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The Procrustean bed revisited: Ways to scale 'physical service' platforms

Prakash Bagri, Associate Professor (Practice), Marketing and Associate Dean - Corporate Engagement
Summary by Devidutta Mohanty, Manager CBM

The article “The Procrustean bed revisited: Ways to scale ‘physical service’ platforms,” article argues that in reality the tendency of new-age companies to ‘platformise’ physical services has yielded discouraging results (relative to their digital counterparts) for them and their investors.

It talks about how ‘physical service’ based platform companies have tried to force-fit the business model of digital product-based platform companies with a misplaced hope of capitalizing on the ‘network benefits.’ It highlights the challenges companies like Uber, Urban Company, etc., face in accruing these network benefits, and analyses the reasons for these issues.

Physical service platforms are also plagued by issues like disintermediation, platform leakage, and lack of loyalty.

Restricted Gains from Network Externalities: Physical service platforms cannot minimize the cost of delivery in a way fully digital platform businesses or even a platform like Amazon can purely because of the nature of the business. Also, the fact that the ‘delivery person’ or the ‘caregiver’ can only serve one customer at a time on physical service platforms doesn’t let such business take advantage of one-to-many and many-to-one network effects that companies like YouTube and Amazon fully utilize.
Imbalance between user value and platform performance: Physical service platforms cannot minimize the cost of delivery in a way fully digital platform businesses or even a platform like Amazon can purely because of the nature of the business. Also, the fact that the ‘delivery person’ or the ‘caregiver’ can only serve one customer at a time on physical service platforms doesn’t let such business take advantage of one-to-many and many-to-one network effects that companies like YouTube and Amazon fully utilize.
Platform leakage, disintermediation, or circumvention: Physical service platforms face the serious issue of disintermediation, which occurs when a customer on the platform establishes direct contact with the service provider by bypassing the platform. For businesses like Amazon, the seller has no incentive to make deals with customers off-platform, however the same is not the case for service platforms like Uber, Urban Company etc.
Lack of platform loyalty: multi-homing is a significant issue for physical service platforms like Uber and Zomato. Their customers frequently change platforms looking for a higher discount and better deals, thus bringing down the platform’s customer stickiness. The digital product platform companies, on the other hand, have achieved notable success in ‘platform extension.’ Digital product platforms have managed to overcome these challenges because of their relentless emphasis on developing robust core technology and capacity building through collaborations.
Enhancing the technology core: Companies like Google & Amazon have built robust core technology to support their platforms. For example, Google’s Page Rank technology enhances its core search capability. Based on this capability, Google ‘platformised’ its business model and forayed into other spaces like location-based services, videos, etc.
Collaborating to supplement capabilities: Apart from banking on the strength of their core technology, digital platforms forayed into new markets by forming alliances and partnerships—Google with HTC, Netflix with the United States Postal Service, and Apple with app developers. In India, Jio has forged partnerships with Google, Facebook, Microsoft, and Qualcomm to enhance its capacity and extend its network further.
Investing in core technological capabilities: Building the technological core of a physical service platform is as important as adding more service providers and consequently more users to the platform. However, this has been an uphill task for physical service platforms. For example, Uber hasn’t been able to build a technology to provide any discerning information about the cab and its driver other than the superficial ratings.
Providing entire solution stack: Physical service platforms need to ‘productize’ their offering by well thought out product and process modulation. Physical service platforms need to establish well-defined processes before extending to other services.
Delivering end-to-end service: Physical service platforms need to understand the importance of service design and delivery. Rather than ‘forklifting’ business model of established platforms like Uber, they need to build an ecosystem by forging alliances. Building an ecosystem ensures quality control as it continuously tracks customer behavior.
Ensuring stickiness: To ensure stickiness, physical service platforms need to keep the customer experience at the center of their platform design since the user’s expectation is different for different services offered on the same platform. Alibaba enables a seamless transition from one service to another on its app, ensuring a smooth customer journey.
Keeping in mind the human factor: In physical service platforms, the interaction between the user and service provider is of utmost importance. Since the customer’s experience largely depends on the quality of this interaction at the point of service delivery, the human factor remains critical in the platform design.

