Top 10 of Sweet Sixteen Welcomes 2017

Sweet Sixteen – The Year In Review

An old Danish proverb points out that “it is difficult to make predictions, especially about the future”. Similarly, if we have to look ahead to our New Year Resolutions and the Top 10 Trends for 2017, let us not try and predict the future but instead look back and learn from the Top 10 themes that have been playing out in 2016 aka Sweet Sixteen.

Time seems to be flowing much faster these days and “Sweet Sixteen” flew past more rapidly. The last few days are always a good opportunity to reflect on the year and current trends and plan ahead for the coming year.

It has been a memorable and action packed year for me. As I reflect on the past, a train of connecting thoughts are running through my mind. I have connected the dots of 2016 in the form of a Top 10 list to derive some lessons to thrive in the coming year, amidst a slew of global uncertainties. I hope there are some takeaways for each of you, as you welcome the New Year!

#1 – Child is Father of the Man

I started Review 2016 recounting a few interactions and memorable moments with my children turned 12 and 9 respectively, that reminded me of William Wordsworth’s immortal words “Child is Father of the Man”.

Children have an innate curiosity and creativity that we probably lost somewhere in the past. We all can immensely benefit from connecting with our own childhood experiences and re-igniting the creative spark. Some of my interactions with my children have helped me discover new possibilities, that I would have certainly not done alone.

The key to the future lies with the next generation. Children hold tremendous predictive power to illustrate what the future holds in store for us. Hence, even for planning the years ahead, we need to connect with the millennials, to better appreciate the changing dynamics.

#2 – Student Community

Let us graduate, figuratively and literally from children to college students. I was lucky during the year to interact with a diverse set of students including management aspirants, engineering students and budding lawyers in a variety of settings.

The unifying factor is that universities do a remarkably miserable job of preparing students for the real world. We must do something to bring about a change, even if it is a drop in the ocean.

As part of my little contribution, we helped in devising and running a contest for college students in association with Careers360 that was designed to mimic the real world requirements. The contest tested the ability to engage and exert influence on their peers, followed by a contemporary test of creativity. This was followed by the contestants writing researched articles on modern themes such as drones, artificial intelligence and geospatial issues. The grand finale included an online debate on Facebook, much in line with the trends of online professional interaction.

I shared some of my experiences and learnings for the benefit of students graduating from the academic world to the real world. Some of these lessons are also applicable to working professionals, especially in the context of a turbulent world order.

One of the key aspects that I have emphasised in my interactions is the importance of continuous learning. My favourite self-coined word has been autodidactual, a morphed form of autodidact.

#3 – Enter the Autodidact

Enter the Autodidact; but what exactly is the meaning of an autodidact?

In the simplest terms, it is a self-taught person, who treads the path of continuous learning, assimilating an ocean of diverse knowledge.

The importance of continuous skill and knowledge upgrades is at a peak as we are living in a VUCA world that is volatile, uncertain, complex and ambiguous. Our knowledge and skills have been shaped by a redundant educational system that is rooted in the anachronistic Industrial Age.

Consequently, we have witnessed a massive spike in the availability of online resources for learning. There is no dearth of platforms for learning new skills and broadening one’s horizons including YouTube (yes, even if you didn’t see it as a platform for knowledge acquisition) and TED. However, the most promising over the last few years have been MOOCs (Massive Open Online Courses) hosted on platforms such as Coursera and EdX by leading universities including Harvard and Stanford and of course the popular Khan Academy.

Following the adage “Practice what you preach”, I have helped build a strong learning culture in my workplace. The range of skills that we have acquired in the last couple of years makes for a very interesting list covering a wide array of hard and soft skills.

Keeping oneself abreast with the latest skills and know-how is mandatory in today’s environment, where rapid change is the norm. If you refuse to use any software or app that has not seen a version upgrade in the recent past, why would the world see your package of skills any differently? It is indeed time for the Rise of the Autodidacts to thrive in the times of disruptive innovation.

