Predatory pricing in multi-sided platforms

Over the last few days, living and commuting in Nuremberg, I realised that I was not missing Uber. While just about a month ago, commuting for a week in suburban Paris, I was completely dependent on Uber for even the shortest of distances. The penetration of public transport and my familiarity with the city of Nuremberg aside, I began wondering how would Uber price its services in a city like Nuremberg (when it enters here, which I doubt very much would happen in the next few years), where public transport is omni-present, efficient, and affordable. It surely should adopt predatory pricing.

In this post, I will elaborate on the concept of predatory pricing in the context of multi-sided platforms.

Theory alert! If you are uncomfortable with theory, skip directly to the illustration and come back to read the theory.

What is predatory pricing?

Economists and policy makers concerned about market efficiencies and fair competition have been obsessed with the concept of predatory pricing for a long time. The most common definition of predatory pricing is through the application of the conventional Areeda-Turner test. Published way back in 1975, in spite of its limitations, most countries and courts have used it consistently, due to, in some ways, lack of any credible alternative.

The Areeda-Turner test is based on two basic premises. The recoupment premise states that the firm indulging in predatory pricing should be able to predict and be confident of its ability to recoup the losses through higher profits as competition exits the market. The assumption is that the firm could reasonably anticipate the (opportunity) costs of predatory pricing, as well as have an estimate of the future value of monopoly profits; and the net present value of such predatory pricing to push competition out of the market should be positive and attractive. In plain English, the firm should be able to project the effect of lower prices in terms of lower competition and higher profits in the future.

How low can this predatory price be? That is the subject of the second premise – the AVC premise. The firm’s prices (at business as usual volumes) should be below its average variable costs (AVC), or marginal costs in the short run. If the prices were indeed above the AVC, the firm would argue that they are indeed more efficient than competition, due to any of their resources, processes, or organisational arrangements. It is when the price falls below the AVC that the question of unfair competition arises – the firm might be subsidising its losses.

Take for instance, a start-up that is piloting an innovative technology. It may price its products/ services at a price below the AVC to gain valuable feedback from its lead users, but in the absence of a recoupment premise such pricing might not qualify as predatory pricing. On the other hand, imagine a new entrant with superior technology who can bring costs down to a level where the prices fall below the marginal costs of the competitors but stay well above the firm’s AVC, it is just disrupting the market.

Only when both the conditions are met, i.e., when the predator’s prices are below the AVC and the firm could project the extent of recoupment due to monopoly profits as competition exits the market, that we call it predatory pricing.

Predatory pricing in MSPs

There has been a lot of discussion about how ecommerce firms in India have been indulging in predatory pricing and how various platforms have been going under. I had written about subsidies and freebies from a consumer perspective a few months ago (Free… continue hoyenga). Let us discuss how and why it is difficult to assess if a lower-than-competition price is indeed predatory in the context of multi-sided platforms (MSPs).

  1. Multi-sided platforms have a unique problem to solve in their early days, that of network mobilisation. A situation that is like a chicken-egg problem, or a Penguin problem, where “nobody joins unless everyone joins” is prevalent in establishing a two-sided or multi-sided platform (for more details about the Penguin problem and network mobilisation strategies, read my earlier post here). In order to build a sufficient user base on one side, a common strategy is to subsidise, even provide the services free.
  2. Another common feature of MSPs is the existence of subsidy-sides and money-sides of users. The platform might subsidise one side of users and make money from the other side, while incurring costs of providing services to both sides, depending on the relative price elasticities and willingness to affiliate with the other side of the platform. And the prices for the subsidy side would surely below costs for that side. It is imperative that the overall costs and prices are considered while analysing these pricing strategies.
  3. These cross-side network effects will surely force the platforms to price their services most efficiently across both the sides. Even for the money side, the platform might not be able to charge extraordinary prices as such prices would themselves act against the sustenance of these cross-side network effects. It is likely that these extra-normal profits would evaporate through subsidies on the other side to keep the network effects active. Imagine a situation where a B2B marketplace charged the sellers higher than normal prices, only large (and desperate) sellers would affiliate with the marketplace, leading to buyers (the subsidy side) leaving the platform. In order to keep the buyers interested, the marketplace might either have to broaden the base of sellers by optimising the prices, or provide extraordinary subsidies to the buyers to keep them interested. So in order to maintain the equilibrium, the platform would have to price the sides efficiently.
  4. Finally, in a competitive situation, not all competitors might follow the same price structure. So, a reduction of prices by one competitor for one side of the market may not force all other competitors to reduce prices; they may just encourage multi-homing (allowing users to use competitive products simultaneously) or manipulate the price on the other side of users.

So, a direct application of the Areeda-Turner test might not be appropriate while studying predatory pricing in the context of MSPs.

An illustration

Let us imagine a market for home tutors supporting school students. The market is inherently geographically constrained; it is very unlikely that either the teacher or the student would travel across cities for this purpose. For the time being, let us assume that there is no technology (like video conferencing) being used.

