Friday, April 29, 2022

What does Ramana Maharshi mean by “All sciences end in the Self”?

Talks with Sri Ramana Maharshi” has been my reflection companion for over two decades. It contains conversations with Ramana Maharshi (RM) (1879-1950), a spiritual teacher known for his emphasis on self-inquiry. The conversations in this book took place between 1935 and 1939 in RM’s ashram in Tiruvannamalai in South India and were recorded by one of the then residents of the ashram, Munagala Venkataramiah.

In one of the conversations with a visitor in 1937 (Talk 380), RM said, “All sciences end in the Self”.  What did RM mean by this? Science continues to unravel so many mysteries including the mystery surrounding the concept of self. Isn’t it an important path towards understanding reality and one’s own nature? Did RM underestimate the power of science? This is an attempt to explore these questions.

Let’s begin with an excerpt from Talk 380 where this quote appears. The visitor had come from Europe and most likely there would have been a translator.

V: I want confirmation of the Self.

RM: You seek the confirmation from others. Each one though addressed as ‘you’, styles himself ‘I’. The confirmation is only from ‘I’. There is no ‘you’ at all. All are comprised in ‘I’. The other can be known only when the Self is posited. The others do not exist without the subject.

V: Again, this is nothing new. When I was with Sir C. V. Raman he told me that the theory of smell could be explained from his theory of light. Smell need no longer be explained in terms of chemistry. Now, there is something new; it is progress. That is what I mean, when I say that there is nothing new in all the statements I hear now.

RM: ‘I’ is never new. It is eternally the same.

V: Do you mean to say that there is no progress?

RM: Progress is perceived by the outgoing mind. Everything is still when the mind is introverted and the Self is sought.

V: The Sciences - what becomes of them?

RM: They all end in the Self. The Self is their finality

Let’s note that “the Self” is a translation of the Sanskrit word Swarupa which could also be translated as “one’s nature” or essence. 

How ignorant was RM about sciences? In the same book where the above-mentioned conversation happens, there are a couple of places where RM refers to science. “Even the material sciences trace the origin of the universe to some one primordial matter - subtle, exceedingly subtle.” (Talk 199) And, another one, “There is no difference between matter and spirit. Modern science admits that all matter is energy.” (Talk 268) This implies that RM had probably heard of the implications of the special theory of relativity and the brand-new branch of quantum mechanics. Looks like he was not totally ignorant.

Then where does this confidence of “All sciences end in the Self” come from? Let’s look at one more elaboration of RM on this topic (Talk 388):

“There are no objects without the subject, i.e., the objects do not come and tell you that they are, but it is you who says that there are the objects. The objects are therefore what the seer makes of them. They have no existence independent of the subject. Find out what you are and then you understand what the world is.”

Empirical evidence is an important aspect of the scientific method. Scientific theories predict future observations for a given context. This implies the separation of observer and observed. Is observer independent of observed? What if the observer is the observed? It could be like one hand observing the other hand – having some relative independence but ultimately part of one whole. Perhaps what RM is trying to say is that science has relevance when the subject considers itself to be independent of the object and loses its relevance when the sense of separateness vanishes.   

And even if a branch of science (e.g. quantum mechanics, statistical mechanics, neuroscience) is telling that observer and observed are not independent, RM feels that having the mere knowledge is not the same as internalizing that knowledge. A scientist may champion a monistic theory and yet feel frustrated or get depressed because fellow scientists are not paying attention to his theory. RM brings it out in the following Q&A from Talk 27.

Q: Is the study of science, psychology, physiology, philosophy, etc. helpful for (1) this art of yoga-liberation. (2) the intuitive grasp of the unity of the Real?

RM: Very little. Some knowledge is needed for yoga and it may be found in books. But practical application is the thing needed, and personal example, personal touch and personal instructions are the most helpful aids. As for the other, a person may laboriously convince himself of the truth to be intuited, i.e., its function and nature, but the actual intuition is akin to feeling and requires practice and personal contact. Mere book learning is not of any great use. After realisation all intellectual loads are useless burdens and are thrown overboard as jetsam. Jettisoning the ego is necessary and natural.

This is like the difference between cycling and cycology. One may know the theory behind how a cycle works and how a cyclist balances his weight and yet may not know cycling. Cycling is a full-body knowledge also called embodied cognition and it is mostly implicit. Similarly, knowing that the self is not independent of and intimately connected with the outside world is not enough. It needs to be embodied and internalized to be effective.  

One implication of what RM is saying is that reading this blog itself is of very little use. Turning attention inwards, watching the movement of thought, and exploring the origin of I-thought is more important. RM says, “Change your outlook. Look within. Find the Self. Who is the substratum of the subject and the object? Find it and all problems are solved.” (Talk 331)

Related blog:

Ramana Maharshi’s self-inquiry through Upadesa Saram verses, Dec 2021.

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Wednesday, April 20, 2022

Is “8 steps to innovation” still relevant in the digital era?

It has been nine years since the publication of our book “8 steps to innovation: going from jugaad to excellence”. In a fast-paced world where technology becomes obsolete every two-three years, nine years is a long time. My co-author Prof. Rishikesha Krishnan has been nudging me and suggesting that we should re-look at the framework, especially in the context of the digital era. Is the framework still relevant? Here is an attempt to sketch some initial thoughts on this topic. The attempt is clearly biased and criticism is more than welcome.

