VC, Know Thy Fundee

The Venture Capital industry in the US has given extremely poor returns in recent times, and some consider it broken. I'm not sure what the India numbers are, but the focus, modus operandi and problems facing the space are similar, and in some senses, less effective. The huge factors in their favour are the relative stability and ever growing domestic markets (of course, for those focused on India, and more so for those primarily into the PE story), and of course tremendous cost tractability vis-a-vis the Valley, for instance.

Now, imagine:

Don Corleone invests in a million bucks into a "business" run by a fledgling caporegime in a territory with lots of promise. A few months down the road, the monthly meeting is in a dark room full of cigar haze with tough questions flying across the table, and the Godfather surprising the capo with info gathered from the street that the capo might be trying to hide, or gloss over. It could either end in the capo getting a thumbs up for establishing firm control, or a "Its strictly business" list of to-dos to strictly be followed for ensuring the family gets there profitably.

Or, a traditional business family in India pitches in to get a young chap striking out on his own in a new town/business/opportunity afresh. They obviously need to buy in to the idea, and measure progress often enough. They also dig up every source to keep tabs on where the markets headed, what the guy's reputation, image and credibility is as he engages with the market, and offer both advice and tips, as well as harsh feedback on specifics that is passed on immediately and well - transparently.

Thats how businesses get built, sustained, nurtured.

The Venture Capital industry plays an important role in discovering and nurturing new market opportunities. In fact, the businesses they try to help build are usually much larger than what an average capo or a family businessman would attempt at creating. These businesses need even more nurturing, and inputs. Theoretically, at least, the VC not only brings capital to the table, but also helps keep the ship on course, plugging the gaps as they're spotted. They can help engineer the right contacts, aid the best executive hiring, enable appropriate mentoring amongst others.

But then, there's a gap when it comes to those value adds, at least in the Indian context. Unlike Don Corleone, or the average business guy on the streets, venture investors often fail to connect with their startups' work - operationally, technically and sometimes even from a consumer/customer point of view.

The best understanding of the businesses investors have today depend on "other-investors'-opinions" and on their own take on it. Generation, technology gaps, lack of empathy with the target market, and an uncertain understanding of what's really getting built ensure that the meetings are once-a-month "updates" affairs, and the data collection is usually limited to what their protégées tell them. Sure there's some cross questioning, and the numbers sometimes start communicating the true story (often too late in the game).

But to be able to really relate to whats happening, whats right and whats not, and most importantly, what the options are from thereon, VCs would benefit from a deeper, independent assessment of the businesses they're banking on. And of course, the technologies, products and target markets those businesses are banking on!

There is a need for a role which can better understand the domain or technology that the startup is built around. This is truer for technology startups than the others, but there's usually something technical/domain specific about every startup (at least the better ones) that differentiates it. Most investors are generalists and connectors, because of which they bring together a wide array of skills, perspectives and contacts! Obviously, their understanding of what's happening inside of their portfolio companies, and what course corrections could and should be made, is limited to the level of a higher level business scenarios that can only make uncertain assumptions about the finer, and often crucial, details of the product or domain. And we do hear a lot that execution is everything!

So, how do investors get to know better ? Call in the experts!

To someone in the know, the red-flags show up all over the place as you dig a little! One hears of huge investments in companies build around technologies (sometimes mere features) that could be build primarily around commodity stuff that might even be free to download off the web. Other startups build vanity-features that are unlikely to see much usage amongst their target audience. And a whole lot of startups do not even figure out who this "audience" is, and at the same time worry about the numerous textures the product could have.

Then there are obviously numerous "high technology" stories where the potential is enormous, but the success is extremely dependent on both the core as well as the packaging and positioning of the product. A lot many might potentially succeed in one of many avatars, and would benefit from rapid experimentation enabled by flexible product design.

Clearly, VCs would benefit a lot if they got dope on some of the above, early and regularly. This obviously needs a continuously updated understanding, and measurement, of what their companies are doing. Every decision around the product feature and roadmap, its architecture, and even the robustness of the process through which these are arrived at, makes a huge difference to the product's chances in the market. These cannot be gauged easily from a short monthly interaction with the CEO. You need a sharper focus on the goals, and ongoing engagement at various operational levels to ensure those are being worked towards.