This market is apt for the entry of a multi-sided platform, like LocalTutor. This firm provides a platform for the discovery and matching of freelance tutors with students. LocalTutor monetises the student side by charging a monthly fee (that includes a platform commission), and passes on the fees to the tutor. We need to make two assumptions before we proceed with competitive entry and predatory pricing: the market is fully penetrated (all the students who are looking for tutors and tutors looking for students are all in the market) and there are no new students and tutors entering the market; and there are no special preferences between student-tutor matches, i.e., the student-tutor pair does not form a bond like a sportsperson-coach, where they begin working like a team. In other words, the tutor is seamlessly (with no loss of efficiency) replaceable.

Now imagine a new competitor enters the market and engages in predatory pricing to kick-in network effects. The new entrant, let’s call it GlobalTutor (a fictitious name), drops the student-side prices to half. In order to attract the right number and quality of tutors, GlobalTutor has to sustain the same fees that LocalTutor provides its tutors, if not more. So, it starts dipping into its capital reserves and begins paying the tutors the market rates while reducing the student fees. Anticipating a larger surge in student numbers, more tutors sign up to GlobalTutor, and seeing the number and quality of tutors on GlobalTutor (at least if it is not inferior to LocalTutor), students first start multi-homing (use both services for their different needs, like LocalTutor for mathematics and GlobalTutor for music classes), and some of them begin switching.

In a fully penetrated market, the only way for LocalTutor to compete is to respond with its price structure. It has two options – reduce the student-side prices to restrain switching and multi-homing behaviour; and tweak the tutor-side prices and incentives. The first option is straightforward; it is cost-enhancing and profit-reducing. The second option (which is not available for pipeline businesses) is interesting in the context of platform businesses.

There are various ways of responding to this threat. The intent is to arrest switching and multi-homing behaviour of tutors and students from LocalTutor to GlobalTutor.

  1. Increasing multi-homing costs of tutors by providing them with incentives based on exclusivity/ volume: Like what Uber/ Ola provides its drivers – the incentives kick-in at what the company believes is the most a driver can do when they do not multi-home. In other words, if you multi-homed, drove your car with both Ola and Uber, you would never reach those volumes required to earn your incentives in either of your platforms.
  2. Contractual exclusion: This might not be tenable in most courts of law, if these freelance tutors were not your ‘employees’. Given the tone of most courts on Uber’s relations with its driver-partners (drivers’ lack of control in most of the transaction decisions including choice of destination, pricing, and passenger choice), any such contracting would imply that the tutors would be employees, and that would significantly increase the platform’s costs (paying for employee benefits are always more expensive than outsourcing to independent service providers).
  3. Increase contract tenure: LocalTutor may increase multi-homing and switching costs by increasing the tenure of the contracting from monthly to annual. Annual contracting will reduce the flexibility that students and tutors have, and might result in reduction in volume.
  4. The next options for LocalTutor are to work at the two restraining assumptions we made at the beginning – penetration and perpetual matching. LocalTutor might want to add in more and more students and tutors and expand the market, providing unique and differentiated services like art & craft classes, preparation for science Olympiads, or other competitive tests. LocalTutor might also communicate the value of teaming of student-tutor pairs in its success stories, in a bid to dis-incentivise switching and multi-homing.

To predate or not to predate is not the question

Given the differences between pipeline and platform businesses new entrants seeking to mobilize network effects have very little option but to resort to predatory pricing. The choice is not if, but how. And as an incumbent, should you be prepared for a new entrant who would resort to predatory pricing? Surely, yes! And how? By being ready to expand the market and increasing switching and multi-homing costs. Unlike in the tutoring business that is inherently geographically constrained, a lot of businesses could span across markets. Even tutoring could leverage technology to reach a global audience.

Just one comforting thought, predatory pricing as a strategy to eliminate competition is inefficient in the long run. The new entrant might adopt predatory pricing to eliminate competition in the short run, but the act of predatory pricing breaks down most barriers to entry, and sends signals to others that there is a market that is easy to enter. It might attract a more highly capitalised competitor to enter the market with the same strategies … making the market a ‘contestable market’. And no one wants to make a fortune in a contestable market, right? More on competing in contestable markets, subsequently.

Cheers

© 2017. R Srinivasan

 

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Hindsight and foresight in judgments under uncertainty

As I began reflecting on my earlier posts on You are intelligent: have you done something dumb? and Judgments, I rolled back to this classic article, so beautifully titled, Hindsight ≠ foresight. Written by B Fischhoff, way back in 1975, this paper provides two intuitive results (at least in hindsight): once the outcome of an event is known, people associate higher probability of its occurrence; and people were unaware that they have been influenced by hindsight (the knowledge of what actually happened).

Case class in a business school – hampered by hindsight bias

Take a business school case class for instance. As a case teacher, I face this a quite a lot of times. In a typical strategy cases, the primary question to the class is “what should the company do?” And since most cases are set a few years in the past, simple Internet search (by the students as part of their class preparation) would have informed them about what had actually happened. Given that students come into class with this hindsight, they try very hard to fit their preparation and theoretical arguments to the actual outcome, however irrational, or improbable it might have been. A good management teacher ought to therefore provide for this “hindsight bias” in  students and ensure that a fair discussion happens in class on all possible outcomes.

Should I therefore, as a management teacher, provide my students with only cases for which the outcomes were not known? What therefore are my criteria to choose cases for a class? Do I fight to eliminate this “hindsight bias”? Let me come back to this later.

