Tag: ola

Waiting for Kumaraswamy’s Tiger

Finally, last week Softbank announced that it has closed its $9.3 Billion investment in Uber. Since the deal was in the making for a long time, the deal itself is not news. What is news is what Softbank’s Rajeev Misra told Uber – to “focus on its core markets in US, Europe and Latin America”.

One way of reading this message is to see it as “keep off from competing with our other investments in Didi, Grab and Ola“. If Uber takes Misra’s words seriously (they better do, since Softbank is now probably Uber’s second biggest shareholder, after Travis Kalanick), it is likely that they’ll go less aggressive in Asian markets, including India. This is not going to be good for customers (both drivers and passengers) of taxi marketplaces in India.

Until 2014, the Indian market had three vibrant cab marketplaces – Uber, Ola and TaxiForSure. Then in early 2015, TaxiForSure was unable to raise further funding and sold itself to Ola, turning the market into a duopoly. Back then I’d written about why it was a bad deal for Indian customers, and hoped that another company would take TaxiForSure’s place.

Three years later, that has not come to be and the Indian market continues to be a duopoly. When I visited Bangalore in December, I noticed service levels in both Uber and Ola being significantly inferior to what I’d seen a year earlier when I was living there. Now, if Uber were to cede ground to Ola in India (as Softbank implicitly wishes), things will get further worse.

Back in 2015, when TaxiForSure was shutting down, I had assumed that another corporate entity, perhaps Meru (which runs call taxis) would take its place. And for a really long time now there have been rumours of Reliance entering into the cab marketplace business. Neither has come to be.

So this time my hopes have moved from corporates to politicians. The word on the street in Bangalore when I visited in December was that former Karnataka Chief Minister HD Kumaraswamy had partnered with cab driver associations to start a new cab marketplace, supposedly called “Tygr” (sic). The point of this marketplace, I was informed during my book launch event in Bangalore in December, was that it was going to be a “driver oriented app”.

This marketplace, too, has been coming for a long time now, but with the Softbank deal, it can’t come sooner. Yes, it is likely that it will not be a great app (if it is “too driver oriented”, it won’t get passengers and the drivers will also subsequently disappear), but at least it will bring in a sense of competition into the market and keep Ola honest. And hopefully there will also similar competition in other cities in India, though it is unlikely that it will be Kumaraswamy who will disrupt those markets.

A lot is made of the fact that investors like Warren Buffett own stocks in all major airlines in the US. Now, Softbank seems to be occupying that space in the cab marketplace market. It can’t be good either for drivers or passengers.

Incredible stupidity in taxi marketplaces

So it’s nearly a week since Uber and Ola drivers in Bangalore went on strike, and there’s no sign of it (the strike) ending. The longer the strike goes on for, the more incredibly stupid all parties involve look.

The blame for the strike should first fall on Uber and Ola, who in some hare-brained madness, forgot that running a platform means that both sides of the market are customers and need to be taken care of. They took good care of passengers, providing discounts and growing their market, but rather quickly pulled the plug on drivers, and there is no surprise that drivers are a rather pissed off lot.

The root cause of driver dissatisfaction has been falling bonus payments, and consequently, incomes. This is a result of Uber and Ola providing too great a subsidy during the time they built up the market.

I don’t fault them for providing those bonuses – when you are building a two-sided market, you need to subsidise one side to solve the chicken-and-egg problem. Where I have the problem is with the extent of bonuses, which gave drivers an income far in excess of what they could make in steady state. This meant that as the market approached steady state and incentives were withdrawn, once side of the market started getting pissed off, undermining the market (Disclosure: I’d once proposed to Ola that they hire me to help them with pricing and incentive structuring. the conversation didn’t go too far).

With Uber and Ola having done their stupid things, the next round has gone to the drivers. In a misguided attempt that a long strike will help them get better deals from the platforms, they are prolonging the strike. They’ve even ransacked Uber’s offices, and gone to the government for help.

What they don’t realise is that having invested what they have in their cars to drive on these marketplaces, their success is inextricably tied to the success of the marketplaces. And the more the jeopardise the marketplaces, the less their incomes in future.

