Ability or Agility - what matters more?

I'm sure most of you made up your mind on the answer, as soon as you read the question. The small proportion of you who still don't have their answer to this are probably people who always answer with 'it depends'.

The truth is the many people have a strong point of view here. And in my experience the answer depends on where we are from, in an industry and experience sense.

From the perspective of an organization Ability is a more tangible thing to build. We need to execute a set of initiatives in the coming years, which need certain capabilities, which stem from certain competence and so on - clear. Agility is more vaguely defined. It's more talked about in a relative sense, or in a 'I know it when I see it' sense. For many organizations, it's about cross-skilling the employees, which mostly means a policy of job rotations, and a capability view of the employee superseding the experience view.

One thing is clear to me - agility follows ability. I have seen organizations where job rotations happen annually. The head of the company is there by virtue of being the head of marketing before, and he got there because he was head of a different function before. The number three person in sales used to be a number three person in service. While these people have great cross-functional understanding, they sometimes do not get enough time to build functional expertise. The other extreme, is the much cited organization where people super-specialize and finally know everything about nothing - so much so that employees can't speak each-others' language.

What is the best approach depends a bit on the industry and the competition too. In a startup environment in a budding industry, one maybe needs to build a team that knows something about everything. If on the other hand you're competing in a mature industry at the efficiency game, then you need functional and domain specialization.

Finally, to re-emphasize, I'm not against job-rotations or the culture of building for agility - just that each layer in the pudding takes time to set. If we're replanting our plants very often, they don't grow so well, if they grow at all.

Are Discontinuous Purchasing Funnels a norm in eCommerce?

We all talk of the customer journey or purchasing funnel at some point or the other. There are models that start with awareness. And some models start at basics like ability, opportunity and motivation to define the universe before that. Then from awareness, there is interest, there's decision and action. Multiple models exist to talk about similar flows. Then there are models that talk of marketing building a flow of consumers to your store, visual merchandising bringing them inside and engaging them, supply-chain ensuring the product is on the shelf and sales to ensure the customer makes the purchasing decision. One needs to be good at all the funnel acts for awareness, or need, to culminate in a transaction.

If you have a broken link, all other good effort is wasted. Do good marketing, have bad product-development, and you only get dissonance or ridicule, but no transaction. We all believe in this.

Now the interesting aspect you see in eCommerce - what happens when your funnel is better or worse than someone else's? Can a good section in the funnel compensate for a bad section that is later in the flow? What happens if you have good awareness, a great product experience, the widest range, great decision-aids, but not-so-great prices?

In the offline world, of-course, there's a high cost for the consumer to switch. Just because the end of some retailer's funnel isn't the best, the customer won't walk out of the store, take the elevator to the basement, drive out his car after paying for parking, drive through crowds to get to another mall, park in that basement, take the elevator to another outlet, and start flowing through that other funnel. The online world, of-course, bridges distance.

There are five tabs simultaneously open.

It is no additional cost for the consumer to start product search in one tab, price search on another, feature comparison and expert advise on the third, and use a fourth tab for transactions. Post the advent of price comparison, at least for standard, definite, cataloged products, it is possible for an eCommerce platform to be best at nothing but prices and still do well on transactions versus another platform that provides the best decision-tools but higher prices. Now with the democratization of prices, offers and coupons, it has started affecting offline retailers as well, though their leakages for reasons talked about earlier are lower.

So, that is perhaps the lesson to be learnt. The parts of the funnel that contain key decisions are key. Everything else is not. When your website is good for everything else but conversion, then unpleasant as it may sound, you're not in business - you're just an affiliate.

Is there a nucleus, a critical mass for talent?

We all agree that there are always changes in the environment and the company's priorities. We also know that there's a need to continuously create new capabilities that never existed before. And we may have all seen that it's a tough thing to start creating a competence from scratch.

If there's no one in your company who knows Internet Marketing, you want to start hiring Internet Marketing experts. The question is how do you decide on the best candidate when you don't know enough to judge competence in that area. You hire the person who seems the best to you. You make a mistake and realize your mistake in six months. You give it a 'I-don't-know-how-but-fix-it' speech and give it another three months, then a last warning and another three. Then what? You have the same risk hanging on your head. How do you get around this chicken and egg?