#4 – Disruptive Innovation

Disruptive innovation is continuously re-shaping the contours of several industries as we speak. Industries that have already got disrupted are bracing for subsequent shake-ups.

We need a three-pronged approach to thrive in this environment – need to innovate; risk mitigation to combat the impact of other disruptive innovations and market intelligence to understand the innovation landscape.

Our efforts to leverage digital learning, have been a great example that spawned several innovations and helped minimize the potential risks of disruptive innovations in the industry. I was privileged to attend an event hosted by Financial Times in Hong Kong, where our firm was the only Asia-headquartered firm to be recognized for Innovation using Technology for our Digital Learning program.

The event and the report also provided an interesting insight into the state of the innovation landscape. I applied my newly acquired Artificial Intelligence (AI) and Natural Language Processing (NLP) skills to create “KnowBot”. The Top 10 Innovation Trends were uncovered by KnowBot, based on the Financial Times report mentioned above. These provide a great starting point with key themes including Technology, Structures and Networks, innovative Management practices and Analytics.

#5 – Analytics

One of the key drivers of change in the world around us has been the massive information explosion. In this backdrop, the practice of Analytics has gained prominence. Three factors have contributed significantly to the advances in Analytics and Big Data. These are enhanced information availability; increased computing power and ability to process non-numeric data.

However, we sometimes get enamoured by trends and buzzwords and can’t see the woods for the trees. In this context, I have been a vociferous advocate of Value. Last year, I had modified the popular 3V’s framework of Big Data (Volume, Velocity and Variety) to create the 7V’s of Big Data. The concept has been kept alive through my newsletter as I try and direct attention to Big V of Big Data – Big Value.

Our continuous efforts to “embrace Analytics across all practices and functions to change behaviour” and extract value have been recognized across platforms. On the heels of an award for Big Data / Analytics by Dataquest last year, we were commended by Financial Times (FT) this year. Ours was the only instance of an Analytics related initiative by an Asian firm recognized in the “Business of Law” section of the FT report.

#6 – Artificial Intelligence

Analytics, as a term, has started getting edged out by the broader field of Artificial Intelligence (AI) and it’s constituents including Machine Learning, Deep Learning, Neural Networks, Data Science and other buzzing keywords.

The buzz has been getting louder each year and according to the Gartner Hype Cycle 2016, Machine Learning is at the “Peak of Inflated Expectations”. The discovery of value and the ‘plateau of productivity’ will take a few years.

Almost all emerging technologies and buzzing keywords have been following this pattern. Big Data is a case in point, where the discussions have now matured from discovery of enigmatic buzzwords to value extraction. A LinkedIn article I wrote on “Value of Big Data” in June ’15 witnessed more views in the last two quarters than in the first nine months since publishing. This is consistent with many annual reviews on Big Data with value extraction as the key theme for the year.

The same thing is likely to happen with Machine Learning and Artificial Intelligence in the near future. The transition of the discourse from describing an enigmatic phenomenon to a mature field with value derived from mainstream adoption is likely to happen over a period of time.

In this context, I am delighted that I embarked on my autodidactual journey of Machine Learning last year, carefully separating the real from the “Artificial”. Starting as an awe-struck AI novice over a year ago, I extended my Analytics repertoire to Machine Learning. In the latter half of the year, I even found myself conducting sessions on AI, explaining concepts and showcasing projects that I had implemented.