An air-crash investigation

Let us take another example. A special team has been tasked with investigating the cause of an air crash. Any investigation of an accident would inevitably entail putting together pieces of information to arrive at a causal relationship between the antecedent factors and the event, which is known to have happened. It is impossible to eliminate the source of bias here, the event. The investigation team has to be trained to create a counter-factual (good) outcome from the evidence at hand. They need to recreate the antecedents to the event in a manner that they evaluate if anyone in their place would have made the same decisions as the actors (pilots and crew who made certain decisions) did. Experimentally, it is akin to creating a control-group that knows all the facts leading up to the case, but not the actual outcome.

Investigating white-collar crime

In the case of white-collar crime, especially when it involves financial fraud, another significant factor interferes with hindsight bias, the size or impact. Larger frauds are fraught with more pronounced biases. Media coverage on “select” white-collar crimes are testimony to such biases. Nicholas Bourtin (read the article here), adds how armed with hindsight bias, financial crime investigators might ascribe malicious intent to even innocent mistakes or poor judgement.

As I was thinking about this issue, I just saw the breaking news of an earthquake of 7.2 magnitude hitting the Iraq-Iran border (Sunday, 12th November 2017). Hopefully, there isn’t much damage. And it triggered a thought.

Fighting hindsight bias – learning from geophysics

A great learning for fighting hindsight bias comes from geophysical studies. Imagine how geologists and geophysicists study earthquakes and volcanic eruptions. These are events that just “happen”, and then the scientists “reconstruct” the events through carefully collected data. Can we learn something from the way they fight hindsight bias? Sure.

Strategy #1: Conduct stability studies. Not just fault studies, but stability studies. Take the context of highly quake-prone areas, and go study why earthquakes aren’t happening! Such data would provide the ‘normal’ distribution of data with the occurance of earthquakes being the outliers.

Strategy #2: Broaden the search. Take all retrospective data for analysis. Study all the quakes that happened on a plate/ all eruptions of a volcano. Such events may occur very infrequently, and may be randomly distributed over time. However infrequent they may be, it would be worthwhile to study the antecedent conditions every time. Maybe, one can find a cause-effect relationship. Like concluding that most road accidents happen between 2.00am and 4.30am because there is a high likelihood of drivers sleeping behind the wheel (that is if they are still being driven by human drivers!).

Strategy #3: Combine the two, and seek patterns. Conduct stability studies and say why events do not happen, and conduct (with big data) longitudinal studies to infer why events do happen. Combine the two and create patterns. Such patterns can be immensely helpful in studying antecedents of events, and effectively fighting hindsight bias.

Fighting hindsight bias – applying it in managerial judgement

Straight, let us try and apply the learning from geo-physics to managerial judgement. First, consider prior probabilities of an event happening appropriately. Imagine an angry boss (no, I would like to believe that all bosses are not always angry!). In trying to understand what angered her today, use prior probabilities appropriately. She may be angry because she was being held accountable for something beyond her control (like your productivity), or just that she gets angry when she is frustrated about not being able to communicate or convince others. Strategy #1: ask yourself, when is she ‘not angry’? She is not angry when you complete your work on time, when you present your work properly (as she likes it), and when your work is of good quality. Then why is she angry today? You have the answer.

Second, stop thinking sample size and probability. Unless you have a really large sample size of such events, stop thinking about probability. Imagine predictions in sport or financial services. I was taught in my first finance classes, “past performance is not an indication of future performance”. And my brief indulgence with sports tells me that the law of averages is that “sustained good performance does not last long”. Would you be confident in predicting the goals scored by a football team if their prior performances were [4-1, 3-0, 5-2, and 1-0] or [1-4, 4-2, 2-2, 1-0] with the second number in each pair representing the goals scored by the opposition? Most would be confident of predicting the performance of the former scoring pattern than the latter. It might just happen that the next game is against the league leader (including someone with initials of CR7) and all these performances do not matter at all. You really need to collect loads of data on each team’s performance, including historical performances of all the opposition teams before you make any predictions.

Third, stay away from causal relationships (no I did not say casual relationships!), unless you have really “big data” on both the normal distribution of the event not happening, as well as the outlier chance of the event happening. Remember the wonder batsman, Pranav Dhanawade, the 17-year old kid who scored 1009* runs for his local cricket team. After a few years, his father has decided to return the scholarship he received, since he has not performed up to expectations (read it here). It was important that when an event of this nature (an extraordinary performance) occured, one needs to not just reward, but also invest in nurturing the talent. Without an adequate support structure to hone his talent, the financial reward was insufficient to sustain even acceptable performance.

So why do some firms perform better than others?

The answer may not lie in analyzing why those performed better, but in understanding what the others do that make them not perform as well as the high performers; longitudinal and cross-sectional (big) data on multiple firms’ performance; and being very cautious about making causal assertions. Isn’t this the core of strategy research, today?

Cheers!

(c) 2017. Srinivasan R

 

You are intelligent: have you done something dumb?

One of my colleagues does her research on strategic thinking and in one of our conversations we discussed what is critical thinking, and how is it different from other concepts that are commonly used in management and leadership education. I chanced upon the research by Heather A. Butler (California State University Dominguez Hills) on the difference between intelligence and critical thinking. In this piece provocatively titled, Why do Smart People do Foolish Things?, she argues that intelligence and critical thinking are different. In this blog post, I will discuss how intelligent people should/ can acquire critical thinking skills.

