above, insight is typically associated with define and ideation stages, and holding uncertainty is related to hypothesis thinking of the test stage. Thus, if McGilchrist’s hypothesis is indeed correct, then we might have a tendency where LH inhibits RH from either activating or passing on information related to empathy, metaphors, insight, alternate hypotheses. 

Of course, this doesn’t mean everything in design thinking is right-brain centric. For example, one can define a challenge without using a metaphor – improve sales by ten percent or reduce the turnaround time by fifty percent. Inventive techniques seem to, at least partly, belong to the LH domain. Similarly, prototyping would need LH resources to manipulate objects in building the prototype.

In short, McGilchrist’s book “The master and his emissary” suggests that design thinking is heavily dependent on right hemispheric resources. It is no surprise that learners who approach design thinking as purely a conceptual framework to be understood by reading a book or listening to a lecture struggle to grasp the essence.

3 types of thinking Harish Hande highlighted for social innovations

Last week, I finished co-teaching the course “From jugaad to systematic innovation” with my friend Prof. Rishikesha Krishnan at the Indian School of Development Management. In the last class, Rishi had invited Selco founder Harish Hande as a guest speaker. In a short span of half an hour, Harish managed to instill a big dose of creative energy in the class. He told us about the type of thinking he felt is required while innovating in the social sector. Here are 3 types of thinking Harish highlighted:

Holistic thinking: Harish said, “One of my biggest barriers is the ability of people to think holistically”. People tend to identify themselves with a particular discipline such as mechanical engineering, marketing, finance but nobody says, “I am a solution provider”. We get caught up in our degrees and don’t think of what it takes to bring the solution to the doorstep of the customer.

Selco has labs in Kalahandi in Odisha, Williamnagar in Meghalaya, Guwahati and Bangalore where new programs are designed. And every program design team includes an architect, an engineer, a doctor, a finance person etc. Sometimes it also includes an anthropologist and a Yakshagana artist. They have to answer the question, “Is the solution affordable in the long run?” A solution that is low-cost today could be unaffordable in the long run. For example, a solar-powered sewing machine may enable a woman to produce 8 shirts a day instead of 2. However, if she is not able to find a market for her products then we end up creating technology debt. Hence, program design teams are encouraged to spend more time exploring the problem and think long term before they think of solutions.

Cheat thinking: How do we cheat from other processes? That is, how do we copy the seed of an idea from other working examples? Harish illustrated this idea with the mid-day meal scheme. A mid-day meal attracts kids to school in order to get nourished. In a similar way, could kids be attracted to school in order to get portable batteries charged so that their houses get lighting at night? With this observation Selco’s “Light for education” program was born where a school becomes a hub for the solar infrastructure in the village, a go-to place to charge your batteries. If American Express comes up with a new financial product, could one see if there is a seed of an idea there that can be adopted? Or could we borrow something from the vocational curriculum in German schools? What Harish calls cheat thinking is similar to what I call metaphoric thinking, a solution-centric approach to problem-solving.

Open-source thinking:  A question was asked, “How do you see the role of competition in the development sector when it comes to innovation?” Harish said, “Social sector promotes collaboration on paper. But it is the worst collaborator. Competition in the social sector is much more cut-throat than in the private sector.” He added, “The aim of many of the non-profits should be to kill themselves, not to grow.” He felt we need open source thinkers whose end goal is how many people will get benefitted rather than how do I keep it to myself. There is hero-worship in the sector where people are recognized by the awards they amass. “Collaboration is far away,” Harish said. He hoped that program design with holistic thinking would promote collaboration from early stages.

It was a privilege to listen to Harish and thanks to Rishi for making this event happen.

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.

Design Thinking resources #2: Empathy

Three years ago, I wrote a blog “Design Thinking resources #1” where I presented a set of resources (articles, books, videos) related to the overall design thinking process. In this article, I would like to extend the list with resources related to an important element of design thinking – empathy.

1. Getting people to talk: An ethnography & interviewing primer (30 min): This video is created by two students of the Illinois Institute of Technology (IIT) Institute of Design in 2008. It gives a very good perspective on what it means to interview a stranger. It highlights the difference between an ethnographic interview and a hypothesis-driven interview. It tells you about extreme user interviews and expert interviews. It brings out the key aspects of a good empathic interview (curiosity, listening, establishing a rapport, narration of stories). It also points to the common mistakes during interviewing – too much nodding, saying, “Aha, Ya, Thanks a lot, That was great, That’s interesting” which could be distracting, compounding questions, leading questions. Overall, I feel this is an excellent primer for interviewing.