Goals

What are the companies goals ? Are the same goals visible to all functions across the organization ? Are those the ones driving value for users/customers ? For instance, you're trying to create a service that delivers content over SMS along with contextual advertising, and a product loophole that allows people to essentially send free SMSes to friends could be the one driving traffic!

Roadmap

Is the Product Roadmap in line with the goals ? Often, beyond the first release, nimble startups get into a reaction mode where every little piece of feedback from users, VCs, the media and other assorted sources is incorporated, and every little idea that comes from competing sites, or merely sounds cool, gets implemented. You end up with a host of features and functions that are no longer coherent or cogent to your primary USP, which was .... ? Obviously, even the metrics gathered start reflecting this, and there's confusion both externally and internally about what the product or service really is ? Crispness is key.

Team, Hiring, and its first cousin - the Burn Rate!

Funded startups are usually at risk! There's money, and folks now have the luxury of pursuing the various ideas that have not been able to get attention so far! Add to this the ability to right away target multiple groups of customers and consumers, do branding, create pitches and soon, you're lost in infinite activity thats gong nowhere. There's a need to link all spending, right from the size of the team, the skills needed, the necessity of doing certain things all together, to the goals and the roadmap.

Keeping the burn rate down not only helps focus, and it gives the startup get operationally viable sooner, and provides both the founders and the investor a lot of buffer!

Obvious Benefits

The returns on getting onboard an operationally focused team are quite apparent. An investor would do well to have help at hand for regular, clear understanding of what's happening in the portfolio companies. This would ideally be a team which brings in both technology and product management experience from a in-the-trenches perspective. The startup would get better help, better focus and probably leaner.

Quite obviously, whats better for the startup is better for the investor!

Disruptive ? [ Fly standing ]

Its pretty straightforward - if most people are a little shocked and taken aback with the idea or change you're suggesting, it could be one of those big ones. Sure there's a risk, but just might be worth taking!

For instance, I've been wondering why, even on flights that last not longer than an hour - everyone needs to sit! Especially in nicely padded seats that cocoon them. People do take the tube and stand for those lengths of time, and its conceivable that a "rest your butt against" something design works. At the least, rows of long benches can surely optimize space.

Of course, the first reaction is "it compromises safety". But I'm very curious, as a percentage, how much of a role better seats had in reducing fatalities. Unlike road skirmishes, if it fails up there, you usually say your prayers. Yeah, I hear ya about the "every life is worth saving, etc. But,

1. You're assuming the cabin overall cannot be made safer for standing passengers! I'm talking about redesign not mere re-fitting.
   
2. Air accidents take far fewer lives than road accidents than pool drowning incidents....
3. Despite how it sounds in the context, there is something such as a tradeoff. Else, we'd be all outfitting our cars with roll cages, wearing helmets inside them, and donning safety gear before driving anywhere. Everything is percentages.
   

Its an industry in deep trouble. They need to make more, so we can all continue to fly. We need to reduce our flying footprint. So go ahead, innovate the hell out of that cabin space and we can make space for a few more, and keep things cheap too.

Sounds crazy ? But to start with, disruption should. Its a question of figuring out if there's a feasible path to getting there, and making those numbers work.

Data-Driven Decisions vs. Intuition : Is it really a "vs" ?

Its very hip to talk about being data driven, and as engineers, very appealing as well. Its also a more provable way of justifying a decision. User A/B tests on various designs prove it like no amount of brainstorming can, and clickstreams, sales numbers do not lie!

Yet there are majorly accomplished folks that disagree vehemently with the data-centric approach to decisions, and that makes for a good debate :). Here's a very good 360 around that particular one.

So, is the "versus" in the debate actually called for at all ? As engineers, do we beat too many things down with the data club ? (I somewhere suspect the opposite is not that strikingly true for designers, decision makers, etc who are seen as "following instinct")

Let's deconstruct this data driven decision thingy, shall we ?

You gotta decide about a product idea, or a sales strategy, or a marketing message. So typically, this is what you do (explicitly, or otherwise)

• Imagine who might consume the outcome of the decision
• Try and figure out something about the above set. Data ? Helps a lot!
• Take a call on what'll work.

The data is an input (and comes in many forms!). Over this input is a layer of interpretation, analysis and the final decision is a reaction to this process. Data can help decide, but data cannot decide!



At what level is the decision ?