Intelligence vs. critical thinking

Intelligence is measured through standardized tests like the IQ test that measures skills like visuo-spatial skills, calculations, pattern recognition, vocabulary and diction, and memory. Intelligence therefore, arms people with the ability to solve problems.

Critical thinking on the other hand is the ability to rationally think in a goal-oriented fashion, and a disposition to use those skills when appropriate. It has been defined as “the intellectually disciplined process of actively and skilfully conceptualizing, applying, analysing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication, as a guide to belief and action. In its exemplary form, it is based on universal intellectual values that transcend subject matter divisions: clarity, accuracy, precision, consistency, relevance, sound evidence, good reasons, depth, breadth, and fairness” (Michael Scriven & Richard Paul, 1987). In simple words, critical thinking is about questioning both information and beliefs, and using that questioning to guide behaviour. It is that ability to ensure the quality and consistency of information that forms the bedrock of critical thinking. While intelligence is about pattern-seeking and projection, critical thinking is about questioning the quality of information.

What intelligence creates is smartness. But that does not ensure that smart people don’t do stupid/ foolish things. Who hasn’t heard of intelligent Albert Einstein cutting two holes in the door for large cats and small cats? I am not going to tell any stories of all those stupid and foolish things I have done! If you were waiting for it, I am equally flattered (thank you for acknowledging that I am intelligent!), but I am going to disappoint you.

Developing critical thinking skills

Critical thinking creates rational thinking. The way a critical thinker would solve problems would be very different than someone with just intelligence. I conceptualize critical thinking as a skill over and above basic intelligence. Critical thinking encompasses “reflective and reasonable thinking” that is focused on defining “what to believe or do”. Defining “what to believe and do” requires three core skills – deduction, induction, and value-judging. Deduction is the process of making inferences based on a general statement, a set of hypotheses, and statements. The inference is based on a general theory of science, and is a top-down process. So, what is true of a class of things/ events in general, is true for each of the components. Therefore, if you were a German, you would be punctual.

Induction on the other hand, is bottom-up; where a set of data and observations from the ground will help make the inference. Data is collected, patterns sought, and from these patterns the theory is generalized. The key in inductive inference making is the collection of right quality and quantity of data to make good inferences.

The third and most important component of critical thinking skills is value judging. While it is easy to teach and train people on deductive and inductive reasoning, value judging is very difficult. Value judgement is an assessment of something good or bad, given one’s realities and priorities. At the definitional level, value judgements are made independent of data – these are value judgements. However, critical thinking as a competence integrates deduction (top-down inference making), induction (bottom-up inference making), and value judgements (assessment of good or bad).

As we define value judgements as “a choice of what we like or want” or “what is good or bad in this context”, it is very difficult to teach in a classroom, through any of traditional methods. In-situ experiential methods are required to train someone on making robust value judgements. Internships, externships, and apprenticeships are some useful methods for teaching/ training value judgements. Do you now realize why certain professions are called ‘practice’ – like law, consulting, or accounting?

Why should I learn critical thinking?

Critical thinking helps you in many ways. One, it helps you remain goal-directed. Armed with critical thinking skills, everyone will collect, collate, and make inferences based on what is good/ desirable for them. In the absence of critical thinking (all of deductive-inductive-value judgement or DIVj), one might not be able to make inferences in relation to the goal. For instance, if my objective is to choose an investment plan, I need to surely invest in a manner that matches my financial goals; and DIVj surely helps.

Two, critical thinking allows you to be flexible thinkers and evolve into amiable sceptics. It would not be easy to convince you in the absence of good theory (deductive), solid data (inductive), or goal-directed behaviour (value judgements). You are most unlikely to be swayed away by mob beliefs and unscientific arguments.

Three, critical thinking helps you be aware and accept your conscious and unconscious biases (including hindsight and confirmation biases).

Practising critical thinking

It is therefore important for you as a smart person to learn and practise critical thinking. Practising critical thinking is about consciously using deductive, inductive and value judgements. I know a lot of managers we train at our business schools with deductive and inductive skills, but much less of value judgements. One of my favourite arguments for the case method of learning is that it is the closest it gets to training people to make value judgements (read my earlier post on Judgements).

Some may argue that intelligence is part genetic and you may be born with or without intelligence. On the other hand, critical thinking is surely developed; albeit only through conscious efforts. Here’s calling all intelligent and smart people: to go out there and acquire/ practise critical thinking.

(c) 2017. R Srinivasan

 

Business biographies

I was invited to speak at the Bangalore Business Literature Festival 3.0 (http://bangalorebizlitfest.org) yesterday. I prepared some notes, but true to my style, spoke mostly impromptu. It was a great opportunity to meet with writers I read regularly, as well as a lot of aspiring writers. No, I am not a prolific business writer, in fact, I have not written a single business biography yet. I wondered why I was drafted in as a speaker in the session on business biographies and management education. The moderator of my panel, my colleague Prof. Ramya Ranganathan clarified – I was in because I write cases and use firm biographies in my teaching and consulting. So, I thought I would begin by distinguishing between biographies of firms and biographies of individuals. Consequently, it is important to clarify these three words – biography, history, and a case.