A long strike reduces market size on two counts – it gives people time to adjust to the absence of service and get adjusted to alternate arrangements, and it decreases the reliability of the marketplaces in the eyes of the passengers. Thus, the longer and more frequent the strikers by the drivers, the less that passengers will look to use these services in the future.

A strike can work when the striking employees are protected by some form of labour laws, and there is no way ahead for their employers apart from a negotiated settlement. In case of a marketplace, the platform has absolutely no obligation to the drivers, and Uber and Ola can simply do what Uber and Lyft did in Austin, TX – pack up and move on. And if they do that in Bangalore, the drivers with their shiny new cars will be significantly worse off than they were before the strike.

The other act of stupidity on the drivers’ part has been to involve the government, which, as expected, has responded in a nandelliDLi (“where do I keep mine?”) fashion. The recent ban on shared rides (UberPool/OlaShare) came after a regulator read the rulebook after the last strike by the drivers. Given the complex economics of platform markets, any further regulation can only hurt the drivers.

All in all, the drivers’ stupidity can be traced back to not understanding platform markets, and protesting the way protests used to be done in highly unionised industries. Drivers, whose main skill is in driving cars, cannot be faulted so much for not understanding platform markets. Uber and Ola, on the other hand, have no such excuse!

Why Uber/Ola is Nehruvian

According to Ramachandra Guha’s India After Gandhi, the ostensible reason for India adopting a statist/socialist/planned approach was the scarcity of capital.

With capital being scarce in the newly independent country, Jawaharlal Nehru had reasoned that in order for the country to develop, whatever capital existed had to be deployed in the most productive manner possible. A free market for capital would end up deploying capital where it wasn’t required the most, denying more critical sectors of capital. A planned economy, on the other hand, would result in more efficient usage of capital.

While India has developed significantly in the 70 years since independence, it is still not completely out of the woods. Poverty remains high and India’s per capita income is at the lower end of the spectrum. Thus, while capital may not be as scarce a resource as it was in 1950, effective deployment of capital is still necessary to ensure India’s continued economic growth.

From this perspective, think of the car. When at rest, it is adding no economic value apart from making itself available to its owner (and its owner alone) at a point of time when the latter needs it. From this perspective, the economic value that the parked car adds is almost entirely in terms of “option value”.

A parked car also consumes valuable economic resources, with the most important being the real estate it stands on. This particular resource is so important that it forms an important form of urban regulation in most markets (a building or a business needs to have a certain minimum number of parking spaces and so on).

Moreover, the two common axes on which the value of a car is evaluated are age and distance travelled. Considering that the car adds economic value only in terms of the latter – when it helps transport someone, depreciation of the car in terms of age is entirely uncompensated. On this account, too, a parked car is a dead weight loss.

It is not hard to see, thus, that a parked car is an enormous waste of capital; capital that an emerging economy such as India could very well utilise elsewhere. Yet, the large number of cars in the country that are standing still at any point in time show that despite being an overall inefficient use of capital, a large number of people value the inbuilt option value.

Back in the time when Nehru had his way, he had solved the problem in his own unique way – by limiting the number of cars that could be manufactured and sold in the country, which automatically put a limit on the number of parked cars. In this technologically advanced day and age, however, we don’t need such drastic measures.

All we need is a restructuring of economic incentives such that the option value of a parked car goes down. And what better incentive than to provide the option to summon a car on demand? While this summoned car might have a higher marginal cost per trip than an owned car, taken in aggregate it leads to a significantly lower cost.

Thus, the Nehruvian answer to the inefficient capital wasted in parked cars would be to encourage services that allow you to summon a car on demand. In other words, services such as Uber and Ola fulfil a Nehruvian objective by freeing up capital that was being earlier wasted in parked cars. There is data to show that such services have resulted in a decline in growth of car ownership.

Given that Uber and Ola follow the Nehruvian ideal of reducing wasteful capital, it is baffling that the government in Karnataka, which belongs to the Congress party which is based on Nehruvian ideals, or the government in Delhi, headed by the Nehruvian Arvind Kejriwal, were to campaign to clamp down on such Nehruvian services.

There might be some tremors under Shanti Van.

