Is creative thinking an oxymoron?

Eckhart Tolle quotes Einstein in his bestseller “The power of now” that goes – “Thinking plays only a subordinate part in the brief decisive phase of the creative act itself”. And then Tolle writes further, “So I would say that the simple reason why the majority of scientists are not creative is not because they don’t know how to think but because they don’t know how to stop thinking!” Contrast this with Edward de Bono, famous for his work on lateral thinking. De Bono is the proponent of creativity as a learnable skill and his thinking tools are part of school curriculum in over twenty countries. de Bono says, “Creativity should be producible on demand. Formation and design of new ideas can’t merely be left to chance.” Is creative thinking a skill that can be learnt like de Bono says or is thinking a hindrance to creativity as Tolle says? Let’s explore.

Let me start with one of my favourite stories on creativity in the last 25 years – Andrew Wiles proving Fermat’s Last Theorem on 15^th Oct 1994 – a famous mathematical problem open for 350 years. This is how Andrew views the process leading to the moment of insight: “Often you write something down to clarify your thoughts. In particular when you’ve reached a real impasse, when there’s a real problem that you want to overcome, then the routine kind of (mathematical) thinking is of no use to you. Leading up to that kind of new idea there has to be a long period of tremendous focus on the problem without any distraction. You have to think about nothing but that problem – just concentrate on it. Then you stop. Afterwards there seems to be a kind of period of relaxation during which the subconscious appears to take over, and it’s during that time that some new insight comes.”

Andrew’s version of the moment of insight looks closer to what Tolle & Einstein are saying. In particular, Andrew is saying that there comes a time when one type of thinking (he calls it routine kind of thinking) stops and another type of thinking (he calls subconscious thinking) takes over. Daniel Kahneman calls the former – slow mode of thinking or system-2 thinking or rule governed thinking. And the latter – fast mode of thinking or system-1 thinking or intuitive thinking.

The intuitive thinking involves brain reaching out to a vast associative network of ideas already present in our memory. In the last one year before Andrew published his final proof, he had been struggling to solve one glitch in the proof that was discovered by one of the manuscript reviewers. The technique that finally helped Andrew overcome the issue was something Andrew had worked on and abandoned a few years ago i.e. the technique was present in his vast associative network of ideas all the time he was struggling. He remembers the moment, “I couldn’t understand how I’d missed it.”

Kahneman advocates following definition of creativity attributed to Sarnoff Mednick: Creativity is associative memory that works exceptionally well. Mednick’s definition of creativity connects both Tolle and de Bono. When Tolle says that thinking should stop, I feel he means that the interference due to the slow mode of thinking (system-2 or rule governed) should stop and let the intuitive thinking take over. Similarly, de Bono’s six thinking hats technique is trying to help you reach out to those areas of your associative network that you will not go to in the normal course.

In short, whether creative thinking is an oxymoron would depend upon the type of thinking involved.

Sources:

Einstein quote from “The power of now” by Eckhart Tolle, p 20

Andrew Wiles quote from “Fermat’s last theorem” by Simon Singh, p228

Kahneman’s definition of creativity is from his “Thinking, fast and slow” p 67

Impossible problems and successful approaches: story of Fermat’s last theorem (my blog, Oct 2008)

Technical Leadership: Frequently Asked Questions (FAQ)

I was invited at an IT services company in Bangalore to give a talk on technical leadership last Friday. During the talk as well as in the Q&A session several questions were raised. I realized that there is a need for a platform where engineers transitioning from being a technical expert to becoming a technical leader can turn to for raising doubts, discussion and guidance. I also realized that there are several people out there, some of whom I know personally, who are in a better position to answer the questions than me.

With this background, here is an attempt to create an FAQ forum for questions related to technical leadership. To get started let me use following definition of a technical leader - we can always question the definition later. A technical leader is someone whose sphere of influence due to his technical expertise is significantly greater than his span of control. As per this definition, engineers on the technical ladder (Product / Solution Architects, Principal / Chief Engineers, Technology Consultants, Scientists) are technical leaders. Moreover, managers who are able to influence people beyond their team with their technical expertise are also technical leaders.

Please give your views by clicking on any specific question and then adding your comment. You can also raise a new question.

FAQ:

1. In IT services companies, one needs to move from project to project - each lasting only a few years. How does one balance breadth vs depth?

2. I like to work alone and not worry about other peoples’ salary / leave etc. Does it mean I should opt for technical career path?