Biographies of people and firms

In a panel before mine, a question was asked (to which the panelists had no answer, and it was part of my preparation!): in writing a biography, how do we separate the founder from the firm (especially in the case of a startup)? As a significant part of my classroom conversations, I separate the two explicitly. When you write and analyse a set of events in the form of a chronology, it is very difficult to separate the person from the firm. If you want to chronicle a firm biography, it is important to slice the narrative across specific decisions. Say a diversification decision could be narrated as a specific chapter bringing in the environmental context, how it was perceived by the leaders, how and what strategic change was initated, what were the implications of the change on the internal and external contexts, and if and when it achieved its intended purpose.

This way, writers can separate a firm biography from an individual biography, and highlight the idea that firms outlive (and outperform) people. As a strategy teacher, it is important for me and my class to focus on the firm independent of the strategist. And this distinction is critical to learning and application.

Biography, History, and Case

As a case writer (I want to believe that I have been prolific), I am continuously confronted with this distinction. And when I teach/ mentor colleagues on writing cases, I make sure I tell them that they are not writing a biography or history! So, it important to articulate the differences.

The purpose of a historical narrative is to recreate the context in the minds of the reader and inspire. Some exaggeration is acceptable; some glorification of the protagonist is expected; and therefore, triangulation of methods and validation of data are not that critical (though good history is based on well organized and validated data). The purpose is to present the reader with a interpretive representation of the context. The example that came to my mind yesterday was that of the imagery of the Rani Laxmi Bai of Jhansi. The job of a historian is to recreate an image of the Rani in the minds of the reader with his narrative. Every one (in my audience) may have heard of her, and having read the narrative/ heard stories about her, the readers would form an image of her in their own minds. It is inconsequential if she was right or left-handed; if she had 12 guards of 16; or if she indeed wore a saree as depicted in the imagery. What is important is to highlight the paradoxes – a woman warrier in a society and time when no woman fought in the frontlines; a saree-clad horse-rider; a lady carrying both a baby slung on her back and a sword in her hand; and the like. Symbols of bravery and obstinence. Period.

On the other hand, a biographer is expected to carefully validate all data and record them diligently. She is expected to present all aspects of the personality – the good, the bad, and the not so expected facets; from multiple perspectives, without judgement. The biographer cannot exaggerate, should not glorify, and should present the facts as they are without any interpretation. It is for the readers to make sense and take specific learning. It could be anything; like when Prof. V Raghunathan spoke yesterday, he said he picked up the idea that a man can do more work by sleeping only four hours per day, when he read the biography of Napolean (who apparently slept for four hours on horse back). Maybe, when I read the same biography, I would pick up something else, and you something totally different. No representations here.

A case is a decision-focused narrative. The purpose of a case is to emphasize how learning about a context can help students and learners from applying it other contexts. My colleague Prof. Rakesh Godhwani narrated a story yesterday. It was about the great imposter, Dr. Joe (made famous by the movie of the name: Catch me if you can), on how as MBAs we need to “fake it till we make it”. A member of the audience wanted to know the ending – did he get rewarded for saving lives, or did he go to jail for impersonation? As a case writer and management teacher, I would say, the ending does not matter. What matters was the criteria to make the decision, not the actual decision. Therefore, good cases do not need to be neat and complete. Then are non-comprehensive accounts of events and antecedents leading to a decision.

Therefore, the historian would create an imagery of the Rani of Jhansi, the biographer would focus on her valor, while the case writer would discuss the context of why she was at all required to fight (in the context of British India’s Doctrine of Lapse).

Celebrating the also-rans

I called the audience to write about firms that were also-rans. Success has many fathers; and these days, even failures have enough parents. In fact, I was proud of the fact one of my first cases as an academic was about India’s first ecommerce firm (way back in the year 1999), Fabmart.com; and in one of the panels yesterday the co-founder of Fabmart.com, Mr. K Vaitheeswaran was speaking about how the firm failed subsequently and his coping with that failure (read about his book, Failing to Succeed, here).

However, there is little focus on the also-ran firms. Since a majority of our students are also-rans who make their careers in also-ran firms, it is important to study them. It is important to study how these firms perceive the environment, adapt/ adopt, make strategic shifts, learn/ unlearn, pivot, take feedback, measure impact and performance, and go round and round in circles! Developing, what we strategy researchers call, dynamic capabilities. These bios are extremely valuable for the management researcher.

So, the next time you hear about a firm that is neither a success or a failure, remember that there is a lot to learn in terms of processes, routines, and dynamic capabilities from them.

Cheers.

(c) 2017. R Srinivasan.

PS: Edited Prof. Rakesh Godhwani’s coordinates and the name of the movie he referred to (Catch me if you can) on 11 Sep 2017.

Changed the featured image: 21 Sep 2017.

Judgments

This is that time of the year when Indian business schools welcome their new students. As a self-proclaimed proponent of the case method of learning, I am often invited by my school to teach a session on “case method of learning” to the first year students. And one of my key messages to one such group of students this year was this: “a lot of what you will learn in the business school in terms of content, can be read from a variety of sources; what you will learn in class through continuous, repeated practice is the ability to make sound judgments.” This post is an elaboration of my understanding of the role ‘judgments’ play in business and life.

