About Unicorns And Related Things

Monday morning brings with it a post laying out the new ‘strangeness’ in the universe of the Indian unicorns by my former boss, Haresh Chawla. Some of the points, especially the one on doing due diligence, are ones that have bothered me for a while. I mean, even as an outsider, without access to the P&L statements of the companies it is not too difficult to mock up a hypothetical model of the business the investors are putting money into. So, why is it that the landscape seems to be littered with what seems to be strange moves by all parts of the ecosystem, unicorn or otherwise?

Be warned, what is to follow is a mix of personal experience, anecdotal information and lots of conjecture.

The crux of my argument is based on the factors that play an important role in the India story.

Execution

This is the ability of a team, enabled with capital, to execute a product/platform. It means that things work as advertised, as a norm. Whatever does not work is quickly fixed and the state of the system is such that edge-cases are minimal.

In some markets, this ability is determined by the team’s chops at quickly setting up a product operations, in other markets, it means primarily how enabled is the team towards closing key alliances, leads and relationships. In India this factor is particularly important because who you know can make a significant difference in being able to close a deal than the outright finesse of the product of the state of the finances of the start-up.

Market Size Validation

The truly gifted salesman can sell an ice cream to an Eskimo, but not even the most gifted salesman cannot build a big business selling ice creams to Eskimos. Every early-stage business and market makes assumptions about the size of the market it is selling to. The gap between starting a business and the business hitting escape velocity is often marked by the time spent in validating the market size and the long-term margins that can be accrued in selling to that market.

Market Growth Potential

Some markets start small, but given the right conditions, it can grow into substantial ones. A classic case of this is mobiles in India. 15-years-ago, this is a market that barely existed. Today, it is a multi-billion dollar industry. Given the right conditions, can a market grow like this?

Path To Opening Up Market

A market that is large enough or one that has enough potential to grow a lot alone does not mean that you can open up that market. Some will require a lot of capital to acquire users (deep discounting and CoD that did this for Indian e-commerce), others will require regulatory roadblocks to be lifted. There are various paths to getting this done, some are feasible, others are not.

Ease Of Access To Capital

Every business needs money to run and most early stage businesses will always spend more than what they earn. Which means that they need money in the bank to cover for expenses till the tide turns and they can turn at least cashflow positive. Easy access to capital means a lot of undeserving ideas/companies will also get funded, but a lack of it means a lot of good ideas/companies will never get funded.

Operational Efficiency

Operational metrics is key to measuring the health of a company. A company that does not manage to make at least a couple of operational metrics more efficient as the years go by is a big stonking red flag that everyone needs to take notice of.  If you keep needing more and more to do less and less and at some stage the ability to acquire the more is going to run out.

Capital Efficiency

This one is self-explanatory and the classic “how much do you make on your dollar?” question.

Exits, M&A

Investors and founders (especially the former), need an eventual big payday for all the risk and effort they have put into the start-up. A healthy ecosystem needs a regular supply of exits (through IPOs, M&A) for the payoff and also to correct over-leveraged players. Not all exits are of the sexy kind, where founders and investors make lots of money. But even fire sales are necessary to let the early risk takers cap losses. An ecosystem where exits are far and few in-between will struggle to sustain itself in the long run.


The Indian ecosystem, seen through the prism of the above factors, has gone through two cycles so far. For the sake of convenience I will ignore the smaller cycles (the 2008 meltdown, for instance).

 The First Stage (1997 – 2005)

  • Execution was terrible
  • Market size unknown
  • Market growth abysmal
  • Path to opening up market unknown
  • Lack of easy growth capital
  • Operationally inefficient
  • Capital inefficient
  • Unit Economics Is Bad
  • Very few exits, M&A

The Second Stage (2005 – 2015)

  • Execution has improved significantly
  • Market size has been validated
  • Market growth has picked up
  • Path to opening up market is known
  • Plenty of easy growth capital
  • Operational inefficiencies have skyrocketed
  • Capital inefficiency has skyrocketed
  • Unit economics has worsened
  • Exits and M&A has picked up

The key to unlocking the value in the Indian ecosystem is to get all the points to go green. We have improved significantly in execution, validating the size of the market and figuring out how to open up that market. But the two key factors — of improving operational and capital efficiency — are key to the long term well-being of the ecosystem and we are far from being able to crack open those two fronts. It is imperative that we figure out how to do that in the next stage at least.