Take another equivalent problem. Say you have IM competence and you, for some reason, start losing it. At some point, the people who are left start getting frustrated because no one in your company now understands what they do. Some start enjoying the vacation and start doing what they fancy, or even nothing. There's no one to guide and drive them. At some point, the IM folks don't have a gang and they lose interest and motivation. More people leave. Is that something that also rings a bell?

So here's the question, is there a nucleus needed for talent / capability? Is there a critical mass needed to make that talent-pool self-sustaining? And the other question, if you don't have a nucleus, what do you do?

Some companies try an agency model, some try and get experts on board to help out in hiring. Some just push good people in the company to acquire that missing competence through trainings. And are there ways to increase your capability mass? If you were to connect your IM people to IM folks in other countries within your company, or if you connect them to a similar community in another, non-competing company, does that delay the exodus?

Missionaries vs. Mercenaries

We all want to establish a culture of commitment in our teams and companies. We all prefer to work in teams where people are willing to die for each other. And yet we all know that's rare to find. It would seem almost a Utopian imagination if we did not have examples of where this has happened, at least for certain lengths of time. We've heard about it in books and movies, all the way from love stories to war stories. We hear stories of people so motivated that they strap bombs and blow themselves up, and of soldiers who choose to die saving others and each-other.

The one place it seems to happen the least, if one looks at basic social connects of self, family, clan, society, nation and so on, is unfortunately work, a context where we probably spend more time than any other.

When Wharton management professor Peter Cappelli and Monika Hamori of IE Business School analyzed job search data from a leading executive search firm, they found that more than half of the high-level executives contacted by the firm — 52% — agreed to be candidates for positions outside their company. The more senior the executive, the more willing he or she is to engage in a job search. The lack of allegiance to one’s company “is symptomatic of a broader way of managing organizations in general,” Cappelli says. The two researchers found that executives with “career breadth” — including international experience — are more likely to engage in a job search, suggesting that when executives are moved around from city to city or country to country, “they don’t develop strong ties to the organization. It becomes easier for them to leave”.

The bigger facts to consider are that companies nowadays hire employees with a width of experience. They also make it clear that churn is inevitable. Any post-merger-acquisition, leadership change, or just plain hard times mean that employees will be let go off. Employees treat the company as they are treated. Such employees also create companies that behave this way. Structurally, there are very few long-term incentives at most firms.

Now, I do realize every startup is not the same, but the typical copybook garage startup starts with friends, or at least people comfortable with each other, not from hiring the best resumes. The best resumes climb corporate ladders while start-up-ers slug it out in at least some hard times. Even after a few years, these guys may not have very marketable resumes because they've done bits coding and business-dev and marketing and HR and everything else, but the corporate world is looking for functional specialists. You see? They need the startup and the startup needs them, and needs them to stay. If they stay long, they can cash out. If they don't, both have nothing.

That could be the one reason why so many people mention they find missionaries in startups and mercenaries in corporates. And while it's far from conclusive in my mind, it's definitely a thought starter.

Piloting Non-existent Concepts

One of the more interesting discussions I have had around Strategy is around Pilots. We all know that in general, and specifically in emerging or nascent markets, is that there isn't enough past data to base decisions on or to make business plans on. What you do in such cases is not research but pilots? Bet small amounts on multiple horses, see which horses win their first races, bet more on them and less on the others and so on till you have a winner.

Talking of Pilots, it is possible in eCommerce, more so in eCommerce than in offline commerce, to pilot out hypotheses. If you have a great packaging solution, try and see how the product does without the fancy packaging but discounted to that effect, check how the same listing does with or without CoD, or with or without no-questions-asked returns. If website / platform flexibility is an issue, one could try out the demand pilots purely on mailers. If one wants to know what's the sweet spot on prices or discounts, or the tradeoff between, say, faster delivery and price, it is possible to have two listings at different prices and different delivery timelines to check which one takes off faster in sales. It is then possible to dynamically alter the discount and the delivery timeline to check what's the point at which decreasing returns set in. And this brings us to the crux of this discussion.

How does one pilot faster deliveries - or any other offering we don't have and that takes sunk investments to build-out? We already operate on optimal delivery schedules. Won't we have to set up a separate infrastructure to create faster deliveries? And if we have to invest in setting up stuff, then doesn't it defeat the purpose of piloting the concept? We can't create a warehousing and pre-shipment infra and then conclude that faster delivery doesn't create value in the eyes of the consumer i.e. the consumer is not willing to pay more to get the goods faster. Then we can't roll back our investments to go back to what we had earlier.