The article goes on to provide some guidance for physical service platform, which despite the limitations, can still reap some of the benefits of a network platform by:

Investing in core technological capabilities: Building the technological core of a physical service platform is as important as adding more service providers and consequently more users to the platform. However, this has been an uphill task for physical service platforms. For example, Uber hasn’t been able to build a technology to provide any discerning information about the cab and its driver other than the superficial ratings.
Providing entire solution stack: Physical service platforms need to ‘productize’ their offering by well thought out product and process modulation. Physical service platforms need to establish well-defined processes before extending to other services.
Delivering end-to-end service: Physical service platforms need to understand the importance of service design and delivery. Rather than ‘forklifting’ business model of established platforms like Uber, they need to build an ecosystem by forging alliances. Building an ecosystem ensures quality control as it continuously tracks customer behavior.
Ensuring stickiness: To ensure stickiness, physical service platforms need to keep the customer experience at the center of their platform design since the user’s expectation is different for different services offered on the same platform. Alibaba enables a seamless transition from one service to another on its app, ensuring a smooth customer journey.
Keeping in mind the human factor: In physical service platforms, the interaction between the user and service provider is of utmost importance. Since the customer’s experience largely depends on the quality of this interaction at the point of service delivery, the human factor remains critical in the platform design.

The article highlights the contrast between platform-based product businesses and service businesses. Based on these differences, the author has enlisted valuable suggestions for physical service platforms to adopt. Although the journey of growth and extension of physical services platform is strewn with challenges, it behooves any physical service platform to keep in mind the suggestions given in the article while embarking upon that journey.

Developed market partner’s relative control and the termination likelihood of an international joint venture in an emerging market

Kiran Pedada, Manjunath Padigar, Ashish Sinha, Mayukh Dass, University of Manitoba, UTS Business School, University of Technology Sydney, Australia, Rawls College of Business, Texas Tech University, United States
Summary by Pradeep Kumar Chokkannan, Research Associate CBM

International joint ventures with companies in emerging markets like India and China are destinations for global companies in developed economies seeking expansion prospects. This study investigates the moderating effects of partnership scope (R&D, sales, distribution) and Developed Markets (DM) partner experience on the relationship between DM partner relative control and Emerging markets -International Joint ventures (E-IJV) termination likelihood while controlling for EM growth, EM FDI intensity, E-IJV industry concentration, EM firm age, and EM firm size to a better understanding of international joint ventures terminations in developing markets, which vary from joint venture performance and termination in developed market economies.

The research address two important questions (1) How does the DM partner's relative control affect the likelihood of an E-IJV termination? (2) Under what conditions does the DM partner's relative control enhance or reduce the likelihood of an E-IJV termination? A unique dataset of E-IJVs in India between 2001 and 2012 from multiple databases were collected. A sample size of 108 observations from 18 industries, were are taken. Out of which 62 terminated E-IJVs were collected. The coefficients and the respective significance values are estimated using Cox proportional-hazards regression.

DM companies mostly have larger international exposure and financial resources, whereas EM firms provide local market experience to E-IJVs. Despite their popularity and advantages, over half of all E-IJVs' fail within five years of inception. For example, Hero MotoCorp, India's biggest two-wheeler manufacturer, had substantial difficulties in achieving its sales objectives and operational plans when Honda, its Japanese partner business, disbanded its E-IJV in 2010. Existing studies stated that DM businesses create E-IJVs with EM enterprises to obtain market knowledge and access. When they fulfill their learning and resource acquisition goals, they dissolve their joint ventures with EM enterprises. Such unexpected E-IJV terminations undermine partner companies' strategy and performance in emerging economies. The result from this study suggests that the E-IJV would be mutually fruitful when the DM partner firm possesses high relative control with high scope, as this may decrease the likelihood of E-IJV termination irrespective of the DM partner's experience in international joint ventures.

This study adds to the knowledge of E-IJV terminations from the organizational learning perspective. Insights acquired from such research can help DM and EM partner firms to take proactive measures to align their E-IJV goals and termination plans strategically. The results help managers of DM firms to find the right partner to collaborate with and negotiate better terms with the EM partner. Managers of EM firms should consider forming E- IJVs with a higher scope and higher relative control by the DM partner. As a second option, EM firms may focus on taking higher control of the E-IJV to reduce the termination likelihood. This study suggests future research to examine the impact of post-formation characteristics on E- IJV termination for a holistic understanding.