Through 2015, I had the opportunity to see up close some of the e-commerce operations struggle with extreme inefficiencies. These operations can easily improve margins significantly if they can reduce inefficiencies. But that is easier said than done.

Some of the reasons behind the inefficiencies:

A System That Monetizes Inefficiency

Our famous ‘jugaad’ system ensures that people who can navigate around that can quickly acquire wealth and a significant number of people benefit from the existence of that inefficiency. A component of an ecosystem that brings itself into play in the ecosystem because of its complexity will always strive to increase the complexity in the system as a matter of survival.

Most of the e-commerce companies deal with problems on a daily basis that are in place because of this inefficiency. We have varying tax codes, local laws and levies. Till we get in place an administration that has the political willpower to remove these inefficiencies, it is anyone’s guess when that point in time will arrive when the people who benefit most from the inefficiency will stand to benefit more from an efficient and predictable system.

No Standardization

You would assume that after so many years into the e-commerce revolution in India, there would be a standardized framework of addressing pin codes in India. The funny fact is that there is not one. There are numerous ways of doing this and some of the courier companies even make up their own pin codes. Even where the pin codes are the same, the areas they consider under coverage of a pin code can vary from company to company. There is no standardization on buckets of weights or measurements either.

All this leads to an environment where an apple is not the same apple for everyone. An apple can be various kinds of apples and each shipment of apple takes a conversation with all stakeholders which results in disagreements, disputes etc.

No Experience In Large Scale Retail

The scale of e-commerce possible in India requires prior experience at the scale of what retail is like in North America, where it has been refined to a fine art with decades of experience driving logistics, pricing and marketing. The largest Indian operation on that front, which comes closest is a Big Bazaar, which is tiny compared to the large American retailing operations.

The lack of this experience has resulted in a bonanza for the same sellers across the platforms, while for the customers there is not much in terms of differentiation other than price. Our discounting is also not well thought through, because we don’t understand discounting as well as we should.


All this results in the current strangeness of the Indian unicorn ecosystem. From the investor side, most of the money being put into the market is just what the investors have to put in during each round to stay in the game. There is little to guide them, even in these times, to show what is possibly a good bet. The market is such that someone can easily outspend the top player into a position of dominance as there are really no moats that cannot be overcome with money.

This also leads to the overemphasis on founding teams than pure product in India. A good team in India that can move the wheels faster is always likely to win more than a great product with an inexperienced/not-so-well-connected team.

Understanding Ramp-Up, Burn And Other Key Business Metrics

One of the common mistakes seen in business plans and projections is that entrepreneurs treat various key business metrics as big aggregate numbers. While this approach makes the plan easier to understand (example: addressable market of 3,000 units per year, convert 10% in year 1 at average revenue of 100 per unit), it also glosses over significant complexities involved in acquiring customers, factoring in churn and other factors that play a key role in determining how far the business can go.

While it is true that there is no 100% accurate plan or projection that is possible, it is foolhardy to not make projections that can at least help organizations be prepared for the various scenarios than be caught confused when faced with various eventualities. This post is based on a template that I normally use to model similar things. It is nowhere close to being detailed, nor is the scenario that it portrays a realistic one, but it is one that should give you a good idea how to go about creating your own model. Consider it more a template than a finished model.

ramp_up_table_1

 

Acme Corp Offerings

The table above describes the key offerings of our hypothetical company (Acme Corp). The company has five offerings, of which two are products and three are services. There is no particular reason why this mix is there other than that I wanted a decent spread of offerings. Of the lot, Service C is a big ticket item, which sells the least, while Service A, being the cheapest, sells the most. Again, for the sake of convenience, I’m not taking into account the addressable market for each offering, which is not a smart thing to do, but for now, we have to make do with it. We are also assuming that the company is being started with a 100,000 investment.

ramp_up_table_2

Acme Corp Ramp-Up

The table above shows the ramp-up scenario we have in mind for the company. The cheaper offerings are predicted to grow in a somewhat linear manner, while the expensive ones are erratic in how they grow. We are taking major liberties with factoring in churn here, as we are working backward from the total unit sales for the year than to consider how a customer’s actual lifecycle impacts the system. There are also no volume or pre-payment discounts taken into account, all for the sake of simplicity again.