Uber’s anchoring problem

The Karnataka transport department has come out with a proposal to regulate cab aggregators such as Uber and Ola. The proposal is hare-brained on most  counts, such as limiting drivers’ working hours, limiting the number of aggregators a driver can attach himself to and having a “digital meter”. The most bizarre regulation, however, states that the regulator will decide the fares and that dynamic pricing will not be permitted.

While these regulations have been proposed “in the interest of the customer” it is unlikely to fly as it will not bring much joy to the customers – apart from increasing the number of auto rickshaws and taxis in the city through the back door. I’m confident the aggregators will find a way to flout these regulations until a time they become more sensible.

Dynamic pricing is an integral aspect of the value that cab aggregators such as Uber or Ola add. By adjusting prices in a dynamic fashion, these aggregators push information to drivers and passengers regarding demand and supply. Passengers can use the surge price, for example, to know what the demand-supply pattern is (I’ve used Uber surge as a proxy to determine what is a fair price to pay for an auto rickshaw, for example).

Drivers get information on the surge pricing pattern, and are encouraged to move to areas of high demand, which will help clear markets more efficiently. Thus, surge pricing is not only a method to match demand and supply, but is also an important measure of information to a cab aggregator’s operations. Doing away with dynamic pricing will thus stem this flow of information, thus reducing the value that these aggregators can add. Hopefully the transport department will see greater sense and permit dynamic pricing (Disclosure: One of my lines of business is in helping companies implement dynamic pricing, so I have a vested interest here. I haven’t advised any cab aggregators though).

That said, Uber has a massive anchoring problem, because dynamic pricing works only in one way. Anchoring is a concept from behavioural economics where people’s expectations of something are defined by something similar they have seen (there is an excellent NED Talk on this topic (by Prithwiraj Mukherjee of IIMB) which I hope to upload in its entirety soon). There are certain associations that are wired in our heads thanks to past information, and these associations bias our view of the world.

A paper by economists at NorthEastern University on Uber’s surge pricing showed that demand for rides is highly elastic to price (a small increase in price leads to a large drop in demand), while the supply of rides (on behalf of drivers) is less elastic, which makes determination of the surge price hard. Based on anecdotal information (friends, family and self), elasticity of demand for Uber in India is likely to be much higher.

Uber’s anchoring problem stems from the fact that the “base prices” (prices when there is no surge) is anchored in people’s minds. Uber’s big break in India happened in late 2014 when they increased their discounts to a level where travelling by Uber became comparable in terms of cost to travelling by auto rickshaw (the then prevalent anchor for local for-hire public transport).

Over the last year, Uber’s base price (which is cheaper than an auto rickshaw fare for rides of a certain length) have become the new anchor in the minds of people, especially Uber regulars. Thus, whenever there is a demand-supply mismatch and there is a surge, comparison to the anchor price means that demand is likely to drop even if the new price is by itself fairly competitive (compared to other options at that point in time).

The way Uber has implemented its dynamic pricing is that it has set the “base price” at one end of the distribution, and moves price in only one direction (upwards). While there are several good reasons for doing this, the problem is that the resultant anchoring can lead to much higher elasticity than desired. Also, Uber’s pricing model (more on this in a book on Liquidity that I’m writing) relies upon a certain minimum proportion of rides taking place at a surge (the “base price” is to ensure minimum utilisation during off-peak hours), and anchoring-driven elasticity can’t do this model too much good.

A possible solution to this would be to keep the base fare marginally higher, and adjust prices both ways – this will mean that during off-peak hours a discount might be offered to maintain liquidity. The problem with this might be that the new higher base fare might be anchored in people’s minds, leading to diminished demand in off-peak hours (when a discount is offered). Another problem might be that drivers might be highly elastic to drop in fares killing the discounted market. Still, it is an idea worth exploring – in my opinion there’s a sweet spot in terms of the maximum possible discount (maybe as low as 10%, but I think it’s strictly greater than zero)  where the elasticities of drivers and passengers are balanced out, maximising overall revenues for the firm.

We are in for interesting days, as long as stupid regulation doesn’t get in the way, that is.

Market depth, pricing and subsidies

A few days back I had written about how startups should determine how much to subsidise their customers during the growth phase – subsidise to the extent of the long-term price. If you subsidise too much initially, elasticity might hit you when you eventually have to raise prices, and that can set you back.