The following four patterns emerge from my experiences and experiments with Artificial Intelligence:

• Diverse Application – I found that Machine Learning applications including clustering, segmentation and predictive analytics found use across almost all functional areas. I had implemented use cases in the fields of Finance, CRM, Human Resources, Operations and Knowledge Management in addition to my adventures with predicting short term stock market movements.
• Scale – The most remarkable learning was that one does not need massive infrastructure to implement these techniques. You do not need to be an Amazon or Netflix or Google or IBM Watson to solve problems using AI. A lot of work has been done to enable these algorithms to work on medium scale data and even on standalone machines. This is not what a plain reading of developments in the AI world seems to indicate to the layman.
• Simple – Most of the experts on this subject appear to be PhDs in Computer Science. The underlying statistical wizardry involved in the algorithms is humongous and sometimes resides in black boxes. However, the root logic involved is often fairly simple and can be traced back to basic concepts such as conditional probability. The sheer magnitude of the volume obfuscates our thinking and adds a layer of perceived complexity and a cloud of enigma.
• Text – Most of the information that resides in the world today is not in structured quantitative format but rather in the form of unstructured text. There is tremendous potential to unlock value by mining text. Off the shelf tools are available for word processing but unfortunately not for text analytics.

This leads us to the next section on Text Analytics, that can be performed using a combination of Natural Language Processing (NLP) and Artificial Intelligence.

#7 – Processing Text

In the quest for Value extraction from data, one of the striking factors is that more than 80% of the world’s information resides in unconventional formats. The bulk of the data is in text or formats that are neither quantitative nor structured. Traditionally, off the shelf tools have not been available for processing such data.

If we have tools to add and subtract numbers, then why don’t we have an equivalent for language processing? Why don’t we have tools to conduct even basic mathematical and algebraic operations with words, such as addition and subtraction? After all, words convey a lot more to the average human being than numbers.

Thankfully, these questions have been bothering a lot of smart people who decided to do something about this gap. One of my “aha moments” this year has been the discovery of advances made in the field of Natural Language Processing. Thanks to the advances, capabilities such as word algebra are now available to us.

I have been experimenting with text analytics during the year across several use cases. However, there was one particular instance of text analytics that was rather illuminating.

As part of our internship contest, candidates submitted articles that were evaluated by our team of professionals. However, I also engaged our custom built KnowBot on the job to segregate the articles into three clusters, powered with Natural Language Processing (NLP) and Machine Learning (ML) capabilities. There was a very significant correlation between the scores assigned to the articles by the human evaluation process and the clusters created (independently) by KnowBot. The possibility that there is a pattern in the subjective human evaluation that can be deciphered by an algorithm dawned upon us.

We took a bolder step in the evaluation of the subsequent online debate on Facebook and incorporated KnowBot’s scores in the final decision on the winning candidates!

However, the journey has not been smooth for the field of text analytics. Even Google had extensive debates on the risks of machines taking over refining of search algorithms before increasing the adoption of NLP and ML techniques.

The key takeaway is that the world presents interesting new capabilities of processing something as ubiquitous as raw text. We have deep seated neural associations with how text is to be processed. These beliefs largely revolve around the concept of an ‘understanding’ of language with its ambiguity and idiosyncrasies that cannot be condensed into rules.

However, a change in circumstances calls for a change in beliefs, practices and habits. Machines and bots powered by artificial intelligence are staking claims to domains that were once exclusive to the humans. This is true not only in the field of language processing but also in the world of machines that have traditionally only been controlled by humans but are now developing a mind of their own.

#8 – Robotics

A combination of advances in mechanical and computational sciences has led to a revolution in the field of IoT (Internet of Things) and Robotics. Although I am not qualified to speak on either of the two, but I did dabble around enough with the latter to share my personal experiences and provide my perspective.

I started with “Child is Father of the Man” and most of my experiences in Robotics are in my capacity as observer and assistant to my 12 year old son. I was stunned when he declared few years ago that he wanted to do something that combines mechanical engineering with computer programming aka Robotics.

The journey since then has been exciting, in different ways, both for him and for me. We have been playing around on different platforms such as Raspberry Pi and Arduino with a wide variety of sensors and motors.

Our creativity has manifested in building toy equivalents of weather monitors, intrusion detection systems and autonomous vehicles. My son even contemplated completing one of his summer assignments that involved maintaining a record of traffic conditions by creating a robot with motion detecting sensors.

You may find this intriguing, given my son’s age and my non-geeky Commerce background with exposure to the C family and Python only after turning 40.