ramp_up_table_3

Acme Corp Expenditure

The expenditure table is the one that sees the maximum liberties taken with numbers. The dead giveaway is the ‘Average S’ (average salary) figure. In a realistic scenario, it never stays constant over a 12-month period as the headcount grows. Same is the case with rent. There are also a raft of other costs like connectivity, travel, legal etc. that is not taken into account into the picture. Make sure you make those changes and represent them accurately, if this exercise has to be of any real use.

ramp_up

When you plot all those numbers in a graph, what shows up is that the most critical time period for the company is the 6-9 moth period. Even though the organization has its first positive cash flow month in month four, it is only during month six that it starts a streak of positive cash flow months and it is not until month nine that it actually turns in a profit, even though it is a tiny one. For the 12-month period the organization turns in a profit of 17,38,500. But this profit won’t be realized if the company cannot survive beyond the first six months.

This first six months is the period where angel/seed rounds are critical. The cash flow situation for the organization is negative through that time period and even for the extremely cheerful model presented in this post, the company would go under in five months (or less) if it can’t raise anything above 310,000 during that time. The capital raised at this time only allows for basic validation that a market exists for the product/service at the price levels they are being sold at.

Breaking down the ramp-up to this level allows us to estimate which product or service is the one that we should look to grow. A high ticket value service/product has a different sales cycle and support requirements compared to a low ticket value one. What complicates matters is also the fact that these days disruption happens through pricing which mandates larger scale and also considerably lengthen the road to profitability.

To conclude, what I will stress again on is that what is presented in this post is an oversimplified picture, but it does give us an idea about what is a good starting point to do projections and figure out the kind of ramp-up that is required over time to make the organization a sustainable and profitable one.

Building A Digital Product: Part I

There used to be a time when building and launching a digital product was a straight forward affair. The steps were something like this:

  1. Start with a rough idea of what you were looking for
  2. Find someone who could design and build it for you
  3. Find people who would help you run it and go live.
  4. Find ways to market the product.
  5. Find ways to sell the product.

Other than the really big players, most of the regular Joes would handle most of the steps on their own or, in some extreme cases, handle all the steps on their own.

In the last five to eight years the steps have been shred to bits, thrown out to the dustbin and replaced with a set of steps that bear no resemblance to the earlier ones.

Most of this disruption can squarely be blamed on mobile computing. The revolution that started with telephonic devices being able to access bits of textual data (read SMS), was turned on its head when the same devices were transformed into data devices that could also do telephony as one of the many things it could do.

The other significant development that has caused the playbook to be thrown out is the commoditization of many of the moving parts that are used to build a digital product. From databases, to job queues, to logging, to any other part of the technical stack, finds an array of plug-and-play software service platforms that a new product can leverage from day one.

In the early days, teams had to develop everything — from email subscription systems, to delivery systems to, logging infrastructure — to get going. With all these new services, product builders are less builders and more integrators these days.

While this has created an entirely new universe of opportunities and possibilities, it is also responsible for creating a lot of confusion for companies and individuals looking to build products.

What this series will attempt to do, in the first part, is to bring some structure to the steps and elaborate on the steps a bit with an aim to reducing the amount of confusion in the market regarding the steps.

I have no illusions that this will be a definitive list as there are parts of the stack and ecosystem I am completely unaware of. My idea is to fill in the gaps that I can and I’ll be more than happy to bring in suggestions about what else can I cover here.

I am going to tackle the more technical aspects in this post:

Design: Designs are best approached first with storyboards. The story boards are used to create process flows. The process flows lead to wireframes. The wireframes lead to the final design.

You can skip all of the steps and go directly to a design, but the odds are that you will struggle at a later stage to force fit that disciplined a process into an existing system that has grown without it.

What is more important — short term gain or long term pain — make your pick.

Development: The choice of framework/language to build on is made at this stage. Unless you are someone who knows technology very closely, avoid using the latest fancy framework in town.

You have to establish coding standards, documentation standards, bug tracking, version control systems and release management processes.

Testing: Set up both automated and manual tests to address both logic and real-world usage. Testing infrastructure built right will include a good set of unit and behavioural tests and a continuous integration framework that will catch most errors during the build phase itself.

Deployment: No (S)FTP. Simple. Deployment options are available these days from the simple, to the ridiculously complicated. It gets harder when you have to update code on a pool of application servers that need a rolling update/restart cycle.