3. I am a Java person with 6 years of experience. What can I expect to be doing 4 years from now? Where do I begin?

4. Will the IT industry in India need more managers or more technical leaders in future?

5. Technology such as .Net or Java changes very fast. How do I cope up?

Thinking, fast & slow: A landmark book in intuitive thinking & decision making

"What is E=mc2 of this century?", our son Kabir asked me a few days after we watched the NOVA film "Einstein's big idea" together sometime last year. I thought about it for a few moments and said, "Psychology is the physics of 21st century, Kahneman is the Einstein and his work on happiness is like E=mc2". My answer and speed with which it came surprised me more than it surprised Kabir. I was clearly under the spell of Kahneman. Who is this Kahneman? And what is his work about? If you want to know, your best bet is to read Nobel Laureate Daniel Kahneman's bestselling book "Thinking, fast and slow". It has come out a couple of months back in India. It is a landmark among the psychology literature intended for layman, more specifically about intuitive thinking and decision making under uncertainty. It covers a vast spectrum. Let me articulate a few nuggets of wisdom from it.

Answering an easier question: When I look back at my answer to Kabir's question, it is clear that the answer was given off-the-cuff. In fact, I was in no position to answer the original question because I am clueless about most of the recent breakthrough developments in various sciences including those in psychology. Then what happened here? Kahneman explains it in chapter 9 titled "Answering an easier question". Whenever we are asked a question whose answer we don't know, the fast thinking mode answers an easier question. And unless the slow thinking mode checks & rejects the answer, it is given out like it happened with me. In my case the easier question that got answered was, "Among the scientific results I know, which one appeals to me the most?" Kahneman calls such shortcuts "heuristics" and we use them all the time. They work mostly and trick us real bad occasionally. When we are asked, "How happy are you with life these days?" we tend to answer the easier question, "What is my mood right now?"

Expert intuition: when can we trust it? I wrote an article last month about mathematician Srinivas Ramanujan and the marvels of his expert intuition. The article also highlighted how the intuition tricked Ramanujan occasionally creating incorrect results. In chapter 22 which is titled "Expert intuition: when can we trust it?" Kahneman presents the exact criteria under which experts develop real expertise. You acquire skill when (a) you have an environment that is sufficiently regular to be predictable and (b) you have an opportunity to learn these regularities through prolonged practice. In some cases like that of stock analysts, the environment isn't sufficiently regular. On the other hand, chess players and basketball players do develop real skills.

Illusion of understanding: Kodak filed for bankruptcy protection last month. All the related stories published in Economist, Wall Street Journal, Wharton School of Business, an HBR blog had one thing in common. None of them contained the phrase "bad luck". Most of them sited some story or the other related to poor management decision making, the most common being the Kodak's invention of digital camera and how Kodak didn't pursue it's development etc. Implicit in these articles was an assumption that bad management decisions cause bad outcomes like bankruptcy and randomness or bad luck plays insignificant role. Kahneman calls these generalizations where randomness is substituted by causation "illusions of understanding" (chapter 19). It stems from 3 things: (1) We believe that we understand the past. However, in reality, we know a story of the past constructed from very limited information easibly accessible to us. (2) We can't reconstruct the uncertainty associated with the past events. It leads to things like the HBR blog suggesting Kodak should have created a photo sharing social network. (3) We have a strong tendency to see causation where there is none. Many times a single story such as Kodak's digital camera story is good enough for us to label Kodak management as the root cause of its debacle. I don't know how much of strategy literature suffers from "illusion of understanding".

Kahneman's law of happiness: Ask yourself "How special is your car to you?" and then ask yourself "How much do you enjoy the commute?" Psychologists have found a decent correlation (0.35) between the first question and the blue book value of the car. And, they have found zero correlation between the second question and the blue book value of the car. Such observations have led Kahneman to formulate the following law - Nothing in life is is as important as you think it is when you are thinking about it. Your car's importance to you is exaggerated only when you think about it. Unfortunately, you spend significantly more time driving it than thinking about it.

Kahneman's confession about the book: "I don't think reading this book will prevent any of you from making any significant mistake. Because even writing it hasn't helped me." said Kahneman in an interview. Then what does he hope to achieve? Well, Kahneman wants to see more sophisticated water cooler gossip about biases in decision making, mostly of others. I love the book and I am sure I will come back to it again and again in the future.