The problem is in determining what this long-term sustainable price will be. In “one-sided markets” where the company manufactures or assembles stuff and sells it on, it is relatively easy, since the costs are well known. The problem lies in two-sided markets, where the long-term sustainable price is a function of the long-term sustainable volume.

A “bug” of any market is transaction costs, and this is especially the case in a two-sided market. If you are a taxi driver on Ola or Uber platform, the time you need to wait for the next ride or distance you travel to pick up your next customer are transaction costs. And the more “liquid” the market (more customers and more drivers), the lesser these transaction costs, and the more the money you make.

In other words, the denser a market, the lower the price required to match demand and supply, with the savings coming out of savings in transaction costs.

So if you are a two-sided market, the long-term sustainable price on your platform is a function of how big your market will be, and so in order to determine how much to subsidise (which is a function of long-term sustainable price), you need to be able to forecast how big the market will be. And subsidise accordingly.

It is well possible that overly optimistic founders might be too bullish about the eventual size of their platform, and this can lead to subsidising to an extent greater than the extent dictated by the long term market size. And some data points from the Indian “marketplace industry” show that this has possibly happened in India.

Having remained credit card only for a long time now, Uber has started accepting cash payments – in order to attract customers who are not comfortable transacting money online. This belated opening shows that Uber perhaps didn’t hit the numbers they had hoped to, using their traditional credit card / wallet model.

Uber has problems on the driver side, too, with an increasing number of its drivers turning out to be rather rude (this is anecdata from several sources, I must confess), refusing rides, fighting with passengers, etc. Competitor Ola has started buying cars and loaning them to drivers, perhaps indicating that the driver side of the market hasn’t grown to their expectations. They are all indicative of overestimation of market size, and an attempt to somehow hit that size rather than operating at the lower equilibrium.

So an additional risk in running marketplaces is that if you overestimate market size, you might end up overdoing the subsidies that you provide to build up the market. And at some point in time you have to roll back those subsidies, which might lead to shrinkage of the market and a possible death spiral.

Now apply this model to your favourite marketplace, and tell me what you think of them.

Barriers to entry in cab aggregation

The news that Reliance might be getting into the cab aggregation game got me thinking about the barriers to entry in this business. Considering that it is fundamentally an unregulated industry, or rather an industry where players actively flout regulations, the regulatory barrier is not there.

Consequently, anyone who is able and willing to make the investment and set up the infrastructure will be able to enter the industry. The more important barrier to entry, however, is scale.

Recently I was talking to an Uber driver who had recently switched from TaxiForSure. The latter, he said had lost “liquidity” over the last couple of months (after the Ola takeover), with customers and drivers deserting the service successively in a vicious cycle. Given that cab aggregation is a two-sided market, with prominent cross-sided network effects (number of customers depends on number of cabs and vice versa), it is not possible to do business if you are small, and it takes scale.

For this reason, for a new player to enter the cab aggregation business, it takes significant investments. The cost of acquisition for drivers and passengers is still quite high, and this has to be borne by the new player. Given that a significant number of drivers have to be initially attracted, it takes deep pockets to be able to come in.

Industry players were probably banking on the fact that with the industry already seeing consolidation (when Ola bought TaxiForSure), Venture Capitalists might stop funding newer businesses in this segment, and for that reason Uber and Ola might have a free rein. Ola had even stopped subsidising passengers in the meantime, reasoning (correctly for the time) that with their only competition being Uber they might charge market rates.

From this perspective it is significant that the new player who is entering is an industrial powerhouse with both deep pockets and with a reputation of getting their way around in terms of regulation. The first ensures that they can make the requisite investment (without resorting to VC money) and the second gives the hope that the industry might get around the regulatory troubles it’s been facing so far.

I once again go back to this excellent blog post by Deepak Shenoy on the cab aggregation industry. He had mentioned that what Uber and Ola are doing is to lay down the groundwork for a new sector and more efficient urban transport services. That they may not survive but the ecosystem they create will continue to thrive and add value to urban transport. Reliance’s entry into this sector is a step in making this sector more sustainable.