The more challenging part in this is to abstract away this part of the stack to a simple interface that the developers can use. You cannot and should not expect developers to debug problems in the deployment infrastructure.

Distribution: A local CDN or an international one — which is the right one to use? Should I use a CDN at all? Recently, a company that I spoke to had a response time to their origin server that was 1/5th of what they were getting from their CDN. This was done to leverage cheaper CDN bandwidth and is a classic case of cost optimization at the wrong place.

Is Couldfront the right solution? Can my preferred CDN provider handle wildcard SSL termination at reasonable cost? How costly is it to do a cache purge across all geographies. Is it even possible? Is it important to purge CDN caches? Is a purge important to avoid compliance hurdles for some obscure requirement in my market of choice?

Mobile-specific Parts: Native, cross-platform or HTML5? Do I need a mobile application at all? Which platforms should I target? What is the minimum OS level that I should support on each of those platforms? How do I align those decisions with the target audience I am going to address?

Outbound, non-consumer-facing Services: Should I expose any of my internal data with a developer-facing API? What should I use to expose that API? Do I build it own on my own or do I use a hosted platform like Apigee? What sort of authentication should I use? What sort of identity management should I use. Should I even try to split identity and authentication as two different services?

Inbound, non-consumer-facing Services: What do I use to handle data that I fetch from other sources? How do I ensure that I cache my requests to respect rate limits. What is a Webhook? How do I go about implementing one?

Replication & Redundancy: What is the maximum acceptable downtime for my application? Is there a business case for a multi-DC deployment? How extensive does my disaster recovery plan have to be?

AWS, Rackspace, good old dedicated rack in a datacenter? Should I use Glacier? What should I use for DNS management?

Analytics & Instrumentation: DAU, MAU, WAU — what all do I have to track? Are bounces more important than acquisition? Is acquisition more important than repeat transactions? How do I bucket and segment my users?

How do I measure passive actions? Should I start tracking a minor version of an otherwise less-used browser as my javascript error tracking reports are showing that the current release is breaking critical parts for my most valuable demographic who use that exact obscure browser?

Wait, I can track client side javascript errors?

Conclusion

As you can see, the list raises more questions and provides no answers. This is intentional as there is no one-size-fits-all answer for these questions. Even within specific company lifecycle segments (early stage, stable start-up, established company), the internal circumstances vary from company to company.

These list is more a starting point than a destination in itself. Use it to build a better framework that is suited for your organization and your product. And if you need more help, just ask!

How Not To Build Software For SMBs: SAP’s 3 Billion Euro Story

Tucked away in the story about SAP closing down its SMB suite is one significant detail: It cost the company about 3 billion euros to develop.

SAP, one of the world’s biggest makers of business management software, originally projected that Business by Design – which was launched in 2010 – would reach 10,000 customers and generate $1 billion of revenue.

The magazine reported, however, that the product, which cost roughly 3 billion euros to develop, currently has only 785 customers and is expected to generate no more than 23 million euros in sales this year.

By comparison, in the second quarter, SAP’s software and software-related service revenue stood at 3.35 billion euros.

I am astonished by how on earth can you spend 3 billion to develop almost any software, leave alone one that is aimed at small and medium-sized businesses. The ERP/CRM/PLM landscape these days is an ocean of riches for companies looking for an implementation; be it customization of a generic or product or niche, extremely vertical ones. When anything costs as much as that to develop, it is hamstrung from the word go. I am just surprised that they have managed o keep it going for ten-years. For some perspective, three billion is still considerably north of what most successful software companies are valued at with revenue in the hundreds of millions.

Looking at the pricing for the product (link) it makes no sense at all. If you have to price a product/service like that and yet spend even a billion euros on developing it is nothing short of suicidal. They were hopeful of doing a billion dollars in revenue (annual, I assume); which is astounding considering that their main offerings brought in under 4 billion euros in the second quarter. Normal SAP implementations are long-winded expensive affairs, which plays a key factor in how the company makes most of its money. When big companies lose their way, they tend to do it a spectacular manner like this.

The SMB marketplace is extremely price sensitive and resistance to any change is fairly common place. The newer crop of companies who provide similar services also operate on lower pricing, have no contracts and don’t have many other nice bits companies like SAP are used to. Not surprisingly, the revenue is not expected to top 23 million euros this year, which puts in only in the league of a successful newer SaaS companies.