Or maybe we can.

We could partner with a third party to create this experience for the pilot, but then the costs of doing this won't be representative. But there's something simpler we could do - which is not exactly the same thing, but quite useful for pilot results.

We can pilot slower delivery!

Now we'll put up two listings side by side, one with our standard price and delivery-time, and the other with a lower price but slower delivery, and check which one appeals to consumers. Versus a listing with an elevated price and faster delivery, this simulation will also give us results on what is the sensitivity on between delivery-time and price.

You see? There's always a way. When the ideal option is not possible to pick, pick the best possible option.

What are your thoughts?

Where is the Devil in Business Plans ....in the Assumptions?

...is in the details, right? Well if you know where to look. I have often been asked what I look for when I check a business plan. Many people I know spend a lot of time going through the data, the data-sources, the formulae, the methodology (e.g. discounted cash flow valuation) etc. Some even check for links between data-sheets, references and so on. Where I spend 90% of my time, based on my experiences so far, is on the assumptions sheet.

I'm not saying, for a moment, that the output sheet is not sensitive to the other things highlighted above. I'm saying something else. Most people who build business plans can be trusted for accuracy on formulae and linking of cells. Where competence has a smaller role to play is on the assumptions. Assumptions are futuristic, they are usually based on data but there is a choice of data to choose from e.g. for the GDP or inflation data, one could have different sources, all authentic, saying different things. Which source you pick determines which data point is picked up and how your business plan results look. A lot of assumptions are not even data based e.g. assumptions of how much market share one will get in year-3. There is no sure-shot way of getting that data. All you have in such cases are scenarios.

Next interesting point, how many business plans have scenarios built up? Even if it's not a complex monte-carlo simulation here, just basic scenarios - base case, pessimistic, optimistic etc. Now when you apply scenarios on the end-results, which is how it's commonly done, you'll end up pushing up results by 15% for one scenario and down by 10% in another - but that means little. What one could and should do is apply those to the assumptions sheet. Pick up the lowest GDP growth estimate in the pessimistic case, the most probable estimate in the base case and the best estimate in the optimistic case - and so on for all the assumed variables. This gives you a much wider range of what is the worst that might happen when all goes downhill and what is the best case when all looks up.

Now let's take yet another perspective, of biases and vested interests. Often the person who creates the business plan is the person who stands to gain or lose the most by the overall verdict on the plan. If this person were to have an ulterior motive, where do you think he / she plants his / her biases? It'll probably not be in the formulae or methodology - since getting caught there could be the end of that career. It's more likely to be in minor tweaks of assumptions one could easily reason or argue out of.

One more perspective is on what happens to business plans over time. The calculations don't change, what changes is all on the assumptions sheet. Interest rates change, market or competition developments happen, new products hit the market, and the impact is again on the assumptions sheet, and still when we look at our follow-up processes, so very often we tend to focus on the summary sheets e.g. RFP vs. actuals, projections vs. latest forecast etc, rather than setting up a frequency where all the past business plans are reopened and the assumptions revised.

Either way we look at it, checking assumptions is most critical. Updating assumptions periodically is also very important. Finally scenarios - do not accept business plans without scenarios, and without those scenarios being linked back to the assumption-sheet where - you guessed it - each assumption has scenarios.

What has been your experience? Have you caught more devils elsewhere? Or is your experience the same?

Is Cash-on-Delivery really eCommerce? if yes, then what is (also) Mobile Commerce?

We've all read about how eCommerce is bigger than it looks. There are needs other than actual purchasing that eCommerce fills. Amazon, it seems, has overtaken Google in the US as the startingpoint of product-search. In order to make a purchasing decision, you need information, and an eCommerce site is (or should be, it is believed), in the business of providing the same. Therefore, what you can also do is also use eCommerce only for the purpose of decision-making, deciding what to buy, maybe even where to buy - but not actually buying. 

A recent BCG report ("From Buzz to Bucks") have called this internet-influenced buying.

What also happens is the reverse - people don't know what an Xperia J looks like, weigh or feel like, so they go to a mall, check it out, come back and purchase online where prices are better for the same standard product. This is split by consultants (naturally) into (guess-what) a 2X2, with segments called Research-Online-Buy-Offline, Research-Offline-Buy-Online, and of-course the other two blocks of people who complete the buying process Online or Offline. The transaction will be called Online or Offline basis where it is *consummated*. So this is the first thought I'd like you to hold on to.