Will I switch once they launch? Depends upon the quality of service. Currently I’m loyal to Uber primarily because of that factor, but if their service drops and Reliance can offer better service I will have no hesitation in switching.

The ET article linked above talks about drivers cribbing about falling incentives by Uber and Ola. It will be interesting to see how the market plays out once the market stabilises and incentives hit long-run market rates (at which aggregators need to make a profit). A number of drivers have invested in cabs now looking at the short-term profits at hand, but these will surely drop with incentives as the industry stabilises.

Reliance’s entry into cab aggregation is also ominous to other “new” sectors that have shown a semblance of settling down after exuberant VC activity – in the hope that VCs will stop funding that sector and hence competition won’t grow. After the entry into cab aggregation, I won’t be surprised if Reliance Retail were to move into online retail and do a good job of it. The likes of Flipkart beware.

Cabs to airports

Early yesterday morning I had a minor scare when Mega Cabs stood me up. I had a flight to catch at 7 am to Mumbai, and had booked a Mega Cab for 5am. This was after consulting a few friends who are frequent travellers on Monday mornings, who advised that finding an Uber or Ola at 5am is not particularly straightforward. I must mention that I haven’t done business trips for a while, which means I haven’t had to catch 7am flights, so the last time I took one such flight was before Ola/Uber became big in Bangalore (October 2014). And I’ve always preferred Mega to Meru since their cabs are relatively better maintained and more prompt.
And then Mega stood me up. The assigned driver Nagesh N never called me, and when I called him, didn’t pick up. I didn’t panic, since I knew I could get a cab on Uber or Ola, except that neither had any cabs available. I called Mega customer care, who promised an alternate cab at 5:15 (still leaving enough time to get to the airport and catch my flight). But then I received an SMS saying that I’ll get a cab at 6:15. Rather than arguing with Mega, I tried Uber once again, and this time I was in luck, finding a cab that would take me to the airport at a surge of 1.8X (80% more than the “normal” fare).
So on the way to the airport I got talking to Kumar, my Uber driver, about the economics of cab rides in Bangalore, and airport trips. As I had mentioned in my earlier post on Uber’s new pricing model, the reduction in per kilometer fare and increase in per rupee fare has meant that an airport run is normally not remunerative for an Uber driver. Add to this the fact that Uber’s bonus payments to drivers are on a “per trip” basis rather than a percentage or distance basis, that a driver reaching the airport at around 6am has to wait for at least a couple of hours to get a passenger to ride back to the city, and that Uber’s new bonus structures that began today not paying much incentives for trips before 7 am (this was told to me by Kumar), drivers have responded by simply not switching on their Uber systems at 5 in the morning, when the likelihood that any trip is an airport run approaches 1.
This is clearly inefficient, and  consequence of bad pricing on behalf of Uber. On the one hand, drivers are denied opportunities to carry customers over long distances, which is an airport run. On the other, customers are inconvenienced thanks to the lack of cabs, and have to rely on the otherwise rather unreliable and mostly unused Meru or Mega cabs, whose cars are of poor quality and drivers unresponsive. A lose-lose situation. All thanks to bad regulation (read my post in Pragati on how Uber is like a parallel regulator).
The solution is rather simple – an airport surcharge. Any trips to or from the airport on Uber can be slapped a further surcharge (of Rs. 200, perhaps). Such a surcharge will make the ride remunerative for drivers, while at the same time still keeping Uber much cheaper than the likes of Meru or Mega. In fact, this morning’s trip, after the 1.8X surge, cost me Rs. 780, which is cheaper than what it would have cost me if Nagesh N of Mega Cabs had not ditched me, and I could pay in a “cashless” manner, directly from my Paytm account. It’s a surprise that Uber hasn’t yet figured this out, given all their “data science” prowess!
Update: 
A friend who I met on the flight told me that in his town (Whitefield) it’s not hard to find an Uber/Ola cab at 5am on Mondays, except that the drivers cancel rides once they figure out it’s for an airport drop. Again pointing to the fact that incentives are not aligned for maximum throughput

What sets Uber apart from other marketplaces

While at the gym this evening I was thinking of marketplaces.  To give some context, the reason I went there was that there were too many thoughts running around my head, so I needed to focus on something mindless or something that required so much concentration that I could only hold one other thought in my mind at that point in time. In fact, when you go “under the bar” (do a back squat),  even that one thought will vanish – you need all your physical and mental energy to complete the squat.