The upside to all of this is that it makes acquisitions a better option companies like SAP. Three billion euros could easily have been spent on 300 million every year on acquisitions and it would not be a stupid bet to assume that they could have had at least a couple of winners or more in that pick. That said, the conflicts in the business models of the newer crop of software companies and the older mammoth-sized companies is far from a resolution. Companies that are acquired this way have to often force fit themselves into the larger picture, which can be a huge drag. But, that’s a different story altogether, for some other time.

Go West, Young Man And Other Tales From The Entrepreneurial Crypt

Washington is not a place to live in. The rents are high, the food is bad, the dust is disgusting and the morals are deplorable. Go West, young man, go West and grow up with the country. — Horace Greeley

The context maybe different, but the theme — that the fight is simply not worth it here, aim for the Western market — is a recurring one in the digital entrepreneurial space in India. The difficulties in starting up in India are well known and documented. The most recent notable one was Dev Khare‘s ‘The Silent Killers of Startup Growth‘.

The popular thesis seems to be that it is better not to build a product specifically aimed at the Indian market, but at the global one. This thesis is backed by the two kinds of proof – the first being the success story of Wingify and the second being stories like Linea, which, reportedly, has raised $4 million recently. An app like that would not stand any chance in India, no matter how well executed it may be.

The problem has different parts:

1. Lack of funding.

2. Lack of an existing market.

3. Lack of exits, M&A activity.

4. Product DNA that’s not tailored to the Indian audience.

Most of these factors actually compound each other, so the effect is rather drastic on both activity and perception of the market.

But, Hold That Thought

The story is not all of gloom and doom, as shown by the SAIF Partners’ story. The fund, apparently, made 4x returns on their first fund and are on course to do a 5x return on their second fund. Not bad for a country that seems to be a bad bet for entrepreneurs, eh?

The devil, though, in any story (positive and negative) is always in the details. SAIF’s portfolio is not limited to digital and it is spread across different domains. They also struck out with iStream, which recently shut shop and the prospects for the e-commerce plays are not too bright at the moment (Zovi maybe an exception due to their manufacturing background).

Even then, their willingness to make big bets across sectors and have more hits than misses in a market like ours is remarkable. And, having met the team couple of times, I have to say that they are very approachable and low key.

Let us be honest. The Indian story is not a straight forward one. As pointed out rightly by Archit Gupta on a Hacker News thread, success here can often be about having the right connections. A good product and a great team addressing a potentially huge market opportunity is absolutely no guarantee of success here. Connections, above everything else, matters.

Even when corruption and regulation are not determining factors, who you know in a company and how much you can influence them is more critical to closing a sale here often than having an excellent product. Unfortunately, it is also reality that we cannot choose to ignore if we have to grow in the market.

The way out of this morass is neither simple nor easy. There are some really excellent people in every part of the ecosystem who are good and who are looking to good, but they are nowhere close to being empowered to do it. For all of us who care enough, it is imperative to make all the changes we can make, even if it looks hopeless. It is even more important for those who are in influential positions to make this change.

It will take time, it will be hard, but we can break this wall down, one brick at  a time.

Please Don’t Stop The Music

And just like that Flipkart announced the demise of the Flyte, their digital music offering. And the numbers are pretty damning. 100K paying customers is not a great number, when you consider that even a single track purchase at Rs.5 can be considered as a paying customer and we don’t know the detailed breakup of the numbers.

The biggest downside of this development is that it will now set a sort of benchmark at 100K users for any paid digital content product in India, at a really low ARPU. This will have a pretty damning effect on anyone who is looking to get into this segment as Flipkart’s failure will loom large for a long time to come; at least until the fundamentals of the market changes.

While it is hard to figure out what exactly caused Flipkart to shut Flyte down within a year (sorry, no insider info), from the outside, it would seem that the company miscalculated the market size and costs. The product probably made sense two-years-ago when it was critical for the company to widen its base of offerings and topline; much has changed (drastically) since that time.