The third thought is a simple question - is Cash-on-Delivery eCommerce? The "transaction" i.e. the exchange of goods for consideration really happens after the goods are delivered to the shipping address, acknowledged, checked and then paid for. The entire decision-making process and the commitment to buy has happened online, but the transaction is really offline.

Now the second thought is just an extension of the same logic to say there are people who extensively use the mobile phone to research, but then open their PCs / laptops next morning to transact - maybe because screens are larger, or keyboards are better, or connectivity is better, or just due to plain habits. The use case for the reverse is thinner but still non-zero. You could have used your laptop to make a decision (where you can actually compare four products'-specs side by side), and then used your mobile to monitor prices and then when you saw the price drop to the level you wanted - maybe you were on your way home then - you just clicked on 'Buy' on the mobile.

Now putting it all together, if you read this at one go, it will appear that Mobile Commerce is bigger than it is. If CoD is eCommerce (and rightfully so) then mobile-initiated transactions are m-commerce. That can help change perspectives of a lot of organizations in countries like India where we keep thinking m-commerce has not happened yet just because there aren't enough transactions culminated on the mobile. 

How different is "my" customer and "yours"?

So many brand discussions start with customer profiling. There are deep dissections on the difference between our customers and those of our competition. Our customer is more open to using her credit card online while the competition's customer favors cash on delivery. Our customer is older but more evolved. Our lapsers are more likely to be staying in big cities. It stops striking some of us after a point that we're using a cognitive shortcut by giving an identity to an aggregate average statistic.

More importantly, we forget that in many if not all cases, all these different identities are just one person. These many customers aren't different people who behave differently. Our customer also shops with the competition. Our customer is the competition's customer.

This is not trivial. We draw up pen-portraits, day-in-life's, mood-boards of preferences and so on and forth for these supposedly different characters. We do qualitative research around customer groups that are 'our customers' and 'our lapsers' or 'competition customers' to understand them better. If we see the same person turning up in two groups, we suspect incorrect recruitment if not foul-play and impersonation. How could the agency mix up our customers with theirs? Or customers with non-customers? Sounds familiar?

If there are more men in the people who end up converting on my platform versus my competitor's, this may show up as 'our customer is 70% male while our competitor's is 80% female'. I think it starts off being a small poetic license (the use of the singular) and ends up sounding inane. There is no one out there who is 70% or 20% male.

Reality check - it gives us great pleasure to prick this balloon with the pin of knowledge you had all along. These different characters with their distinct unique personalities are like the average man. Like the man with exactly the average height, weight, hair and nose-length - who doesn't exist.

These customers - yours and mine, are heuristics, short-cuts, simplifications - and just that.

What we really should be talking about, and thinking about - are different need-states. In one need-state, a customer prefers my shop and in another, my competitor's. That's really what it is.

If my eCommerce platform, for example, is great for technology products and not so great for lifestyle products, the same customer, in the lifestyle need-state is my competitor's customer and when in the technology frame-of-mind, is my customer. A frequent misread of this state is as follows: my customer is a technology buyer and the competitor's is a lifestyle buyer. Familiar?

So what?

A lot of things. Just as a starting example, do you think segmenting users or customers makes more sense now or segmenting need-states, use-cases or states-of-mind? Litmus - think of yourself, are you ever just one brand's customer?

Are you building a Concorde?

All of us know about the concorde - sorry, let me correct myself - about Concorde, right? You have to get it right, so I hear.

So here's what happened, broadly.

An Anglo-French JV (Aérospatiale and the British Aircraft Corporation) built Concorde, a supersonic passenger plane (out of two ever built) that halved transatlantic flight-times, a proposition that'll still sell if you were to poll potential passengers today. It flew for 27 years but only 20 aircrafts were built. While there are multiple theories on its efficacy, it is known as a supreme technological feat. It is also known that it never made money. Finally after the one accident it had, and in face of mounting losses, the program was shut in 2003. This was despite Government subsidies and sponsorship, despite the muscle of Aérospatiale and BAC, but importantly, despite a very strong consumer proposition – halving transatlantic time, the hype value of flying cutting-edge etc.

Or was it? Was it really a strong value proposition? I'm not an expert there, I've not seen the value-prop, but I assume that while it was undeniably good for the customers to half their flying time, maybe it wasn't important enough to pay the ticket price premium. Why I say this because had it not been the case, I assume other supersonic passenger jets would have been built.