Anyway so I was thinking of marketplaces, and marvelling at the kind of impact companies like Uber and Ola have had. They have been an absolute gamechanger in their business in that it has completely changed the way that people and cabs get matched to each other. This was a matching that had been extremely inefficient in the past, but with these apps, they have become better by an order of magnitude. And it is this order of magnitude that sets apart Uber/Ola from other marketplace businesses.

And as I was moving between weights, I had another thought – the trick with Uber/Ola as a marketplace is that it is near impossible to do “side deals”. The ultimate nightmare for a platform/marketplace provider is to let the two sides “discover each other” and conduct further deals “offline”. This can be the bane of services such as dating services, where once you go on your first date (as recommended by OkCupid or Tinder), the dating service need not know anything about your relationship after that! They’ve “lost” you. In fact, talking to someone from the industry recently, I learnt that they do dating rather than marriage since in the former there is the hope of “repeat happy customers”.

It is similar with a service such as Airbnb, where once you’ve located a B&B you like, you can cut airbnb out of the deal from the next time on. Of course availability and stuff matter, but given how much in advance you book, a quick call to check availability is a small cost vis-a-vis the benefit of cutting out the middle man.

The beauty of Uber/Ola, however, is that it is impossible to do deals offline. Yes, after a ride, the driver and the passenger have each other’s numbers. But the next time the passenger wants a ride, the probability that the same driver is in the vicinity and free to give a ride is infinitesimal. So the passenger has to go to the app again. Moreover, it is the app that takes care of the pricing (using GPS, etc.) – something that is impossible to estimate if you try to cut out the app.

So when people say that they are building the “Uber for <some other service>”, in most cases it is not exactly the case – not all marketplace transactions are like Uber. For to be like Uber, you need to be an instant matching mechanism that changes the way the industry fundamentally operates; and you need a mechanism that keeps deals “online” by force.

Chew on it!

Rating systems need to be designed carefully

Different people use the same rating scale in different ways. Hence, nuance is required while aggregating ratings taking decisions based on them

During the recent Times Lit Fest in Bangalore, I was talking to some acquaintances regarding the recent Uber rape case (where a car driver hired though the Uber app in Delhi allegedly raped a woman). We were talking about what Uber can potentially do to prevent bad behaviour from drivers (which results in loss of reputation, and consequently business, for Uber), when one of them mentioned that the driver accused of rape had an earlier complaint against him within the Uber system, but because the complainant in that case had given him “three stars”, Uber had not pulled him up.

Now, Uber has a system of rating both drivers and passengers after each ride – you are prompted to give the rating as soon as the ride is done, and you are unable to proceed to your next booking unless you’ve rated the previous ride. What this ensures is that there is no selection bias in rating – typically you leave a rating only when the product/service has been exceptionally good or bad, leading to skewed ratings. Uber’s prompts imply that there is no opportunity for such bias and ratings are usually fair.

Except for one problem – different people have different norms for rating. For example, i believe that there is nothing “exceptional” that an Uber driver can do for me, and hence my default rating for all “satisfactory” rides is a 5, with lower scores being used progressively for different levels of infractions. For another user, for example, the default might be 1, with 2 to 5 being used for various levels of good service. Yet another user might use only half the provided scale, with 3 being “pathetic”, for example. I once worked for a firm where annual employee ratings came out on a similar five-point scale. Over the years so much “rating inflation” had happened that back when I worked there anything marginally lower than 4 on 5 was enough to get you sacked.

What this means is that arithmetically averaging ratings across raters, and devising policies based on particular levels of ratings is clearly wrong. For example, when in the earlier case (as mentioned by my acquaintance) a user rated the offending driver a 3, Uber should not have looked at the rating in isolation, but in relation to other ratings given by that particular user (assuming she had used the service before).