Kahneman videos:

TED talk “The riddle of experience vs memory”

“Explorations of the mind: Intuition” talk at University of California at Berkeley

“Thinking fast and slow: Conversations with Kahneman” interview at London School of Economics”

What innovation programs can learn from Quality Circle (QC) activity

I got an opportunity to attend 24^th CII QC Circle Convention involving finalists from 4 states in South India (Tamilnadu, Kerala, Karnataka and Andhra) held in Le Meridien on Dec 20, 2011. Each of the 15 participating teams had already excelled in the statewide competition. They were representing companies like Amar Raja, Ashok Layland, BEL, Kancor, Kochi Refinery, Lucas TVS, Rane Madras, Toyota-Kirloskar etc. My objective for attending this event was to understand (a) How does QC activity happen in manufacturing industry in India? (b) What can innovation programs learn from it? Here is my take:

A Quality circle is a volunteer group, a team of four to seven workers with the possible inclusion of their supervisor that understood the methodology of identifying and solving problems. For example, one of the teams named “Gold Star” had five members aged between 23 and 55 years. Two of them were 10^th standard, two had PUC and one had Diploma in Mechanical Engineering. Four of them were machine operators and one of them was a Quality auditor. The team had a patron who was a manager.

From their presentations, following things struck me as worthy of emulating by innovation programs in other sectors.

1. Team activity with gamification: QC circle is a team activity. Contrast this with the suggestion schemes where individuals are the heroes. Each team identified problems, set goals and systematically went about solving them. Weekly/fortnightly one hour was reserved for this activity (e.g. every other Wed 3-4pm). A typical project lasted 2 to 5 months. Each team had created an identity – some called themselves Kadamba warriers, some were Red Chillies, others were New Millennium etc. Each team competed against others within the company to do better at innovating within their environment. In at least some of the participating companies it was a decade long initiative with 100% participation as shown by the picture below.

2. Problem selection criteria: Selecting which problem to solve is given a lot of importance in QC activity. All the teams presented the list of problems they identified first – about 50 to 70. A commonly used technique for selecting the problem was called SQPC analysis. It meant to rate each problem on 4 dimensions – Safety, Quality, Productivity and Cost. In some cases these parameters were crisply defined. For example, safety – zero accidents, quality - < 2 defects per vehicle, production – MTBF > 3 hrs by Mar ’12, cost – 5% saving in allocated budget. See the picture. Depending upon the scope of innovation, this criterion may vary. However, it makes sense to identify some criteria in selecting problems to solve.

3. Genchi Genbutsu: This is a Japanese phrase meaning “go and see for yourself”, which is a central pillar of the Toyota Way. Genchi genbutsu is sometimes referred to as “get your boots on”, which has a similar cadence and meaning. Toyota-Kirloskar team presented how they did brainstorming at workplace to identify and solve the problem better (see the picture). This is similar to immersive research of P&G.

My learning: I derived following learnings for the innovation programs: (1) They can introduce innovation as a team sport - it just makes it more fun. These teams could be Communities of practitioners (like Java / SAP developers) or theme based teams (e.g. sustainability). The teams could compete based on a simple scoring mechanism (no of ideas submitted, no of prototypes demonstrated, no of ideas implemented, business impact etc). (2) Organizations can help innovators in developing a challenge-book. Similarly, organizations can define strategic priorities for selecting problems where it is willing to make non-trivial investment. These could be specific technology areas, customer segments or consumer/social/regulatory trends (3) Organizations can make “immersive research” an important aspect of problem understanding and solving. For example, Intuit’s “follow-me-home” or P&G’s “Living it, working it” programs do this.

Note: Thanks to Prof. Rishikesha Krishnan for the suggestion to make the learning explicit.

Dr. Gururaj Desh Deshpande’s insights on entrepreneurship and innovation

I got an opportunity to listen to Dr. Gururaj Desh Deshpande on “Can Social innovations and Technology innovations leverage off one another?” at the IIT Alumni Club Bangalore event held at Bangalore International Centre, Domlur, last morning. It was a fantastic talk. Here are a few of the insights Desh mentioned in his talk and during Q&A:

· Concurrent innovation: In a place like MIT where Desh is a Board member, there is no dearth of technology innovations. However, for the researcher or the faculty member working on the innovation, the primary interest could be elegance and publishability – criteria that matter for tenure and impressing peer group. The challenge is to create an atmosphere where innovations get connected with relevance to create an impact. This is what Desh calls concurrent innovation where innovators get connected to the real world up front as opposed to much later in the life cycle. Over the last 10 years MIT has funded 80 projects and a third of them have generated $100 M or more.

