Category Archives: Product Management

India’s new Software Products Policy marks a Watershed Moment in its Economic History – Can the nation make it count?

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India is on the glide path of emerging as one of the economic powerhouses of the world – its economy is ranked sixth in size globally (and slated to climb to second by 2030); it has the fastest growing annual GDP growth rate amongst (major) countries; the country ranked in the world’s top 10 destinations for FDI in 2017-18. With a population of 1.3 billion and a large middle class of ~300 million+, it is one of the most attractive markets globally. Specifically in the digital economy – India has a huge $ 167 billion sized IT industry; it boasts of a 55% market share in global IT services & outsourcing; 1140 global corporations run their tech R&D centers in India. In the tech startup space, India has attracted Private Equity (PE) & Venture Capital (VC) investments of $33 billion in 2018, and it has over a dozen unicorns (startups with over $1 billion valuation).

These data-points are truly impressive and would make any country proud, but they belie one of the glaring historical paradoxes of the Indian economic story – the sheer absence of world beating products from India. Ask Indians to name three truly world class, globally loved Indian products or brands – chances are they’ll struggle to name even one. Check out the Global Innovation Index 2018 from the World Intellectual Property Organization (WIPO) – India doesn’t figure in the top 50 countries. Or the Interbrand 2018 Top 100 Global Brands Ranking – there’s no Indian name on that list. Leave aside brick & mortar industries, the Indian IT & Digital sector doesn’t fare any better on this count. IT services, which forms its lion’s share comprises largely of low end, commoditized services or cost arbitrage based outsourcing contracts. Most of the new age tech unicorns in India are based on ideas and business models that are copied from foreign innovators (with some local tweaks) – their outsized valuations are a result of them being the gatekeepers to the large Indian market, rather than from having created path-breaking products from first principles. So the overall trend is that India has a large domestic market, and it is a big supplier of technical brain power on the world stage, but when it comes to building innovative products, we come a total cropper. This is best reflected in the Infosys Co-Founder, Narayan Murthy’s candid quote – “There has not been a single invention from India in the last 60 years that became a household name globally, nor any idea that led to earth-shaking invention to delight global citizens”.



Launch of the National Software Products Policy (#NSPS):

It is in this light that the recently rolled out National Software Products Policy (#NSPS) by the Ministry of Electronics & IT (MeitY), Government of India marks a watershed moment. For the very first time, India has officially recognised the fact that software products (as a category) are distinct from software services and need a separate treatment. So dominated was Indian tech sector by outsourcing & IT services, that “products” never got the attention they deserve – as a result that industry never blossomed and was relegated to a tertiary role. Remember that quote – “What can’t be measured, can’t be improved; And what can’t be defined, can’t be measured”. The software policy is in many ways a recognition of this gaping chasm and marks the state’s stated intent to correct the same by defining, measuring and improving the product ecosystem. It’s rollout is the culmination of a long period of public discussions and deliberations where the government engaged with industry stakeholders, Indian companies, multinationals, startups, trade bodies etc to forge it out.

#NSPS will bring into focus the needs of the software product industry and become a catalyst in formulation of projects, initiatives, policy measures etc aimed at Indian product companies. One of its starting points is the creation of a national products registry that’s based on a schematic classification system. Other early initiatives that will help in operationalizing the policy – setting up of a Software Products Mission at MeitY, dedicated incubators & accelerators for product startups, development of product focused industrial clusters, preferential procurement by government from product companies, programs for upskilling and talent development etc.

The Indian IT / Software Industry Landscape:

To understand the product ecosystem, one needs to explode the $ 167 billion sized Indian IT / Software sector into its constituent buckets. The broad operative segments that emerge are –

1) IT Services & ITES: This is by far the largest bucket and dominates everything else. Think large, mid & small sized services companies throughout the country servicing both domestic & foreign markets. e.g. TCS, Infosys, Mindtree, Accenture, GE etc
2) Multinationals / Global Development Centers: These are foreign software companies serving Indian markets and/or using India as a global R&D development center. e.g. Microsoft, Google, Netapps, McAfee, IBM etc.
3) Domestic Product Companies: This is a relatively small segment of Indian software product companies selling in domestic or overseas markets e.g. Quickheal, Tally etc.
4) Startups – Ecommerce / Transactional services: This is the large, fast growing segment of startups into direct (or aggregated) transactional businesses like ecommerce, local commerce, grocery shopping, food delivery, ride sharing, travel etc. e.g. BigBasket, Flipkart, Amazon, Grofers, Milkbasket, Swiggy, Dunzo, Uber, Ola, Yulu, Ixigo, MMT etc. You could also include the payment & fintech companies in this bucket – e.g. Paytm, Mobikwik, PhonePe, PolicyBazaar, Bankbazaar etc. This segment has absorbed the maximum PE & VC investments and is poised to become bigger with time.
5) Product Startups – Enterprise / CoreTech / Hardware: This is comprised of companies like Inmobi, Zoho, Wingify, Freshdesk, Chargebee, Capillary, electric vehicle startups, drone startups etc. They could be serving Indian or foreign B2B markets.
6) Product Startups – Consumer Internet: This segment is composed of media/news companies, content companies, social & professional networking, entertainment, gaming etc. e.g. Dailyhunt, Inshorts, Sharechat, Gaana, Spotify, YouTube, video/photo sharing apps, Dream11 etc.

