Do You see What You get?

An ancient Sanskrit proverb says “ Yat Bhavam Tat Bhavati” which means ‘ As you think , so you become!’. Lets look at how this applies in everyday life.

Did you know that a sculptor sees the statue BEFORE he even makes the very first strike on the stone?

Lets start with a simple one. If you are playing a ball game say Tennis, you need to first see where the ball is going to land , BEFORE you play/place the ball there. Unless you see the ball there BEFORE it lands there, you cannot plan your stroke to ensure the ball lands at the exact spot.

Now lets say you are building a product. Unless you see what the product will be 5 years hence, you cannot take actions today in that direction. Granted you cannot see what the world will be 5 years hence but you can certainly imagine what your own product would be.

Thanks to Private Equity /Venture capital deals, many enterpreneurs are able to see beyond a quarter ( many in fact) and make moves that may deliver in the long term and not just the current year. Visionaries like Elon Musk and Jeff Bezos are commanding outsized valuations not because of their current profit numbers but their longer term view and moves. When the Paytm founder says he wants to make it in the United States, he is not just looking for market expansion. He is envisioning something very long.

You can no longer hide behind quarterly results to refuse to see the view beyond. In everything that you do today, imagine what would it be 5 years hence. Do not stop with the dreaming. Take actions ( atleast some ) which help you steer along that vision.

Like the Sanskrit proverb says, it will surely happen!

Your margin is my opportunity

I am sure you heard this famous quote from Jeff Bezos. What is actionable from this insight?

1. Look at segments that have a wide spread mediocre offerings , that have not evolved much.
2. Look at segments that do not have wider choice for customers. Customers need to choose between 2/3 options and even those are not really options. Remember the limited options might have come about from a string of acquisitions or the segment attribute itself.
3. Look at segments whose players’ margins do not come down even when new entrants come in. Why does this happen? Either the new entrants are not radical enough or do not attack the fundamentals
4. Look at segments which have a number of intermediaries and each takes a cut in the value chain . Also look at value each intermediary adds in the value chain.
5. Look at markets that have traditionally been low on innovation.

These segments will inevitably be attacked from unknown quarters,sooner than you think!

Valley and the Main Street

 Since the unicorns have started killing industry categories, every firm wants to emulate Silicon Valley firms or want to look like one. The differences are too many.

1. Business Model : The Valley models are non linear, asset light, digital natives and cloud first. Risk taking and Pivoting come naturally to them. Growth and customer acquisition first and Profit later. Main Street firms have linear business models, legacy resisting change, Profit first and growth next and technology baggage.
2. Skill Base : Domain skills are more critical in the Main street and technology supports domain. Its the reverse in the Valley. Pivoting related re-skilling is easier.
3. Funding : As most are venture funded in the valley, the accountability is to a smaller set of investors and do not have the quarterly results /disclosure/regulatory compliance pressure as the Mainstreet firms do.
4. Hype curve: As both these are at different points of hype curve, the problems both of them solve are quite different. Some of the challenges that Valley firms fight on, the Mainstreet is not seeing anytime soon.
5. Resistance : Resistance to change for Main street firms comes from employees, industry stakeholders, regulators, channels. Valley firms are able to quickly get off the ground since they are not seen as a threat until its too late.

Its not all roses on either side. Valley firms seem to be poor on fiscal prudence, focus and business acumen while the Mainstreet firms seem to be poor at seeing anything beyond a few quarters , ability to attract tech talent and slow.

Why does all this matter?

You need to consider all the above factors depending on which side you are playing.

Fail More

Reinforcement learning is one of the critical components of machine learning algorithms today. Every right prediction/action is rewarded, every wrong prediction/action is punished. Each reward/punishment tells the algorithm what behavior to repeat and what to stop. Over time , the algorithm works to maximise rewards.

What is critical here? In most situations, there are more wrong answers than right answers. There are more wrong steps and very few /or a single right step. What is key for the algorithm to learn fast? Fail more.

The more wrongs that you avoid ( based on past learning) , the closer you are to the right answer. While you might chance upon the right answer very quickly, the learning happens by finding the wrong ones and avoiding them in future.

Yet this behavior that is so intrinsic to us early in our childhood elludes us later in life. We try to look/plan /be prepared for 100% success at the first attempt . We are woefully unprepared for any other result. Failed project owners are crucified/vilified/taunted. Failed project teams try to hide under the table/ act as if they have committed a crime.

Without the wrong actions, there is no learning ( as we have seen from the reinforcement learning ). Instead of celebrating learning, we are forever scared of failures/ do not prepare for failures. What is worse is that we do not want to start a project if we are not 200% sure it will work.

While such conservatism worked in the past, it may not work now as every industry/business is getting disrupted from unkown quarters. ‘Fail Fast’ is not a buzzword and certainly not an optional!

Easier to Simpler

The next wave of growth will be from making complex things simple. Making simple things easier is done and dusted.

The explosive growth of telecom and internet have enabled the first set of apps to make the simple things easier. Ordering groceries, hailing a cab , booking a hotel room, buying a flight ticket…

Current generation of unicorns have done and dusted all these ideas. It’s time to leverage the new age technologies to simplify the complex. Leveraging technologies such as deep learning, blockchain, Quantum computing to simplify complex problems and make them as easy as making a request to Siri/ Alexa or touching your phone will give rise to next generation of unicorns.

This is easier said than done. It needs a wider different set of skills than before. Deep domain knowledge ,out of box thinking and risk taking, tackling the resistance of the incumbents' well financed self interests…

On the flip side returns are enormous. Unlike b2c platforms, B2B decision making is not strictly by the price and that enables for more profit making platforms from day 1 instead of ‘ buying the market ‘ at huge losses .

The complexities involved ,the value propositions, stakeholders for all quite different. So are the returns!

Half of Plan B and full Plan C

In most projects, Plan A never works.

What works is half of Plan B and full Plan C.

That's it.

Half of Plan B and full Plan C

For most projects, Plan A never works.

What works is half of Plan B and full Plan C.

That's it.