· The sandbox for social innovations: In social sector, the equation (innovation + relevance = impact) needs to be turned around. The real challenge is in understanding the problem. Then you bring in the ideas to solve the problem. We need to create an environment where this happens systematically. 6 years ago Deshpande Foundation created a sandbox in Hubli to do that. What is this sandbox? It encompasses 5 districts: Belgaum, Dharwad, Gadag, Haveri, and Uttar Kannada, and is home to about 10 million people. Ideas / interventions that need to be proven get experimented within this sandbox first and successful ones get scaled. Help is provided in the form of access to advisory network, teaching, additional resources from corporate / NGOs and of course, grants. Akshayapatra (mid-day meals), Karadi Path (learning through Karadi Tales), Agasthya Foundation (sparking creativity in rural India), Sikshana Foundation (improves quality of teaching in Govt schools) are some of the organizations that were incubated in the Hubli sandbox.

· Sustainability of social ventures: In many social ventures, the beneficiary does not have buying power (e.g. mid-day meal in state schools). Hence, there is a donor. Every time the donor wants to add value to the organization, he projects his risk tolerance on the project. Unfortunately, from his standard of living, he finds everything risky. Very quickly the product does not cater to the requirements. The idea is to take the performing assets, scale them and make them sustainable. i.e. find those interventions that are already working and scale them.

There are three ways a social venture becomes sustainable: (1) By becoming part of free market economy (2) By becoming part of Govt & (3) By supported through broad based charity as opposed to funded by a few rich people. Sometimes it is a combination of the three. For example, Akshaypatra combines (2) and (3).

· Role of value system in innovation: Entrepreneurship or innovation is just a tool. It allows you to do something faster and better. It quite doesn’t say whether it is for the good of the world or for the bad of the world. So you need a value system on top of it. That is a bigger issue we need to resolve. World economy is based on consumption. In the 70s there used to be a debate between capitalism and socialism. About 10 years ago, it looked like capitalism all the way. But now we are beginning to see cracks within capitalism. Consumption based economy means everybody has to consume more and more and more which will just rip apart this whole world. There will be nothing left. So the bigger challenge is to re-think on what winning means. Does winning include sustainability, goodness? Etc. In some area where we see this happening. For example, in energy, 10 years ago it was all about producing more energy. Now, people are realizing that the low-hanging fruits in energy are efficiency and savings and you could save up to 40-50%. Now there are 50 startups in Boston area and another 50 in Silicon Valley who are trying to figure out how they can get access to the low-hanging fruit – efficiency. People are building huge database of every building and then you do audit on a building and show what you can do to achieve how much saving.

· Role of technology in education: Majority of school going kids in India still don’t have access to computers and Internet. In fact, a lot of little things like eraser, pencil, 5-10 pieces of paper, old newspaper (acts as a reading material) have much bigger impact than the computers (For example, see “spot prizes” intervention of Sikshana Foundation – it is the oldest and most popular activity). This is not to say computers are not useful. It is just that getting tablets to villages and putting them to use is a little unrealistic at this point. That doesn’t mean we shouldn’t continue to experiment on these things. One of the best experiments Desh has seen being carried out in a few California schools is as follows: Suppose you want to teach Pythagoras theorem, then the students will be asked see Khan Academy video in the evening at home and come and do the homework in the school the next day. It is changing the whole paradigm. You need a lot of interaction / debate / discussion during the homework. There are going to be a lot of innovative ways of educating each other. In Desh’s opinion, the biggest problem in education is always inspiring kids to want to learn. So any intervention that inspires kids to want to learn is going to create significant value. Technology has been trying to intervene in education for a long time. But it hasn’t. Next 10 years are going to be exciting. MIT just announced a new initiative – MITx - which will offer certification through free online courseware.

Sources:

Photo from thehindu.com

The marvels and the flaws of expert intuition: story of Ramanujan’s first letter to Hardy

Malcolm Gladwell’s “Blink” presents the marvels of expert intuition and Nassim Taleb’s “The Black Swan” highlights the flaws of expert intuition. Well, Srinivas Ramanujan’s first letter to Hardy exemplifies both – the marvels and the flaws of expert intuition. Let’s see how.