(N.B. Off course, this segmentation schema is not water-tight and there could be other ways to slice and/or label it)

Why India lags behind in Software Products?

The global software products industry has a size of $ 413 billion, and it is dominated by US & European companies. India’s share in that pie is minuscule – it is a net importer of $ 7 billion worth software products (India exports software products worth $ 2.3 billion, while it imports $ 10 billion). “Software is eating the world” – entire industry segments are being re-imagined and transformed using latest developments in cloud computing, artificial intelligence, big data, machine learning etc. In this scenario, it is worth understanding why India seems to have missed the software products bus. The reasons are multifarious, cutting across cultural, economic, market, behavioral and societal factors –

a) Cultural aversion to Risk, Ambiguity & Failure: Indian society has traditionally valued conformity and prepares people not to fail. Our family and educational environments are geared for teaching us to eschew risk-taking and avoid ambiguity. But building products is all about managing risk and failure. When you take a product to market from scratch, you take on multiple types of risk – market risk, execution risk, product risk. For many people in India, this is in stark contrast to their social / attitudinal skills and expectancies they have built up over a lifetime.

b) “Arbitrage” offers the Path of Least Resistance: If you pour water down a heap of freshly dug mud, it will find the path of least resistance and flow along it. Human behavior is similar – it is conditioned to look for the path of least resistance. And “arbitrage” offers that least resistance path in the IT industry – be it cost arbitrage, labour arbitrage, geographical arbitrage, concept arbitrage et al. The IT services industry leverages the cost arbitrage model via cheaper labor costs. Many of the transactional ecommerce startups in India have used geographical arbitrage to their advantage – once a successful product or model is created in another market, they bring it to India to capitalize on a local first mover advantage, build a large valuation and become the gatekeeper to the market before the (original) foreign innovators arrive in India many years later! But arbitrage means, that while you are taking on market & execution risk, you are not assuming the product risk. This dynamics played out at scale over the years has meant it is easier for a wannabe entrepreneur in India to go the arbitrage way and quickly build out a business using a readymade template, than go down the software products path, which has a much longer gestation & higher risks associated with it.

types of startup risks - market risk, product risk, execution risk, financial risk

IMHO, this “arbitrage” factor represents the single biggest reason why India has seen a virtual explosion in ecommerce startups, at the expense of product startups. Look around the startup ecosystem and you’ll see all kinds of transactional businesses involving activities like buying, selling, trading etc. Why… this almost reminds of that famous 17th century quote by Napolean when he described Britain as a “nation of shopkeepers”🙂

c) Tech isn’t enough – you need design, marketing skills: To build great software products, you not only need strong technical abilities, but also good design, marketing & branding skills to carve out a compelling product offering. Ask any startup in India – one of their most common problems is the inability to hire good designers and UX professionals. This puts Indian companies at a comparative disadvantage – even if they have the engineers to build the technology, their inability to translate that technology into an appealing user experience often means the difference between success and failure.

d) Lack of “patient” venture capital: This is a complaint you hear often from Indian product startups – the lack of venture capital that’s willing to be patient over the longer gestation cycles software products demand. While there is some truth to it, the more likely explanation is that software product companies present a “chicken & egg problem” for Indian startup investors. Investors are driven by financial returns – if they see returns from product companies, they’ll bet their monies on them. It just so happens, that Indian investors haven’t yet seen venture sized returns from software product companies. Hopefully this dynamics will even out as the ecosystem grows.

e) Inadequate Domestic Market Potential: Many software products are monetized via subscription models, where the market’s ability (and propensity) to explicitly pay for the service is critical for success. Sometimes (SAAS/enterprise) companies try their model in India, only to discover there just aren’t enough paying customers. These startups may then be left with no choice but to either target foreign markets, or in extreme cases just move abroad for business continuity. Thus it has become imperative for the Indian domestic market to grow in size and scale to ensure viability of product startups.