2.  How to do a user interview (from Google Ventures) (6 min): Many times you have a hypothesis about what the user wants. And you might have created prototypes (paper/plastic models or wireframes) and you want to validate the hypothesis. This video presents a good illustration of this process. It demonstrates 5 acts: Friendly welcome, context questions, introduction of prototypes, tasks and quick debrief. The video demonstrates that when the user actually uses your prototypes, the interviewer mostly just watches and only occasionally asks questions.

3.  3 essential elements of an empathic interview: In this article, I present 3 elements which I consider important in an empathic interview – listening, appreciation and elaboration.

4.  What is an empathy map? (5 min): Empathy map is an important tool to organize data gathered through design research (interviews, observations). This short video introduces us to a basic Say-Do-Think-Feel empathy map.

5.  Lego story: What the company learned from its mistakes (5 min): In this short video, the then CEO of Lego company, Soren Torp Laursen presents the difference between listening and really listening. He tells a story of how despite focus group interviews with kids, the company heard what it wanted to hear. This shows how the power of biases can act through the well-intentioned interviewing process.

6.  Sonu Nigam – The roadside ustaad (6 min): Try method – i.e. trying to live like another person is a powerful empathy method. In this short video, a popular Bollywood singer Sonu Nigam is shown to spend some time singing on the street walkway dressed like a beggar. The camera captures the responses of the passers-by. And Sonu also gives his perspective later in the video. Companies like Tesco make it mandatory for executives to work behind the checkout counter a few days in a year. I learn a lot while walking on the street with my 83-year-old mother who is severely arthritic. 

7.  Amazon CTO Dr. Werner Vogels highlights listening to customers: This is an hour-long interview of Amazon CTO Dr. Werner Vogels. However, the part that is relevant for empathy comes around 14:00.  Here Vogles articulates his role as an external-facing CTO. And he highlights the importance of listening to customers while evangelizing the technology they are developing. He says, “95% of our new features and services are a direct response to customer requests.”

Are there any empathy tools that are missing from this list? One is journey mapping. Let me see if I can find one or create one if I don’t find a satisfactory resource.

Problem-solving approaches: clock-fixing vs cloud-fixing

 

“Car breakdown? Internet not working? Boss or spouse upset? Garbage everywhere? Long commute times? Corruption? Poverty?” How to solve it? Thus begins the blog I wrote six years ago titled “Four approaches to problem solving”. Today, we could add Covid to the list of problems. The four approaches presented in the blog are system-centric, problem-centric, solution-centric, and solver-centric. Which approach is applicable in which context? I suggested that as the social complexity of the problem increases, the role of solution-centric and solver-centric approaches increases. Recently, I came across a framework that sheds some light on this hypothesis. It involves understanding the difference between clock-fixing and cloud-fixing. Before understanding the fixing part, let’s understand what the analogies of clock and cloud mean.

Dividing the world between clocks and clouds is attributed to Karl Popper, the philosopher of science, who wrote the article “On clocks and clouds” in 1966. Clocks are predictable while clouds are unpredictable. When a clock malfunctions it is possible to dismantle it into smaller parts, diagnose the problem, replace the malfunctioning parts, and put it all back. In contrast, if a cloud doesn’t give enough rainwater, we don’t know how to fix it – at least not yet.

As a system, a cloud is considered more complex than a clock2. What makes a cloud more complex than a clock? One characteristic could be its degree of openness. A clock is a relatively closed system i.e. its behaviour doesn’t depend much on the environment while a cloud is a relatively open system i.e. its shape and content may be undergoing continuous change due to the interaction with the surrounding environment. A few more properties of complex systems are Non-linearity (Can a small change cause disproportionately big impact?), Emergence (e.g. a cloud can suddenly turn into a tornado but a clock can’t transform itself spontaneously). There is no precise definition of a complex system but we can get some idea by contrasting clocks and clouds (see complex system page from Wikipedia for more details). Could this distinction between cloud vs clock or clock-ness vs cloud-ness of the problem help us decide on the approach of problem-solving?