Healthcare in post-COVID India: A call for a decentralized healthcare system

Equitable Healthcare Access Consortium; C. S. Pramesh, D. V. R. Seshadri, Evita Fernandez, Gullapalli N. Rao, Manisha Dutta, Pavitra Mohan
Summary by Venkata Srikrishna Mamidipudi, Manager CBM

Over the years, the healthcare system in India has largely been centralized, expensive and impersonal. Most people live in rural areas where care is inaccessible, unresponsive and unaffordable. The COVID pandemic exposed these difficulties further when travel restrictions significantly affected healthcare access across the country. This paper argues that improvements in efficacy, responsiveness and sustainability of healthcare can be achieved by decentralizing and distributing the current system, using evidence from their association with three organizations that demonstrated the robustness of such a system during the COVID-19 crisis.

Eye Care at LV Prasad Eye Institute (LVPEI)

The non-profit, comprehensive eye care provider LVPEI delivers its services through a pyramid model in Telangana, Andhra Pradesh and Odisha. The pyramid has four layers, with vision centers (VCs) in villages and semi-urban clusters managed by trained community members at the base, secondary eye hospitals at block headquarters managed by ophthalmologists in the second tier, tertiary hospitals at the next layer respectively at Vijayawada, Visakhapatnam and Bhubaneswar, and an advanced state-of-the-art eye care hospital at the apex in Hyderabad. During the lockdown period, LVPEI made over 800,000 telephonic contacts to reassure patients and understand the support that their families may require. Home visits were made to elderly and post-operative patients. Following these measures, vision centers and secondary hospitals started receiving more patients who availed the full scope of services.

Primary healthcare in remote, rural communities of South Rajasthan

Basic Health Care Services (BHS) runs six not-for-profit primary healthcare clinics (AMRIT) in remote rural and tribal communities in the Udaipur district in Rajasthan. AMRIT Clinics provide low-cost and accessible care through a team of qualified primary care nurses, most of whom are tribals themselves. A visiting physician supplements the clinical care. In addition, local health workers educated communities on issues relating to health and self-care. During the lockdown period, AMRIT Clinics continued to provide the full scope of services. In addition, the clinics also delivered drugs to households that had patients with chronic diseases, resulting in higher patient footfalls at the clinics compared to the previous year.

Cancer Care across Centers of National Cancer Grid

The Tata Memorial Centre (TMC), India's largest cancer care institution, provides comprehensive cancer care, free of cost or at highly subsidized rates for over 60% of the patients hailing from different parts of the country. TMC also convenes the National Cancer Grid (NCG), a network of cancer hospitals located in large and small cities of India. During the lockdown period, TMC decided to provide uninterrupted care while instituting a series of measures to increase access and reduce the risk of COVID transmission. TMC widely shared the resulting SOPs and protocols across member hospitals of NCG, guiding them to provide uninterrupted, standardized quality care.

Call for decentralized, distributed healthcare

The experiences presented in this paper demonstrate the value of a decentralized health system that is closer to the people. Based on these experiences, the authors argue that such a system would have the following characteristics to provide effective and equitable care: A distributed network of clinics and hospitals, task shifting and task sharing, Application of technology

Faculty Spotlight

Ratna Geetika (RG), Manager at the ISB-Centre for Business Markets and Venkata Srikrishna Mamidipudi (MV), Manager at the ISB-Centre for Business Markets, spoke to Professor Sudhir Voleti (SV), Associate Professor, Marketing Associate Dean - LRC & Faculty Alignment and Academic Director – IIDS. Professor Voleti shared unique insights on marketing research and analytics.

Day and date: Friday, March 5, 2021
Interview performed digitally

RG: You recently had delivered a program on Marketing Research and Analytics which was for the faculty from the management education. Could you please tell us something about this and how it will be helpful for other takers from the corporate domain?

SV: This program is in line with the recent trend of low-code/no-code frameworks. Many people have figured out that companies and employees have a lot of domain knowledge and expertise. But those employees may not necessarily be good at programming. The idea is to enable access to machine learning tools, algorithms expertise, and domain expertise to the employees who are now using machines that require programming. The idea is how do we bridge this gap? A lot of them may not be familiar with programming. So, the idea is to cut code out of the picture. And bring some menu-driven interfaces, frameworks, and a user interface (UI) with a back-end of ML and AI. This is called a no-code solution. There is a movement toward no-code environment nowadays. The tools and online interactive web applications that Manish and I have developed are intended for such use. They are easy, portable, customizable, and deployable and can be used in diverse classrooms with people from different backgrounds of whom only a few would be familiar with programming. So, the idea was to not keep it entirely within ISB but to spread this idea, tool, and platform to other MBA colleges so that they too can take advantage of this framework.
The faculty development program was one such effort. We invited people from well-known MBA colleges in India, people who teach marketing research. I introduced some of these tools to them and the associated datasets and use cases that go along with them. The hope is that some will take it up and spread this new way of doing things and familiarity with these tools to a much larger set of people.