Platform companies from India are a non starter: One aspect that needs calling out specifically is the sheer absence of any platform companies from India. Platforms are the next evolutionary step for scaled software product companies – if you get to the stage, where other industry stakeholders start building on top of the plumbing you’ve provided (thereby becoming totally dependent on you), that’s an immensely powerful position to be in e.g. AWS, Android, iOS etc. This factor assumes even greater importance given upcoming trends in AI, machine learning, deep learning, automation, robotics – the companies which emerge as platform providers may offer strategic advantages to the country of their origin. As depicted by the graphic below, India is as yet a non starter on this count. This is deeply worrying – imagine a scenario 10-15 yrs out, when Indian software companies start dominating the domestic markets and also are a force to reckon with globally, but it’s all built on intellectual property (IP) & platforms created & owned by foreign companies!!

Some Suggested Action Areas for the National Software Policy:

MeitY in consultation with industry stakeholders is likely to create an implementation roadmap for #NSPS. Here are some specific action points I’d like to call out for inclusion in that roadmap:

Domestic Market Development: As explained earlier, the Indian domestic market needs curated development to reach a potential that makes product startups viable without having to depend on overseas markets. This calls for a series of steps, such as policy support from sectoral regulators, funding support via special go-to-market focused venture capital funds etc. The government could also help by announcing a preferential procurement policy from domestic software product companies. The Government e Marketplace (GeM) can help in institutionalizing these procurement norms.

Creating Early Awareness (Catch ‘em young): Fed by constant news in media about IT services, ITES, BPOs, outsourcing etc the average person in India is likely to be aware of IT services, but not necessarily software products. Many people may have friends and family members who work at TCS, Infosys, Wipro, IBM etc, but the same can’t be said about product companies. Given this scenario, it is important to create early awareness about products in schools, colleges, universities across metros, Tier 1, Tier 2 & 3 towns. Some of the world’s biggest product innovators like Bill Gates, Steve Jobs started writing software before they had reached high school – so if we can catch people young, we actually get a much longer runway to get them initiated into the product ecosystem. If they learn about products after they’ve started working in industry, or when planning a mid-career shift from services to products, it might be quite late.

Reducing entry barriers for starting Software Product Companies: As shared earlier, one of big problems in the Indian software product space is that there just aren’t enough entrepreneurs starting up product businesses. Ecommerce & transactional services actually absorb (or suck in) a lot of entrepreneurial talent by virtue of having lower barriers to entry. To make a serious dent in products, you need a much larger number of product companies started off the ground. This can happen only by systematically bringing down the entry barriers – driving awareness, providing funding support, providing market development support etc. Advocacy and evangelism by software product industry role models also can help develop confidence and conviction in people to think products instead of services or ecommerce.

Building domestic Software Product Companies atop public goods: Silicon Valley has shown how you can build successful commercial applications on top of public goods (e.g. Uber built on top of GPS, Googlemaps & mobiles). In a similar way, public goods in India like IndiaStack, or HealthStack can be the base (or the plumbing) over which commercial applications get built for mass scalability. The good news is this trend has already been kickstarted, though its still early days.

The Origin of Product Ideas – Where do they come from? And how to think about them in a Structured Way?

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Its been seven months since Twitter officially made the 140 to 280 character limit shift, and by all indications they have pulled it off spectacularly. I remember the outrage when the move was first announced – many Twitter diehards felt the idea was superfluous and would overnight dilute its ethos of forced brevity, painstakingly built over a decade of toil. Trolls had a field day – people were imagining what Trump @280 would do to world peace!

But the changeover happened, and data shows it is working significantly better than before. No one’s complaining – to the contrary, Twitter seems ever more useful. My own usage of twitter and the time I’m spending on it has since jumped significantly. And interestingly enough, the Twitter stock is up almost 100% since the rollout (though that doesn’t necessarily imply causation!).

Betting your Company on a Single (Product) Decision!

If one were to reflect on this – we’d realize this move was unparalleled, something I’d describe as “The Mother of all Product Decisions”. I can’t think of any other example, where a company’s future was bet on a single (product) decision. Twitter is a public company, a globally loved service, and in early-mid 2017, its growth was plummeting, and the stock was tanking. Wall Street analyst types were baying for the CEO’s blood. If the 280 character transition were to have bombed, it would be a public fiasco, possibly leading to the CEO’s removal. But to everyone’s relief, the transition went off smoothly.