However, the icing on the cake is that he finds it relatively simple. In fact, in a session that I conducted on Artificial Intelligence, I showed a video of a self-maneuvering vehicle that my son had created. The audience was surprised that this was made by a 12 year old. However, I went about deconstructing the robot by diagrammatically breaking it up into Input, Process and Output. This resonated with most people of our generation, since this is how we had defined computers.

The future will look very different very quickly if pre-teens are doing this kind of stuff. It is certainly not surprising that the world is reverberating with stories of disruptive innovation triggered by start-ups that have been founded by millennials.

#9 – Startups

How can an annual review that has spoken about disruptive innovation, analytics, Big Data, Artificial Intelligence, Machine Learning and Robotics not talk about startups?

The startup ecosystem is undoubtedly the most vibrant, pulsating with excitement, energy and new ideas. However, this ecosystem is also subject to the perils of becoming a trendy buzzword that we saw in the case of Big Data, Machine Learning and AI.

Most media reports a couple of years back spoke about enormous valuations, huge rounds of funding and astronomical salaries in the startup ecosystem. At pretty much the peak of the euphoria last year, I spoke a few times on the Startup ecosystem at various platforms. One of the sessions at IIMnetWORK, captured in a Short and Tweet Story, illustrated how the interests of investors needs to align with the passion of the entrepreneur.

This year started with a bang with the slogan of StartUp India accompanied by policy announcements in January. Not even six months down the line, I found myself in a panel that was critically analyzing the effectiveness of the startup policies. Several annual reviews appearing in social media are providing a who’s who list of startups shutting shop this year.

Do you see the consistency of the emerging patterns as I do?

The froth is always temporary and it takes some time for the real substance to identify itself. Stories built on a foundation ignoring the basic building blocks will fall flat. It is not rocket science and it is not artificial (intelligence), it is age old common sense.

The foolproof approach is to eliminate all layers of complexity and strip down to the basics. Once you pay attention to the fundamentals, value will not be elusive any more.

#10 – Valuation

And now for the final theme that has been recurring right through and will always remain key – Value !

The concepts of value have remained unchanged for generations. However, the nature of underlying assets keeps changing in line with the current economic realities. The basic financial building blocks of enterprise valuation are cash flows, growth and risk.

Necessity is the mother of invention and various methods of valuation for start-ups have cropped up over the years. All these methods substitute the lack of predictable numbers with some rules of thumb to obviate the need for the key metrics. However, the valuation parameters of a business have to converge to conventional parameters over a period of time, as the business matures and revenue models stabilize.

In addition to start-up valuation, I did get the opportunity to address another equally esoteric segment – brand valuation. In the backdrop of the Prime Ministers of UK and India signing a MOU on Intellectual Property Rights, we hosted a seminar on ‘Brand Management – Protection and Valuation’ in collaboration with UK IPO.

I moderated an interesting session on valuation of brands with representations from brand owners, finance professionals, lawyers and marketing in the panel discussion. The diversity of the group elucidated the need for synthesis across disciplines. We no longer can live in a world of islands and silos. Collaboration will Trump anyday and islands wanting to remain in a silo will continue to exit (references to key events in 2016 purely co-incidental).

I can only hope that my experiences have sparked some thoughts to make your plans for the coming year. And last but not the least, hope you are able to extract value out of your efforts and that value does not get de-monetized!

Welcome 2017 – Seizing the Opportunity

I hope you enjoyed reading through the roller coaster journey of the past year. More importantly, hope you find some elements to help pivot your plans.

Sweet Sixteen taught us that uncertainty is the greatest certainty of our times. In the context of planning for the next year in such times, I cannot but remember Shakespeare’s words:

There is a tide in the affairs of men.

Which, taken at the flood, leads on to fortune;

Omitted, all the voyage of their life

Is bound in shallows and in miseries.

On such a full sea are we now afloat,

And we must take the current when it serves,

Or lose our ventures.

Wish you good luck for making the best of the tide in 2017 !