Even when you keep aside the licensing costs (the minimum guarantee mess), it still costs a lot to deliver the product. Going by NBW’s 2.5 million downloads/100K users number and Medianama’s Rs 9-12 ARPU, the revenue barely touches Rs. 1.5 crore. Another, slightly more liberal, calculation does not push the revenue over Rs. 3 crore for the same time period. Even the most optimistic scenario barely covers the licensing cost, in a segment rife with issues in hitting hyper growth.

None of this should have come as a surprise to the company, as these are well known facts about the digital goods market in India. What has changed is the outlook in the primary business Flipkart is in and the bleak prospects there. With their road ahead firmly set (grow massively big or die quick), they can’t afford to be in niches that won’t enable hyper growth. Flyte seems to be the first casualty of that.

And, oh, incidentally, if you think the Spotify clones are doing any better out here, you are mistaken. They have to pay per stream (at least the cases I know of), monetization is scant and some are already looking for more money to sustain themselves in the long run.

 

Why Do Start-ups Need Investment?

Continuing from the previous post on market opportunities for start-ups, this post will focus on the funding aspect of it. There are various schools of thought in the start-up world when it comes to funding. There are some who believe that investment only ruins companies, while others think of them as enablers and as necessary evil. The key to understanding your need for funding is often found in the opportunity you’re trying to target, so let us figure it out from that point of view.

Before I get going on the four opportunities, the one thing I’ll be very clear about is that there is no golden rule to all of this. Business and funding environments change regularly and every major player in the ecosystem (companies, funds, public markets) all respond to changes in the larger economic climate. So, if anyone shows you the rulebook, pointing out the One True Way™ to grow your company (with or without raising money), feel free throw throw away that book.

Why Do you need investment?

To De-risk: You can always build flying cars using your own money, if you have enough in the first place, or you can attempt to get that money from someone who is better positioned to absorb the losses should flying cars fail.

To Build: You have to put together the first version of the flying car. This involves buying tools, fabricating parts and a thousand other things. Sometimes you may not have the money on yourself to do this without financial help from the outside.

To Validate: A car once built has to find buyers in the market. Even the best built car, kept as a secret in your garage, won’t sell. If it won’t sell, you don’t have a business.

To Grow: The cars are selling well, but you can’t meet the rising demand with your existing infrastructure. You also want to expand into a different geography because you’ve saturated the market for flying cars in your current geography. This involves hopping up through the stages I had mentioned in a previous post.

To Diversify/Consolidate: The flying cars are flying off the shelf, you’re thinking big now and you have hit the limits of efficiency with the current set up. Growth has to come from elsewhere and M&A becomes a viable option within and outside the car industry.

You also realize that you are spending a lot of money in marketing and discounting the prices (thus adversely affecting the margins) to compete with the New Flying Car Inc. A quick look at the balance sheets says that as a combined entity you can be more efficient and improve the margins by an extent that justifies the risks involved in the merger.

The case for not needing investment!

You can build companies through all the four stages listed above without taking on any investment. There are a lot of profitable businesses that were built and continue to run successfully in this manner. These vary from companies of a substantial size to  mom-and-pop stores.

But these are also companies that tend to grow slowly and the odds are, you won’t find much sought-after hockey stick growth in companies that did not take investment. Exceptions are there to this story, but the norm tends to be that to get into the hyper growth stage, companies need some form of a force multiplier in place and the most obvious and organized one available there is capital.

Risks in taking investment & hyper growth

Investors rarely put money into companies for charitable or altruistic reasons. It is important to understand that they’re also running a type of a business that has a substantially high rate of failure. Funds are raised often for a 5-10 year window and to be successful they need to handsomely beat any other investment class out there.

Trouble is that organic growth companies rarely get massive in a 5-10 year window. This is the reason why the hockey stick growth curve is much sought-after by the investors.

The risk with hockey stick growth, though, is that it compress a lot of events and factors into a very very short window. This is similar to human being going from an infant to a full grown adult in an extremely short period of time. Even in companies, you have both Macaulay  Culkins and Dakota Fannings.

On Market Opportunities For Start-ups

‘Disruptive’ is a much-abused word in the start-up world and it is a flawed measure that can be used to determine if an opportunity is worth chasing after. Disruption is an outcome and not a starting point; thus it is best left for glowing testimonials in history books than in business plans.

A better measure ascertain a product’s viability, longer term capital requirements and other key metrics in a business plan is to look at things through the prism of market opportunity. Opportunities can be of the following types:

Greenfield Opportunities: These are products and services that break new ground, building and doing things that have never been done before at any reasonable scale. Example: A car that flies.