Judgment: what is it, anyway?

In the legal world, a decision made by a ‘learned Judge’ after hearing out all the arguments from all parties involved. The judge makes up her mind after providing equal and fair opportunity to all concerned parties to present their points of view; a detailed analysis of the evidence presented; collating expert opinions; gleaning through precedents and cognizant of the opportunity of this particular decision setting a precedent; and keeping the law of the land as well as the changing (socio-economic) contexts. When a judge presents a judgement, it provides a guideline for what is good/ bad; preferable/ not-preferable; acceptable/ not-acceptable in that particular context. To that extent, there is a subjective evaluation of the options, given the specific context; and a specific preference for one course of thought/ action over another.

Is it different from decision-making?

At a basic level, a judgement is a decision. But it is more than a just a decision. A decision by definition is a choice. Professor William Starbuck famously distinguished policy making (where resource allocation is a continuous process) from decision-making as ” … the end of deliberation and the beginning of action” (for more details on this quote, and in general, a history of decision-making, read this classic HBR article).

I see the primary difference between decision-making and judgement as managing risk and uncertainty. In his classic book titled “Risk, Uncertainty, and Profit”, Frank Knight (1921) defined uncertainty in a situation where the outomes could not be comprehensively enumerated and the probabilities of their occurances cannot be estimated. On the other hand, risk is a situation where all possible outcomes could be listed and the probabilities may be calculated.

Instructions and advice

One of my favourite assertions in my case learning sessions is the difference between instructions and advice. Instructions as we all know are directions for performing an activity step-by-step, a sort of a standard operating procedure. No thinking involved here – just go ahead and do what is written up/ told to. Whereas advice is contextual. Someone tells you, “it worked for me/ others in a similar context, you may try it yourself”. Of course, this implies that if your context is different, feel free to ignore/ adapt. Isn’t that why advice is always free?!

I bring in an example of how a little boy is taught to cross the street. Imagine his mother’s instructions: “before you cross the street at the zebra crossing, look for the policeman at the intersection; and when he signals you to cross, run across the street as fast as you can!” Wonderful … as long as the context is fixed. What happens if at the intersection, there is no policeman … does the boy keep waiting? What happens if the policeman does not notice him waiting to cross the street? Of what happens when the policeman signals him to cross the street, but a car is speeding towards him? What happens if …. ? Here is where judgements come in handy. Instead of providing him instructions to cross the street, his mother should develop judgement skills in him.

Imagine how you cross the street … if any of you have tried crossing the street in India, you know it better. I distinctly remember when my German colleagues while attending a conference in India, had a harrowing time crossing streets! When you cross the street, you look both sides of the road, spot a car a fair distance away (163m farther), driving relatively slow (at 26 km per hour). You estimate that at your speed of walking (4.5 km per hour), you will be able to cross the 80ft wide street a well 29.5 seconds before the car crosses the point where you intend to cross. You get the point, right? Nobody does all these calculations, we know it. Decision scientists call it intuition, gut, judgements.

It is developed through practice, accumulated through experience, and through active experimentation. Acculturation through socialization and mentoring may help in developing judgements; but no guarantee that just by repeating an action again and again, one would develop judgement. Apart from this practice and experience, a critical component of judgement is intent. Plus, an ability to weigh the pros and cons (in almost real time), as is in decision-making.

Intent in Judgement

One needs to have a specific intent to learn from experience. It is very likely that someone can continue to do an activity repeatedly without developing a sense of judgement. Something like a rote learning or Pavlovian Conditioning. How many times have you experienced people doing the same activities again and again not knowing why they are doing it, and why that way? Inefficient bureaucracies are built on the separation of thinking from doing; the doers are refrained from thinking … they are told to just do, and suspend thinking. Imagine blue-collared workers in the Taylorian world, or even BPO workers, or some customer service executives in modern-day organizations. It requires concerted intent to learn judgement.

Will I lose my job to automation?

The question in most cases is not if, but when? Judgement has never been more important as it is today. Roles where judgements are not required, activities that can be codified into detailed processes (where all possible outcomes can be enumerated and probabilities calculated), automation will take over. Bots and robots dominate the internet world today. Almost every website that has a customer interface has a bot running … and sometimes the responses could be hilarious. For instance, an airline customer thanked an airline sarcastically for misplacing his luggage and the airline responded with a big thanks for his compliment. Obviously, the sarcasm was lost on the automated response. The machine could not “learn” enough. And the entire twitterati took over (read about it here).

We live in a world today where the buzzwords include “big data”, “analytics”, “business intelligence”, and “artificial intelligence”. I recently saw a cartoon on a blog (futurethink.com.sg) that I can relate to very well.

Artificial-Intelligence-and-Real-Intelligence

As machine learning, automation, robotics, and augmented reality dominate our industrial vocabulary, natural intelligence and human judgement should take centrestage in our discourse.

Learning judgement

My advice to budding managers, invest in learning judgement-making. Consciously, with intent. Practise, make mistakes, experiment. Define outcomes and build expertise. After all, what you want to make out of your life and career depends on your judgement, right?

Cheers.

(c) 2017. R Srinivasan.

 

App-in-app?