It is a similar case with any other rating system – a rating looked at in isolation tells you nothing. What you need to do is to look at it in relation to other ratings by the user. It is also not enough to look at a rating in relation to just the “average” rating given by a user – variance also matters. Consider, for example, two users. Ramu uses 3 for average service, 4 for exceptional and 2 for pathetic. Shamu also uses 3 for average, but he instead uses the “full scale”, using 5 for exceptional service and 1 for pathetic. Now, if a particular product/service is rated 1 by both Ramu and Shamu, it means different things – in Shamu’s case it is “simply pathetic”, for that is both the lowest score he has given in the past and the lowest he can give. In Ramu’s case, on the other hand, a rating of 1 can only be described as “exceptionally pathetic”, for his variance is low and hence he almost never rates someone below 2!

Thus, while a rating system is a necessity in ensuring good service in a two-sided market, it needs to be designed and implemented in a careful manner. Lack of nuance in designing a rating system can result in undermining the system and rendering it effectively useless!

Why the proposed Ola-TaxiForSure merger is bad news

While a merger intuitively makes economic sense, it’s not good for the customers. The industry is consolidating way too fast, and hopefully new challengers will arise soon

Today’s Economic Times reports that Ola Cabs is in the process of buying out competitor TaxiForSure. As a regular user of such services, I’m not happy, and I think this is a bad move. I must mention upfront, though, that I don’t use either of these two services much. I’ve never used TaxiForSure (mostly because I never find a cab using its service), and have used Ola sparingly (it’s my second choice after Uber, so use it only when Uber is not available).

Now, intuitively, consolidation in a platform industry is a good thing. This means that more customers and more drivers are on the same platform, and that implies that the possibility of finding a real-time match between a customer who wants a ride and a driver who wants to offer one is enhanced. The two-sided network effects that are inherent in markets like this imply super-linear returns to scale, and so such models work only at scale. This is perhaps the reason as to why this sector has drawn such massive investments.

While it is true that consolidation will mean lower matching cost for both customers and drivers, my view on this is that it’s happening too soon. The on-demand taxi market in India is still very young (it effectively took off less than a year back when Uber made its entry here. Prior to that, TaxiForSure was not “on demand” and Ola was too niche), and is still going through the process of experimentation that a young industry should.

For starters, the licensing norms for this industry are not clear (and it is unlikely they will be for a long time, considering how disruptive this industry is). Secondly, pricing models are still fluid and firms are experimenting significantly with them. As a corollary to that, driver incentive schemes (especially to prevent them from “multihoming”) are also  rather fluid. The process of finding a match (the process a customer and a driver have to go through in order to “match” with each other), is also being experimented with, though the deal indicates that the verdict on this is clear. Essentially there are too many things in the industry that are still fluid.

The problem with consolidation at a time when paradigms and procedures are still fluid is that current paradigms (which may not be optimal) will get “frozen”, and customers (and drivers) will have to live with the inefficiencies and suboptimalities that are part of the current paradigms. It looks as if after this consolidation the industry will settle into a comfortable duopoly, and comfortable duopolies are never great for innovation and for finding more optimal solutions.

Apart from the network effects, the reasons for the merger are clear, though – in the mad funding cycle unleashed by investors into this industry, TaxiForSure was a clear loser and was finding itself unable to compete against the larger better-funded rivals. Thus, it was a rational decision for the company to get acquired at this point in time. From Ola’s point of view, too, it is rational to do the deal, for it would give them substantial inorganic growth and undisputed number one position in the industry. For customers and drivers, though, now faced with lower choice, it is not a great deal.

This consolidation doesn’t mean the end, though. The strength of a robust industry is one where weak firms go out of business and new firms spring up in their place in their attempt to make a profit. That three has become two doesn’t mean that it should remain at two. There is room in the short term for a number three and even possibly a number four, as the Indian taxi aggregation industry tries to find its most efficient level.

I would posit that the most likely candidates to emerge as new challengers are companies such as Meru or EasyCabs, which are already in the cab provider business but only need to tweak their model to include an on-demand component. A wholly new venture to take up the place that is being vacated by TaxiForSure, however, cannot be ruled out. The only problem is that most major venture capitalists are in on either Uber or Ola, so it’s going to be a challenge for the new challenger to raise finances.

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I’m game for such a venture, and come on board to provide services in pricing, revenue management, availability management and driver incentive optimisation. 🙂
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