Innovation Opportunities: These are products and services that take an existing product or service and approach it from an innovative new angle. Example: A car that costs as same as a regular car, but runs on water.

Execution Opportunities: These are products and services that don’t do anything new, but they do what is already being done in a much better manner. Example: A car that does really nothing new, but it is well put-together and everything feels just right about it.

Pricing Opportunity: These are products and services that are offered at a price point less than what the customer is used paying for a similar service. Example A car that costs half the price of a similar specification model in the market.

Any new start-up or a product has to be very clear within themselves which of the four opportunities do they address, before they hit the market. It also makes things easier for investors to understand your product if you are clear about the opportunity you are after.

What Am I Building?

When 2013 rolled into view I had already completed four-years of working on my own. In shifting to a line of work that is more research and strategy-oriented I figured out that there was tremendous duplication of work and numerous switching of contexts to collect, organize and leverage information.

By then I had tried various approaches — using a variety of tools — to address this problem, but each attempt at it only frustrated me more. To explain the problem, think of your brain as a machine with limited volatile memory and processing power. All the tools only act as physical storage. The pitfalls are rather obvious with this approach.

What I’m building is a framework that approaches this problem from a different angle. What is the approach — I will write more in it as I build more of it. As of now, it is just a set of tacky looking pages and interfaces for entering and managing data. The code has already grown into few thousands of lines and I have only started to scratch the surface with it.

It is fascinating to build something for your own consumption. Most of my development work before this has focussed on getting things built for my clients and building something for myself feels so different. The key thing to watch out for is to not to take any shortcuts and build the system properly. The amount of technical debt that can be acquired at this stage is tremendous.

Focus

In a build of this kind, where the end result often can be a moving (almost unattainable) target, the ability to focus is key. The good part about various tools to build things for the web is that there are endless options available to get the same thing done. If you don’t keep simple, bite-sized goals and validate it regularly you can easily lose your way and give up.

Adaptability

When building against a moving target, assumptions, algorithms, logic and outcomes will change. If you don’t validate quickly and adapt to changes that is deemed necessary by the results, the product will become lesser and lesser useful over time. At every stage, what the product does has to match the desired outcome to a great degree.

Dual Vision

In the early stages it is very hard to see how the gap between what-is and what-it-has-to-be can be bridged. There will be days when you’ll crank out a complicated feature in a better-than-expected manner in the first go. There will be days when a small simple bug will keep everything held up for a day or days.

Building a product on your own can be both gut-wrenching and unbelievably exhilarating at different times. The key thing is to quickly overcome setbacks and triumphs and keep the longer term goal clearly in mind.

The Next Big Mobile Wave

The popular history of the evolution of mobile phones is something on the lines of pre-iPhone and post-iPhone, which is, admittedly, quite a convenient way to look at things. The actual history, though, is a far more nuanced (or, complicated, should you prefer that) affair. The evolution of the mobile phones has gone through various phases like full QWERTY keyboards, colour screens, touch screens, WAP browsers, ability to record and handle videos — the list is endless. Reducing that to a pre and post iPhone world does a lot of injustice to pretty much everyone but Apple.

While Apple deservedly gets a lot of credit for changing our idea of what a smartphone is and how we interact with it, what they don’t get enough credit for how they also changed the way we think of how to use data on a smartphone. If you used a smartphone in the pre-iPhone era the one thing that stood out was that packet data was a second class citizen on the phone. The devices were phone-frist and data access devices second, or later. More than the iOS interface or the physical experience of using an iPhone what is seldom spoken about is this drastic change Apple bought to the market – it was a data access device first, while the phone functionality was a secondary issue.

Always On Data

Data being always-on was a game changer. Phones prior to that would ask you which connection you wanted to use to access packet data and if it should ask you again should the need to use data arise again. Taking data connectivity for granted has changed the way we use these devices. More than faster processors or wider and longer screens, always-on-data is the critical path that has led to the state of affairs today in the mobile domain. Pretty much all of our interactions on a smartphone now takes it for granted that it will be able to access packet data. If it was not for that we’d still be largely relying on text messaging and closed access methods like Blackberry Internet Services.