What is known is that costs spiraled to 6 times the initial estimate. For perspective it was $ 23mn. Note, in 1977 dollars. Post retirement, Branson offered to buy British Airways’ Concorde planes, first offering their nominal original price of £1 each, then increasing the offer to £1 million each. Note, this is in 2003 pounds.

Also quoted is the fact that the big reason behind Concorde's grounding, apart from the cited reasons of the 4590 crash, fuel cost etc, was that it was more profitable to carry passengers at subsonic speeds.

The existence of technology, and a thumbs-up from potential customers sometimes blinds us into confusing these things as a 'buy-in'. Today, a faster website, faster delivery, better packing, better consumer service will all be things that a customer wants. Without a sensitivity curve along all the value-prop axes, however, these are all directional and that's all. What we should be researching is how many customers will pay what it takes to get these desirables on the table. What we should also do is check if there's a margin buffer between original price and a post-spiral price for long development projects.


I'm never against cool technologies. I love them. I'm genuinely sad to see Pandora, Wikipedia and WorldSpace bleed. Maybe not wiki - they made a choice not to make ad-money, but WorldSpace was in it to make money. Customers loved it. Just not enough customers maybe, not enough love perhaps, not enough love to pay. This is an important litmus for those of us in the In Tech industries especially, it is common to see over-spec-ed products. It's an engineer's / designer's self-actualization, but let’s remember all that is useless if there aren't enough people who pay for those specs.

What do you think?

Social Recommendations, Discover-ability of the Truly New, and the Aha!

I'm sure you see a lot of "people who bought this also bought this" or "people who read..." or "friends who listened..." or "friends who watched...." nowadays on sites. That is social recommendation for a lot of businesses. The assumptions are clear. We are sheep. No, that sounds bad, but we're some similar creatures.

I kind-of agree. Most of us are not early adopters, and we seek sanction in the actions of other people. Why should we try untested waters unless we know people who jump in them come out alive, or better, enjoy it? The friends part makes even more logical sense. If we're sheep, we follow sheep and now flies. We make friends based on some commonality, and if my friends like something, maybe I like it too. Better chance than trying out a product none of my friends like. Right?

Yes, except that most of us are also unique. Sometimes, actually most of the times, we are sheep. But some times we are deliberately not. We don't want to wear the same shirt as everyone else. We also try to be different. We want to seek our own New. We want the thrill of being the first to discover something cool which then, other people also like. Some times we want to hold on to what we discover and don't want others to know about the small cozy cafe we discovered because once they do, it'll stay neither small nor cozy. Also if you think about it from the other perspective, that of someone / something wanting to be discovered, you have a terrible cold-start chicken-egg problem.

No one knows you, no one likes you, so no one follows any one to your door. Seems like a dead-end.

Not on the Music Genome Project, not on Pandora.

Anyone who's used Pandora is a fan, or I haven't had the fortune to come across any other type. Pandora is a radio-station for those who still don't know, that will ask you for a couple of songs you like and then will go on to predict, based on what you like and what you skip, to progressively suggest songs that you love, but have never heard of. Pandora doesn't do the 'like' business. The Music Genome Project, in the background, describes each new song, through an algorithm on about 400 attributes (genes), and each new song is rated by a musician on those attributes again, and that is what it uses matches to match your taste. This means that if Pandora has figured out what kind of music you like, and there's someone who's written a song like that, you discover it, hear it, love it - without ever needing to hear about the band, or the genre, or the country or century it was written in - and without any of your friends having heard of it. For those who can (it's legally available only in US / AU / NZ I think), you must try it for genuine aha moments.

What I find even more amazing is that this stuff is possible in as complex a realm as music. What I find amusing, however, it how much simpler it might be for, say, books - and you don't see this happening. T-Shirt fans could be following the herd in styles and trying to stand out a bit in terms of the slogan, but book fans really look for that unheard of book that gives them the aha.

Recap, recommendations work. Social also works. Attribute-based cataloging also works. There are categories (like the undiscovered), and occasions (imagine gifting someone what everyone else is gifting), and people (the cult of the non-conformists) for whom a Pandora of things is a crying need.

It is more difficult to build this out, but this could be well worth its while. I'm sure, at least hoping, that there is stuff being built as we speak.