Genius or fraud? “I beg to introduce myself to you as a clerk in the Accounts Department of the Port Trust Office at Madras on a salary of only Rs. 20 per annum.” Thus began the letter sent by 25 year old Srinivasa Ramanujan to Hardy, the then renowned Cambridge professor of mathematics. It was dated 16^th January 1913. The nine page letter contained around fifty mathematical results claimed by the Indian clerk. Ramanujan had explained in the letter “I have had no University education but I have undergone the ordinary school course.” What struck Hardy at the first glance was the strangeness of the theorems, not their brilliance. His first reaction was: is he a genius or a fraud?

The letter: The letter contained theorems in number theory, calculus, infinite series etc. Some of the formulae were familiar to Hardy, while others “seemed scarcely possible to believe”. For some reason, Hardy decided to consult his fellow mathematician Littlewood to reach a verdict on whether the author is a genius or a fraud. The duo spent three hours – from 9pm till midnight – going through the manuscript. At the end they concluded that its author is “a mathematician of the highest quality, a man altogether exceptional originality and power”. Some of the results Ramanujan sent to Hardy in his letter belonged to breakthrough category – Hardy was to conclude later. Hardy persuaded Ramanujan and the government to bring him to Cambridge.

The marvel of intuition: Ramanujan’s Indian friend in Cambridge, Mahalonobis who later went on to found the Indian Statistical Institute once asked him how he got a startling result. Ramanujan said, “Immediately [after] I heard the problem it was clear that the solution should obviously be a continued fraction; I then thought, which continued fraction? And the answer came to my mind.” The answer came to my mind sums up how Ramanujan got many of his results. Question is: How did answers come to Ramanujan? Did they get handed down by the goddess Namagiri of Namakkal in his dreams as some believed?

Ask yourself “What is 2 x 2 = “ and now ask yourself “What is 19 x 37 =” An answer would come to your mind immediately in the former case while nothing comes to your mind immediately in the latter case. Daniel Kahneman explains in “Thinking, fast & slow” that there are two different modes of thinking: a fast mode and a slow mode. The fast mode (called system-1) is intuitive, effortless and automatic while the slower mode (called system-2) is rule-based, effortful and controlled. You could choose to start the computation of “19 x 37” using the rules of multiplication learnt in school and also stop in between if you wish to do so (slow mode). You had no such control for “2 x 2”. The answer came to mind automatically (fast mode).

For an expert, such as a chess master, when he looks at a board position, several patterns and associated offensive and defensive moves come to mind immediately (like “2 x 2”). They come from a vocabulary of 50,000 to 100,000 patterns stored in memory. Psychologists believe that it takes 10,000 hours (about 6 years of playing chess 5 hours a day) to reach this level of expertise (or active vocabulary). Had Ramanujan done this kind of practice?

By 1900 (age 12) Ramanujan had mastered S. L. Loney’s Trigonometry. However, the year 1903 was a turning point when he found a book written by Carr containing 5000 equations related to algebra, trigonometry, calculus, analytical geometry, differential equations. From this point, life of Ramanujan who graduated from school that year with a reputation of being “off-scale” went off-balance. He didn’t do anything other than mathematics. He failed four attempts to pass in college in 1904, 1905, 1906 and 1907, lost scholarship and didn’t do well even as a math tutor. And yet, this five year period of 1904 to 1909 was the most productive time in his life because, in all likelihood, he was at home manipulating equations in all of his waking hours – on a slate, on a paper and in the mind. It is also quite possible that his fast mode of thinking was so active that during sleep it continued to work on the half-solved problems. The fast mode is known to be working even when we are not conscious. Ramanujan had easily finished his quota of 10,000 hours well before 1909.

Did his intuition ever trick him? Yes, it did, occasionally and it showed in his first letter to Hardy as well.

The flaw of intuition: In his first letter, Ramanujan had written that he had found a function which exactly represents the number of prime numbers less than x. After Hardy demanded a proof, Ramanujan sent one. And Littlewood figured out that it was wrong. Well, Ramanujan’s formula wasn’t bad. It was off by only 53 for calculating primes up to first nine million (which are 602,489). However, the difference became bigger as numbers grew larger. And this is what Ramanujan failed to see.