Relevance of pipeline-velocity-batting average:  The framework addresses the question, “How to become more innovative systematically irrespective of strategy, size, sector, and culture?” This question is more relevant for organizations and teams and less relevant for individuals. The framework divides the main question into three sub-questions: How to build an idea pipeline? How to improve idea velocity? And how to enhance batting average? The pipeline problem addresses the generation of a constant stream of business-relevant ideas. Velocity problem explores validation of various assumptions associated with the ideas and finding relevant resources including investors for the promising ideas. Batting average problem looks at increasing the chance of success for big bets while building a margin of safety. 

Are pipeline, velocity, and batting average problems still relevant in the digital era? I have been presenting these sub-questions to MBA students and corporate executives. And nobody has questioned the relevance of any of these sub-questions. These questions were relevant when Thomas Edison was running his invention factory more than a hundred years ago and are relevant for the innovation engine at Mahindra today. Even a corner grocery shop if it plans to do systematic innovation would have to address these questions. So then, what has changed?

The eight steps are responses to these three questions. First three steps address the pipeline problem, the next three steps address the velocity problem, and the final two address the batting average problem. Let’s see how the relevance of each step changes in the digital era.

Pipeline problem: (Step-1, 2, 3)

Step-1: Laying the foundation: This step involves setting up the core processes like idea management process, buzz creation process, and learning and development process. It also involves establishing clarity on the scope, source, and sponsorship of innovations. I feel these things are not affected in the digital era. Any organization that is serious about innovation has these in place in some form or the other.

Step-2: Create a challenge book: This step emphasizes the creation of a challenge book and establishing collective clarity around it. The digital era has created new metaphors like Uber (marketplace), Tesla (EV, semi-autonomous, over the air upgrades), Zomato (home delivery), Amazon (shopping convenience), Paytm (mobile wallets), etc. In the past few years, we have seen new waves like the pandemic, sustainability-related regulatory norms, electric vehicles, cryptocurrency, machine learning, etc. gaining momentum. All these metaphors and waves contribute to building a challenge book. However, in my opinion, the relevance of challenge book doesn’t go away. In fact, it becomes more relevant because in a world of ever-increasing distractions, challenge book can bring focus to the innovation efforts.

Step-3: Build participation: This step assumes that navigating complex challenges may benefit from participation, the way it happens in a café or a conference. The assumption remains relevant in the digital era. However, the digital era highlights the importance of the customer experience dimension.  With steps like search, discovery, comparison, selection, payment, delivery, and returns associated with online shopping, end-to-end experience has become increasingly important. Moreover, this cuts across the shopping of products like mobile phones, grocery items, and services like blood testing and banking. Hence, a methodology like design thinking which puts experience design at its center and weaves empathy, participative problem solving, and experimentation in an iterative manner has gained significance.

Velocity problem: (Step-4, 5, 6)

Step-4: Experiment at low-cost with high speed: The digital era has seen the emergence of new tools – computational modeling tools, simulators, 3D-printers, etc. Many of these tools are now available on cloud making them easily accessible at low-cost. They are helping idea authors test their ideas or at least some assumptions associated with their ideas with less cost and at high speed. For consumer-facing digital applications, A/B testing – a form of randomized controlled experimentation – has become an important mechanism for testing ideas. No matter what the technology or tools, the relevance of low-cost high-speed experimentation hasn’t diminished over the years.

 Step-5: Find a champion: This step is based on the assumption – An idea either finds a champion or dies. Is the assumption still valid? Very much. Finding a strategic customer who endorses the idea or an investor who supports the development of the idea continues to be important today. Social media has helped ideas authors find champions by publicizing their idea through videos. Programs like Shark Tank are creating platforms for start-ups to find investors and/or mentors.

Step-6: Iterate on the business model: As the relevance of data increased, so did the importance of business models that leverage data. Dental insurance company Bento partnered with Philips which manufactures electric toothbrushes. This is because having the data on how many times a person brushes his teeth would help determine his dental insurance. EV companies like Ather Energy began to unbundle their product offering and started selling batteries separately as a subscription. Banks began to offer Buy-Now-Pay-Later (BNPL) payment option as an alternative to credit cards. Business model innovation continues to be an important lever for digital businesses.

Batting average problem: (step-7, 8)

Step-7: Build an innovation sandbox: Exploring big bets is inevitable for any company that is serious about survival. Google explores self-driving cars, Amazon experiments with Just-walk-out stores, and Facebook bets big on virtual/augmented reality. Small firms may have to consider automation and analytics seriously. The challenge is you can’t bet on all the big trends, you will have to choose. And even after choosing a trend, you may not know how this trend may lead to a new offering. You need to identify a few use-cases, invest in building experimentation infrastructure, and perform a large set of experiments to see what is both meaningful in your context and promising enough. In short, you need to build an innovation sandbox, unless you choose to acquire the innovation. Building an innovation sandbox is neither low-cost nor a short-term project. Technology platforms may speed up the process and open innovation may help in connecting ideas from remote corners of the world.  I haven’t seen its relevance diminished.

Step-8: Build a margin of safety: Big bets bring risky exposures. You can’t have one and not the other. Datacenter outages are a given once you adopt the cloud. If you are a bank and if you don’t worry about managing data center outages you will be in trouble sooner or later. HDFC Bank learned it the hard way. Shakespeare knew that a pound of flesh is a risky promise for the Merchant of Venice. And V G Siddhartha, the founder of Café Coffee Day was expected to know how much debt is enough. This step – building a margin of safety – could very well be the most challenging step to internalize. And it is evergreen.

In short, from my biased perspective, the core problems raised in the book – pipeline, velocity, and batting average are still relevant in the digital era. And 8-step responses are relevant too. However, your input is welcome and it is possible that I am missing something here.