Are you deciding about a UI attribute for an existing, popular product ? Sure, do bucket tests and let the audience speak. Is it about the product's copy ? Hmm, a little less black and white. The positioning and concept you're trying to communicate about the product ? Well - there's no getting away from hard work and decision making on that. If you expect data to always provide all the answers in black and white terms, you're likely to freeze when working on a lot of things at a more "zoomed out" level.

For entrepreneurs, its often a question of whether the product (which is usually the company itself) is working, and if its not. If you need data to tell you that, you have other serious problems :) Of course you will be going through data, and what we popularly refer to as "instinct" or "intuition" does not develop in isolation of data. On the contrary, its something you develop as you learn how to sift through data, read between its lines and deal with the apparent conflicts it sometimes throws at you.

Conflict ? Aren't numbers black and white ?

Are they ?

Here's two data points from an example I remember reading about recently (sorry, do not recall the source). A survey of numerous car buyers in India put safety high up there in the lsit of influencers for the buy-call. Yet the actual purchase decisions (vis-a-vis the information requests) for models with ABS, airbags or till some time ago, even those with seatbelts at the rear said it was not necessarily an important factor.

The case study surmised that the latter was to be believed, and the former to be ignored. Its probably a more trustworthy data point! So the models which get ABS etc continued to be those at the top end of the offerings.

There - you already needed to pick and choose, and not trust every bit of data as is. But is that all ?

Weren't the consumers also communicating an aspirational need, or one that got negated merely because the cost differentials between the (usually high end) models with ABS etc and those without were extremely high ? Would these people pay a smaller difference for the same in an otherwise lower spec'd model ? Is there a way to lower the cost of including the safety add-ons ?

Do you have enough data ? Qualified ?

Very often, a new venture, idea or product does not even have enough data to start with. Product and entrepreneurship decisions are full of these cases. You still do your best to understand what the picture is, and base a call on that. Would you like to base your calls on tiny samples ? Or would you rather ignore them, unless a clear message emerges ?

And them, lets say you launched and had a couple of hundred thousand clicks on a new page/feature. Of course, you SEO'ed, maybe ran an ad or two, and maybe got some initial coverage? What was the quality/value of those clicks ? Did they all come from ad-clicks, with little repeat usage? Are they from the right target audience which might help in engagement and drive usage/consumption of the important features? Should a transactional site be very happy if a lot of folks turn up looking for info alone? Should it be despondent ?

The clickstream is quite useless during the early life of a product unless qualified. Yes you can collect more data for it, but each qualifier and context for data that you measure stems from a judgement call about why a number is important, and when must it be factored in. Of course, again, you can create a analytics framework to crack that as well, but at some stage or the other, its impossible to keep out human judgement and interpretation of data completely.

Its not "data vs intuition".

There's a huge risk to merely following data - in case you've not set the right context. You can be lulled into a sense of safety/driven into panic needlessly merely because the data says you doing great/horribly, and you forgot to try and see whether you were missing some part of the picture.

Data is only about the stated. The rest is conjecture or extrapolation!

Extrapolation (quite like analogies :) ) is a pretty strange thing.

You can collect data about what's out there. What did the user leave unsaid? Did they like your logo? Why did the dropoff happen at some point ? Did something trigger a word of mouth ? What about the not-clicked links - why did those get ignored ?

Some will need another round of hypothesis and data collection. Others will need some level of an educated guess so you can move on. You've got finite time and resources, and your product is not a grant funded lab!

Data is valuable. But the value is elsewhere.

A lot many great businesses have been built on instinct. That does not discount the research they did as preparation, or the amount of information they might have collected. It only highlights that the ability to make a decision with whatever is available is far more valuable. With the same data, the same inputs and for the same scneario, there will be multiple decisions that succeed to varying degrees, and numerous possible ones which might fail. It is an art, and the attempts to reduce it to a science can only work for low-granularity decisions, and that again for existing, running-state stuff.

What's probably more critical, and to be practised to improve one's judgement calls, is to actively seek to verify hypotheses through launch-and-test iterations, and do these cheap. Developing a good sense of what data to collect, how to read it in the context of other numbers, words around it - this will serve you much better than being a data driven automaton. Its a great help to have numbers, but remember to use them both judiciously, and honestly.

Its not yet time to let the machines take over ;)

SlicedBread

Its been a month!







I've gotten together with a couple of other people who're Gurus at understanding various aspects of Products - strategy, positioning, technical understanding and roadmaps, analytics, etc - and created SlicedBread. The idea is to - oh, well - there you go...