I recently got an email from my airline app that I could book my car ride within the same app. It was a way of providing end-to-end services. Much like the home pickup and drop service provided for business class customers by the Emirates. What are the implications of these for the customer, the airline, and the cab-hailing firm? Let’s explore.

It is an app-redirect

First, read the terms of how it works in the case of Jet Airways and Uber here. The substantive part of the T&C is hidden in the paragraphs quoted below:

“PLEASE NOTE, YOU ARE MAKING THE PAYMENT TO UBER DIRECTLY. JET AIRWAYS IS NOT RESPONSIBLE / INVOLVED IN THIS FULFILMENT PROCESS. JET AIRWAYS WILL NOT BE LIABLE AND/OR RESPONSIBLE FOR REFUNDS, DELAYS, REJECTIONS, PAYMENT AND FULFILLMENT OR OTHERWISE OF THE SERVICES OR IN RESPECT OF ANY DISPUTES IN RELATION THERETO, IN ANY MANNER WHATSOEVER.” (emphasis original)

Then, what is the value of this app-in-app integration?

Customer perspective

For the customer, it has the potential to work as a seamless end-to-end service. I imagine a future, where you would find a partner using Tinder or TrulyMadly, plan your evening to a game/ movie using BookMyShow, find a restaurant & book your table using Zomato, and take Uber whenever you are ready to move on, or better still, have an Ola Rentals car waiting for you through the evening. All in one app. Wouldn’t you love it, if all of it were integrated in one App? Just imagine the convenience if your restaurant-finder knew that you are in a particular concert at a specific place and you are likely to head out for dinner at a particular time. This specific knowledge could immensely help your restaurant-finder app to customize the experience for you – for instance, it could not only provide you those restaurant options that are open late in the evening after the concert was over, in a location that is close to the venue; it could possibly alert the restaurant that you were arriving in 15 minutes, based on your Uber location. And through the evening, post your pictures on Instagram and SnapChat, check-in to all those locations in Facebook, and Tweet the experience live.

Yes, you would leave a perfect trail for the entire evening in a single place, and if you were to be involved in an investigation, it would be so easy for the officer to trace you! No need for Sherlock Holmes and Watson here – the integrator app would take care of all the snooping for you!

Convenience or scary? What are the safeguards related to such data sharing across different entities? How will the data be regulated?

The Integrator perspective

Why would a Jet Airways provide an Uber link inside its App? Surely cab-hailing and air travel are complementary services. Plus, Jet Airways believes that its customers would find it convenient to book an Uber ride from within the Jet Airways app, as they trust the app to provide Uber with all the relevant details – like the estimated landing/ boarding time of the flight, drop/ pickup addresses, etc. Jet Airways also needs to believe that its customers would rather choose an Uber cab, rather than its competitor OLA Cabs, or any other airport taxi service. The brands should have compatible positioning. Given that Jet Airways is a full service carrier, and differentiates based on its service quality, Uber might be a good fit. But the same might not hold good for a low-cost/ regional carrier like TruJet connecting cities like Tirupati, where Uber does not operate.

Does integrating complementary services affect customer satisfaction, brand loyalty, customer switching costs, and/or multi-homing costs? In contexts where these services and brands are compatible, and there is a convenience involved in sharing of data between these services, there is likely to be some value added. Like airlines and hotels (hotels would like to know your travel schedule); currency exchanges and international travel (the currency exchange would love to know which countries you are visiting); or international mobile services. If there was no data to be shared between the complementary services, the user would rather have them unbundled. Think travel and stock brokerage.

That said, platforms find innovative complementarities. For instance, airlines (primarily the full-service carriers) have launched co-branded credit cards. In a recent visit to Chennai, there were more American Express staff at the Jet Airways lounge than the airline or lounge staff! And they were obviously signing up customers. What are the complementarities between credit cards and air travel, apart from paying from that card? A lot of business travellers have their business travel desks do the payments; consultants have their clients booking the tickets; and even for individuals and entrepreneurs, the credit card market is so fragmented that everyone holds multiple cards. And the payment gateways accept all possible payment options, including “paying cash at the airport counter”. They why co-brand credit cards – sharing of reward points/ airline miles. Either customers do not earn sufficient airline miles and using these co-branded credit cards help them earn more miles and retain/ upgrade their airline status (remember the 2009 movie, Up in the Air?); or they do not earn enough reward points in using their credit cards that they can redeem their airline miles as credit card reward points. Either ways, each one is covering up for the other.

In this covering up, or more diplomatically consolidation of rewards, the partners increase customer switching and multi-homing costs. Surely, redeemable airline miles might be more valuable to a frequent traveller than credit card reward points that have limited redemption/ cash back opportunities. But for loyalty to increase, it is imperative that both brands stand on their own – providing compatible services.

Mother of all apps

All this looks futuristic to you? A lot of you have been using an ubiquitous desktop app known as the browser for a long time, which has been doing exactly this! In a subtle form, though. However, there are firms that own multiple such apps, and they use a single sign-on – like all of Google services. Plus, even third-party sites like Quora allow for using your Google credentials to sign-in. The trade-offs are not always explicitly specified – it is always the case of caveat emptor – consumer beware.

Quora homepage

So, the next time you experience some cross-marketing across platforms/ apps, think what data might be shared across both the apps; and if you would really value the integration.