When a person undergoes hip-replacement surgery, the process looks closer to clock-fixing. A part of the hip-bone gets replaced and the patient is able to walk again with a high probability. However, when a depression patient undergoes a psychotherapy session, it looks closer to cloud-fixing. You don’t know how many sessions he might need and even after that, it may not work. When a few second long video goes viral on the Internet and mobilizes huge crowds across multiple cities into protests, it certainly looks closer to clouds turning into a tornado. When someone says I want to control thoughts through a brain-machine interface, doubts get raised as to whether a clock-fixing approach is being applied to a cloud-like system2.

Instead of putting each problem into a clock vs cloud bucket, how about if we look at different dimensions of the problem and solve it using an appropriate approach? Let’s take Covid-19 as an example. One could just take maximizing sanitizer usage as a goal, especially in shops and malls. And then apply a system-centric approach, break-down the process of entering a shop, and introduce a mandatory step of using sanitizer at the entry point. Alternately, one could apply the problem-centric approach, do the causal analysis, work towards the Covid vaccine, or in the interim find drugs with sufficient efficacy. Causal analysis can also be carried out through computer simulations of networks and infer probabilities of various causes in a regional cluster. 

We could move closer to cloud-like dimensions and ask questions like, “Why is certain population not even susceptible to Covid despite exposure?” And then one could look at bright spots “people who are tested negative despite sustained Covid exposure” and see if that data gives any clues. Finally, we could just look at the depression wave that is coming as a side-effect of the pandemic. And look at psychotherapeutic or introspective approaches. This is where the dimension gets closest to the cloud. Awareness of the nature of the problem may help us in predicting the chance of success.

In short, we saw that knowing the nature of the challenge – whether it is closer to a clock or a cloud, may help us follow an appropriate approach in creating the response. Alternately, we could look at the clock-like or cloud-like dimension of a challenge and try to respond appropriately.

Notes:

1. This analogy has been used by others to differentiate reductive vs non-reductive approaches of analyzing and fixing systems. For example, see Robert Sapolsky, Stanford professor of biology, neuroscience and neurosurgery use this analogy in his May 19, 2010 lecture “21. Chaos and reductionism” at around 44:18.

2. Karl Friston, Professor of computational neuroscience at University College London, compares brain-computer interfacing to solve psychopathic problems to satellites perturbing weather and changing it meaningfully in the interview “Karl Friston: Neuroscience and the free energy principle: AI podcast #99 with Lex Fridman” at 39:12.

My 3 takeaways from Ken Kocienda’s “Creative selection” at Apple

“How does this process compare with Apple’s design process?” is a question that I often get in my design thinking workshops. I talk about a few anecdotal incidents I have gathered from here and there. But quickly admit that I don’t know how it works at Apple. Thanks to Ken Kocienda’s “Creative selection: Inside Apple’s design process during the golden age of Steve Jobs”, we get some idea how the software design process worked during the first decade of this century, at least in the iPhone project. Ken is the father of the autocorrect feature of the iPhone and the book is also a biography of the idea from challenge to release. Here are my 3 takeaways from the book:

Importance of demo-culture: If there is one thing that Ken is trying to emphasize the Apple design process, it is the importance given to building and reviewing demos from top to bottom. Demos would get reviewed at all levels all the time. Selected demos would get reviewed by Steve Jobs and Ken begins the book with a detailed description of the drama associated with one of his demos to Jobs. That time Ken was working on the iPad keyboard and he was exploring how to provide the user with an option of two keyboards – one with bigger but fewer keys and the other with smaller but more keys. He had used a zoom key to toggle between the two keyboards. He was proud of the flexibility he was offering to the user. And yet the 2-3 questions that Steve Jobs asked him during the review played an important role in simplifying the design. Ken calls this iterative design process – demo – feedback – next demo – creative selection, the title of the book.

Role of challenge campaigns: In 2005, Ken was part of a small team of engineers working on the secret phone project called Purple. At one point, all the engineers were called for a meeting and it was announced that from then on all of them were keyboard engineers. It meant that the issue of software keyboard on a touch screen had become critical enough for all the engineering effort to be focused on it. The tactile feedback of a Blackberry-type keyboard was missing in their phone and hence typing accuracy was low. All engineers began to show their demos of various types of software keyboards. This is when Ken invented the autocorrect feature and his keyboard demo was selected for further development. This is an example of how challenge campaigns can be used to solve critical business challenges.  Unlike the keyboard derby example, not all business challenges need to be solved by stopping everything else. However, like the keyboard derby example, they need to emphasize demos and prototyping. And at the end, promising ideas need to be integrated into the roadmaps.