Momentum, Implications

If you look at the winners and losers in the smartphone game, you will see a clear pattern. The players, like iOS and Android, who adapted quickly to the always-on-data paradigm have moved rapidly ahead of the competition. The ones who failed to adapt that quickly, like Nokia, Palm and RIM, have struggled and continue to struggle. Rapidly growing and evolving markets like smartphones place a premium on momentum and you’ll always find that on the winner’s side. Without momentum, the best of platforms will struggle. And smartphones, being one of those rare objects that potentially can belong to every human being, is a ruthless market where you cannot blink for even a second.

Cycling is a brilliant analogy in this case, especially some of the stages of the Tour de France. The best riders always look to stay in the front group — called the peloton — at all times. This is due to two factors. 1) Momentum: The guys at the front have a much better average momentum through any stage than the rest of the others 2) Safety: In the case of unforeseen eventualities like crashes and crazy headwinds, being at the front gives the riders a better chance of working around problems. Always-on-data was a headwind that was unforeseen by the industry.

The Next Big Wave

Changes in these domains can easily make or break companies depending on whether they ride or miss out on the important waves. Even established big companies can die or go through near-death experiences if they can’t ride these waves quickly. If the last big wave was the switch from seldom-on-data to always-on-data (the one that made Apple), the next big wave in mobile could be anything from a multitude of devices using the same OS to devices that are embedded within/on us than being actual handhelds.

Crystal ball gazing, though, is not an easy task here as products in the domain are not often ruled by simple value choices either to the consumer or to the companies that are involved in the game. There is considerable regulatory interference that stands in the way of services and there’s considerable commoditization at the hardware end. For the skeptics, this is the reason why Apple is very touchy about keeping a cash hoard, the size of which confounds everyone. You don’t take anything in this market for granted and ease off, Nokia is a classic example of that.

 

Grokking Growth: Part I

The topic is a vast one in itself, so I’ll address only a smart part of it and that too from a business-to-consumer perspective.

Growth is one of the key drivers for a business and it is not as uni-dimensional as it is often made out to be. For example, you keep hearing about Facebook hitting a billion users and then some more after it and so on and so forth. Does it mean that once a vast majority of the population in the world is on Facebook the company will stop growing? Obviously, not. Market saturation is a business reality for all businesses that marks an inflection point that often leads to diversification or a comprehensive strategy. Smart companies pre-empt this and change course and pursue another kind of growth, while the not-so-smart ones stagnate and expose themselves to significant risk due to disruption.

 

Chasing growth is, though, quite simple for most companies (keeping side M&A options which don’t happen for most). You can either:

a) Keep getting more users (usually known as the hyper growth stage)  or b) Get more from the same (happens after hyper growth, when market saturation has kicked in).

It is harder for companies to segment growth strategies to address both (a) and (b) as you need to deploy 2x of everything (strategy, resources, measurement) to make this hybrid approach happen, while keeping even a single strategy going is tough enough for most companies. Companies that accomplish it, though, tend to be significantly agile. A good example of a company that didn’t manage a dual strategy would be Nokia.

This dual approach can be applied to specific components of a company’s operations:

Revenue:  How do you increase revenue by getting more users? How do you get more revenue from the existing users?

Profitability: How do you increase profits by getting (customer acquisition cost) new users? How do you increase profits from the existing users?

Putting in place a growth strategy also requires a good understanding of which stage is your company at.

Stage-I: Companies that have low to moderate turnover, revenue growth rate that outpaces at least inflation (ideally outpaces other obvious investment segments). The healthy ones tend to be debt/financing-free and privately held. They also have low risk appetite and low profit margins.

Stage-II: Companies that have medium turnover, they aim for explosive revenue growth through hyper growth. These companies tend to have an extremely high risk and limited runways to make the strategy work. They usually involve significant external investment and/or debt load and tend to be privately held. They have a high risk appetite.  Profit margins are nearly non-existent. Companies in this stage either die or make it to Stage III.

State-III: Companies that have massive turnovers. Their revenue growth rate is low but predictable and use debt as a routine path to fund growth. These tend to be public companies and they have a good ability to absorb risk. Their profit margins tend to be steady and companies like this die a slow agonizing death when they do die.

S-I companies typically grow organically. S-II companies typically grow by spending vast amounts on customer acquisition. S-III companies accelerate growth usually through M&A or by diversification.

I’ll examine each theme in detail in a later post.