Cheers!

(c) 2017. R Srinivasan

 

Beware the stupid!

During one of my random browsing through the internet on my mobile device, I came across an interesting set of laws – the basic laws of human stupidity. Yes, you read it right, stupidity. By Carlo M. Cipolla (read the original article here), an Italian-born former professor emeritus of economic history at University of California Berkeley. This is simply genius. This post is to help you find how these laws apply to the start-up ecosystem of today. Read on.

stupid001

The five laws

Let us first understand the five laws. The first law states:

Always and inevitably everyone underestimates the number of stupid individuals in circulation.

They are everywhere and appear suddenly and unexpectedly. Any attempt at quantifying the numbers would be an underestimation.

The second law states:

The probability that a certain person be stupid is independent of any other characteristic of that person.

There is serious diversity at act here. No race, gender, educational attainment, physical characteristics, psychological traits, or even lineage can explain the incidence of stupidity in a person. He says a stupid man is born stupid by providence, and in this regards, nature has outdone herself.

The third law is also labelled a golden law, and presents itself into a neat 2X2 matrix. It states:

A stupid person is a person who causes losses to another person or to a group of persons while himself deriving no gain and even possibly incurring losses.

This law classifies people in this world into four categories – the helpless, intelligent, the bandit, and the stupid. Organized on the two axes of gains for self and others, the helpless is fooled by others who gain at his expense; the intelligent creates value for himself as well as others; the bandit gains at the expense of others; whereas the stupid loses himself in the process of destroying others’ value.

Stupid003

While the actions of others are justifiable, it is the actions of the stupid that are so difficult to defend – no one can explain why he behaved that way.

While it is possible that people may behave intelligent one day, bandit another day, and helpless in another place and context; stupid people are remarkably consistent – they are stupid, irrespective. No rationality at all – just pure consistent. And that makes stupidity extremely potent and dangerous. For the simple reason that you cannot erect a rational defence against a stupid attack, as it comes as a surprise, and more importantly, there is no rational cause for the attack in the first place.

Which leads us to the fourth law, which states:

Non-stupid people always underestimate the damaging power of stupid individuals. In particular non-stupid people constantly forget that at all times and places and under any circumstances to deal and/or associate with stupid people always turns out to be a costly mistake.

Even intelligent people and bandits (who are rational) underestimate the probability of occurrence of stupid people, are genuinely surprised by the stupid attacks, and are at a loss to defend themselves effectively against stupidity. Given the inherent unpredictability of stupidity, it is both difficult to understand in the first place, and any attempts at defending against it may itself provide the stupid people with more opportunity to exercise his gifts!

Which leads to the fifth law, which states:

A stupid person is the most dangerous type of person.

And by corollary,

A stupid person is more dangerous than a bandit.

The danger of stupidity cannot be sufficiently understated than this law. Given the irrationality of stupidity, and the costs associated with stupid behaviour, a stupid person is far more dangerous than any other type of person. An intelligent person adds value to society, a helpless fool may transfer value from himself to others, a bandit may transfer value from others to himself; but the stupid erodes value to the society by executing a lose-lose strategy. There could be bandits who might border the stupid (someone who can kill a person for stealing $50 – the value they gain is lower than the value you lose; but the $50 for them is as valuable as life for you). But given the power of stupidity, they can create far more harm than one can even imagine.

Stupid002

The five laws of start-up world stupidity

  1. Stupid business models are aplenty – they rear their head everywhere, every-time. Irrespective of the context, they are omni-present. No exceptions at all. Do you remember business models like Iridium (by Motorola) and the FreePC experiment? It exists even today … Casper Tucker wonders why he should make his own IP redundant (read here).
  2. The probability of a stupid business model arising from a developed country, a venture of a large organisation, from the famed Silicon Valley (or Bangalore, Berlin, or Shanghai for that matter) is the same (and high). The start-up graves are littered with corpses of stupidity-induced deaths of both the firms, their investors, customers, and every other stakeholder you can think of. You think sandpaper for shaving or hair-removal is a bad idea, check this out!
  3. Do I need to tell you the costs of stupidity in the start-up world? I have come across founders who in the first few months of the business taking off, begin talking valuation rather than growth. In the process, they have destroyed value squarely and truly for everyone around them, including themselves. Nothing can match the stupidity of a founder who sacrificed his employment to start-up a firm, acquire customers and force them to make asset-specific investments, make wonderful investor presentations and get a few to invest as angels, PE, or VC; and then instead of worrying about making the business profitable, chase valuation. I surely have mentored a few, and do not want to name them for obvious reasons.
  4. The fourth law is the trick – stupid people thrive by their ability to surprise you by their conviction. And there are enough people who irrationally believe in them; but even the rational actors are unsure how to respond – till it all dawns on them. How many products listed in this article do you remember?
  5. And they are just plain dangerous – they can bring the entire ecosystem down. Remember how the Real Value Vaccummizer brought the entire innovative company down (do you know the firm was the first to introduce a portable fire extinguisher by the brand name Cease Fire, which by the way stays a generic name for portable fire extinguishers)?

So, customers and investors, start-up founders and entrepreneurs, students and researchers, and everyone else, beware the stupid.

Cheers!

© 2017. R. Srinivasan