The intersection of technology and liberal arts:  In the chapter titled “The intersection” Ken says, “Apple valued expertise in both technology and liberal arts”. Ken is a history Major and pursued photography seriously for a few years before starting his career as a software developer. “Working at the intersection” was a topic of discussion among Apple employees and there was a half-day course on this topic at Apple University. In the technology industry, I am familiar with, this is hardly the case. People like to hero-worship Steve Jobs, but how many are willing to explore what it means to “work at the intersection”? I guess worshipping has always been easier than exploration in human history.

Apart from these concepts, Ken sheds light on many more areas associated with the Apple culture of his time such as the role of DRI – Directly Responsible Individual, the relevance of empathy & focus, the role of collaboration, the importance of asking oneself, “What do I really enjoy?” especially in the context of individual contributor vs management etc.

In case you prefer listening to audio to reading, I recommend Ken’s interview “Inside the Apple factory: Software design in the age of Steve Jobs”. It covers almost all of these points. 

Image source: goodreads.com

Empathy tips from Kahneman’s “Adversarial collaboration”

(Reading time: 5 minutes)

Empathy is one of the core elements of Design Thinking. It is easier to empathize while dealing with people we care about. However, things get more difficult when we are dealing with people whom we don’t like or who hold opposite views. It could be a family member or a colleague with whom we get into an argument regularly. It could also be a friend on the social network who holds exactly opposite religious or political beliefs than yours. How do you empathize with people holding exactly opposite views? I feel Kahneman’s idea of “adversarial collaboration” gives us a few clues even though he himself feels that this idea may not even survive. What is this idea of “adversarial collaboration” that Kahneman has proposed? Why does he feel it may not survive? And how could it help us build empathy muscle? This is what I would like to explore in this article.

“I have always hated quarrelling,” says Nobel Laureate Daniel Kahneman in this 2-minute video titled “Adversarial Collaboration”. “I have always despised scientific controversies,” he adds, “Because they become very personal and people very quickly get into a point-scoring mode where the truth is unimportant. That has struck me as quite destructive.” For those who genuinely seek the truth, he has proposed “adversarial collaboration”. And he admits, “It is not widely used and I am not sure that this idea would survive.”

Over several decades, Kahneman studied cognitive biases and concluded that human intuition is biased and not trustworthy. Gary Klein, on the other hand, studied expert intuition from people such as chess masters and firefighters and concluded that it is a marvel. Kahneman and Klein decided to work together to answer the question: In what context is expert intuition trustworthy and in what context it is not trustworthy. This collaboration lasted for 6-7 years. At the end, they published a joint article titled, “Conditions for intuitive expertise: A failure to disagree”. In short, they had found common ground.

What is my biggest takeaway from “adversarial collaboration”? It is the importance of context curiosity. The key hypothesis here is that every view is meaningful in some context. A drug addict, a terrorist, a money launderer – everybody carries a world-view which is meaningful in some context. In the extreme case, that context is limited to only one person. Understanding that context is empathizing. Hence, context curiosity forms an important element of empathy.

Understanding context would require a willingness to listen with openness. Listening to people who hold views opposite of yours is not easy. And hence perhaps Kahneman feels this idea of “adversarial collaboration” may not have takers. Listening with openness implies a willingness to say, “I could be wrong”. That’s harder than one can imagine. In Kahneman’s words, “People who think poorly of your work and your ideas, get on your nerves. And you have to overcome that.”

In a world where the polarization of views is increasing day by day, it is easy to encounter people who hold views exactly opposite of yours. I feel that is an excellent opportunity to build your empathy muscle. Are you willing to listen with openness? Alternately, are you willing to say, “Let me find out what is the context from which this view is coming from”? Please try it out and see for yourself.

Image source: YouTube video “Daniel Kahneman: Adversarial collaboration”

Kahneman's video “Adversarial collaboration”: (duration: 1:52)

Another video: Daniel Kahneman: Adversarial collaboration (duration: 2:14)