Checking a sketchy proof rigorously, at least partly, is a responsibility of the slow thinking mode. As Kahneman observes that the slow thinking mode is inherently lazy. If an answer given by the fast mode looks fine, it just endorses the verdict. In Ramanujan’s case the slow mode was not just lazy, it was weak. Because he never formally learnt how to write a rigorous proof until he reached Cambridge. The upside of this characteristic was that the fast mode was freerer than usual in its meanderings – making him highly creative in his approach.

What was interesting about Ramanujan was not that his intuition was sometimes wrong. Even a great mathematician like Andrew Wiles also had a serious hole in his first proof of the Fermat’s Last Theorem. What was different about Ramanujan before coming to Cambridge was that he was equally confident when he was right and when he was wrong.

Two key learnings from this story: One, a rich vocabulary of several hundreds of thousands of patterns resulting from a prolonged practice and timely invocation of appropriate patterns by the fast mode of thinking creates expert intuition. Two, knowing when not to trust the instincts is an important characteristic of a true expert. Ask yourself, "Which are the possible situations in which my instincts could be on a slippery ground?"

Sources:

The man who knew infinity by Robert Kanigel, Washington Square Press, 1991. (Thanks to my friend Ramprasad Moudgalya for recommending the book to me).

Conditions for intuitive expertise, Daniel Kahneman & Gary Klein, American Psychologist, Sept 2009.

Related articles:

My most favorite YouTube video and the marvels and the flaws of intuition, Sept 19, 2010 (On Kahneman's lecture at Berkeley on the same topic).

Impossible problems and successful approaches: story of Fermat's Last Theorem, Oct 28, 2008 (On Andrew Wile's successful attempt at solving 350 old most famous open problem).

Weighing scale, intelligent gossip and the culture of innovation

Gossip is an important element of every culture, be it in the café, corridor or conference room. In fact, Nobel Laureate Daniel Kahneman writes in the introduction of his new book “Thinking, fast & slow” that the primary objective of the book is to generate intelligent water cooler gossip. Which is the most powerful source of gossip? Perhaps there is no easy answer. However, “weighing scale” is certainly a good candidate. When ten of us, old school friends, met a couple of weeks back after a long time, the starting point of the conversation was invariably – how much weight one has gained or lost. What makes “weighing scale” such a remarkable gossip generator? Can we design “weighing scale” for measuring innovativeness? Let’s explore.

The first thing that strikes about any weighing scale is its simplicity. You don’t need a user manual. Have you seen 6-7 year olds weighing themselves? They don’t need any help. The second interesting property of weighing scale is its ease of access. As a kid I remember how weighing was performed as a ritual at the railway platforms every time we traveled by a local train in Mumbai. Anyone who is interested in weighing can find one – either free or at a low cost. The third property is very special and perhaps not understood by most as unique. Weighing scale is emotion-proof. It gives the same weight no matter how angry or anxious you are. Contrast this with blood pressure machine, voting machine and stock price – all are anxiety dependent.

Combination of the first two properties, simplicity & ease of access, creates what is sometimes called a self-test. It is like saying, “Go check it yourself”. Kahneman observes in “Thinking, fast & slow” that embedding “self-test” in the research papers helped he & his co-author Amos Tversky reach out to a wider audience outside psychology fraternity. Authors Chip & Dan Heath mention in “Made to stick” that self-test is a powerful way to build credibility for your idea. An ECG or an MRI scan are not self-tests. Neither can you do it yourself (yet), nor can you diagnose the results.

Designing a measurement system that has a self-test and is emotion-proof is like creating a “weighing scale”. At the very least, you are generating an intelligent gossip. When I wrote about a simple innovation dashboard for checking how innovative you are a year and a half ago, I was trying to create a “weighing scale”. Contrast this with a perceptual survey which is based on questions like “Do you feel the environment in your company is conducive for innovation?” etc. It is neither self-testable nor emotion-proof. I don’t mean to say that these kinds of surveys are not useful. It is just that they are not “weighing scale” like and hence may not lead to intelligent gossip.

In the spring of 1884, Thomas Edison supervised 2,774 lamp experiments at Menlo Park. In 2010, Google engineers performed 20,000 experiments to improve the search algorithm and took 500 ideas live. Won’t it help to build a richer vocabulary of this kind and in fact, generate intelligent gossip from it? I believe it can be a first step in building a culture of innovation.

Related articles:

Innovation dashboard: 4 indicators of idea velocity

Innovation pipeline: a popular lead indicator metric on innovation