This set me thinking about the broader implications of Twitter’s decision from a product management standpoint – where did the conviction for their decision come from, how did they back this call and finally pull it off? And more importantly for lesser mortals – what are the lessons product managers/owners can derive from this very special happening?

Where do Product Ideas come from?

In general, product people are confronted with ideas, opinions & suggestions all the time. They come flying thick and fast, from left, right & center – when you’re at the coffee shop or water cooler, in meetings or focus groups – they keep pouring in via emails, text messages, Twitter, social media, customer support et al.

Should I build that new feature, or just copy my competitor? Do I need specific data to back my product assertions, or that two year old user research I read in the newspapers would suffice? Do you trust your guts, or just listen to your boss (and in the process, make him happy)? These questions have no perfect answers – but what would help is to have a mental model or a decision framework that provides a structured way of looking at the flow of incoming product ideas.

Kipling’s 6 Honest Serving Men as a Product Management Decision Tool

I’ve always been a big believer in Rudyard Kipling’s 6 Honest Serving Men Principle – “I keep six honest serving-men (they taught me all I knew); Their names are What and Why and When And How and Where and Who”. Throw it at any problem, and it always gives you a good starting point to analyze any situation and build your thoughts & arguments upon.

I’ve frequently fallen back on it to analyze product situations and have rarely been disappointed. With time and experience, I’ve had this realization that (as applied to product situations), there are 2 “men” of those 6, that tend to matter more than others – “who” & “why”. This might be surprising because you’d expect “what” & “how” to be paramount. “What” & “how” are important no doubt, and usually get called upon to explain the “content”. But “who” & “why” have something else going for them – in many situations, they capture the context better than the others. And as they say – “Content is King, But Context is God“.

6 ways Product Ideas get Originated

To help product managers & owners add structure to their thinking, and slot the barrage of incoming feedback/ideas into a logical, repeatable mental model, here’s a simple framework (focused on the “who” & “why”). Most incoming product ideas can be slotted into one of the six originating points – each of these would require a different approach to analyze and act upon.

– One Person’s Opinion: Imagine meeting your boss at the water cooler, where he casually shares an idea. Or one of your investors mailed you his thoughts on the future product direction. Or it could be just about anyone else giving you their point of view – all of these are examples of what is essentially a One-Person’s-Opinion. The way to deal with this – take the suggestion at face value and then put it through the rigours of your own decision making process (refer: LinkedIn CEO Jeff Weiner’s post explaining OPO, which is where I borrowed the term from!).

– Multiple Pointers: Suppose three different customers asked you for a particular product feature. So now you have “multiple pointers” about something which seems to have a strong case and merits further exploration.

– Vocal Minorities: Vocal minorities are tricky phenomena to deal with, specially at early stages of your product’s evolution. This might be a (numerically small) set of users who love your product, and have very strong opinions/suggestions about it in a very vocal/loud way. (I’ve personally had bad runs with vocal minorities during SlideShare’s early years, some of whom ping me [read pester:)] on social media even to this day!) The problem – they feed off your psychological biases, and often become catalysts in driving the product in undesirable directions. Needs careful, mature handling. (Suggested reading – Stop listening to just your vocal minority, work to understand your silent majority instead).

– Insights: Sometimes your idea’s genesis lies in statistical data, market trends or customer research. Or it’s something your competitors did so successfully, copying them makes sense. Example – read this excellent case study of Bira, the Indian craft beer and how its founder identified the optimal product attributes, because he had gained deep insights from importing foreign beers into India.

– Derived Decisions: These are product decisions you make based on past internal experiences. You might have tried various experiments in the past which didn’t work, and that shapes your future conviction about what to do (or not do). Example – think Google, and how it has virtually given up on building new social applications. It’s likely that given their previous (numerous) failed attempts at social products, they have come to the realization that their company is engineering centric, doesn’t “get” social, which is best avoided.

– Hunch: Hunch is like your sixth sense about what works or doesn’t work. It’s a rare skill to have, but if you have someone on your team with a good product hunch, that’s a VERY valuable resource. The best example of hunch off course is Steve Jobs with his telling quote “A lot of times, people don’t know what they want until you show it to them.”

If I had to stick out my neck on the Twitter case, I’d imagine it was a combination of derived judgements & specific product insights, while ignoring the (opposing) vocal minorities. They must have had real data (maybe A/B tests or something else thereof) why the 280 character limit would work. If Twitter were still a small startup, one could have attributed it to its (brilliant) founder’s hunch. But given it’s a public company and high on public/political visibility, unlikely this was just a hunch. Its fair to assume that in large organizations, such pivotal decisions would need the backing of objective data-points and scientific measurements.