MV: There are several determinants like the size of the target market, demographic factors, firmographic and psychographic factors in the market analytics domain. According to you what are the other key factors that would possibly drive the marketing research?

SV: Firmographics, psychographics and demographics are traditional segmentation bases. Modern segmentation relies increasingly on the availability of vast troves of data, including big data, personal data, browsing histories, etc. And most importantly, the use of purchase histories. So, for example, Amazon would have your purchase history, everything that you may have purchased or not have bought but have put in the cart, and then remove it. Even every page you browsed.
Of course, behavioral data on Amazon is an extreme example, but even your local supermarket or quick service restaurant tries something similar, right? So basically, based on a loyalty card you use or your phone number, these businesses build a record of your entire purchase history since they can identify you with a customer ID. Now purchase history or browsing history is behavioral history, so it is a new input. Besides demographics, iconographic firmographic factors are significant inputs into the segmentation scheme.

MV: What according to you is the relevance of Machine Learning (ML) tools for managers (especially marketing managers) in their work on a daily basis?

SV: Machine learning, traditionally, can be divided into supervised and unsupervised approaches. Supervised means I have a set of inputs and an outcome variable that is of interest. Now marketing managers have various outcomes of interest. Think of the number of metrics that they track. It could be anything from cost per impression on one side to number of likes or comments or retweets to sales. Profits, promotions, and many things are available; some are inputs, and some are outputs. ML tools allow us to connect a set of inputs to any outcome of interest on the supervised parts.
It is quite beneficial. Pretty much anything we do that is information based, either has an outcome that we are trying to optimize or has no outcome variable. You have an entire menu or supervised algorithms to choose from if there is an outcome variable. If you don't have an outcome variable, we have a complete menu of unsupervised algorithms to choose from.
The problem is that it took technical expertise to choose an algorithm program to fit the data to it and run it. Going back to the first question, low code-no code was discussed. This entire framework is where we will provide a UI, menu-driven interface, interactive interface, and the back end. The programming back end is hidden from the user. Marketing managers don't have to worry about the technical and programming details of how to implement an algorithm. You have a UI that will do it for you, so I think there is a lot of relevance for these tools; we haven't yet used them fully. I believe that process has started now.

MV: What according to you is the relevance of Machine Learning (ML) tools for managers (especially marketing managers) in their work on a daily basis?

RG: How can the organizations drive the customer engagement more effectively in a digital market scenario?

SV: So basically, digital is a very data-rich environment. Once you have behavioral histories of people on any data or digital platform, you can easily customize and tailor the UI that that user sees to their requirements. You can reduce the annoyance levels – i.e., things they don't want to see can be taken away. So, there is a lot of possibility and opportunity in the digital markets' scenario for customer engagement.
Suppose you look at video games and so on; you see a lot of online entertainment in the form of streaming video. In that case, influencers on YouTube, all of these folks of digital markets are constantly doing trial and error customizing, trying new things out, and trying to appeal to changing audience tasks and bump up audience engagement using digital tools that measure how long somebody stayed, at what point did they exit, etc. We also have lab-based tools that do high tracking. For instance, where they were looking, where they engaged, and so on. So, there are many tools in the education sector, including online education; these tools are starting to become helpful.

RG: Covid-19 pandemic has significantly changed the market scenario. What skill sets should middle and senior-level managers in an organization focus on to be successful in a digital market ecosystem? What advice would you give for the marketers in the market analytics realm?

SV:This is a very broad question. The skill sets required aren’t very different from what they were a generation ago. These are: having a feel for the market, having a feel for who our customers are, having some insights into customer needs in terms of what their world is like, where do we fit into their world, etc. That kind of a perspective was there as a generation ago, is essential even today.
At the more tactical and strategic levels, those core skills remain the same. The core skills are marketing abilities. Marketing thinking and tactical level tools have emerged. A generation ago, we didn't have this widespread use of Internet-based, microcomputer-based tools, which are now everywhere. Mobiles were not there a generation ago. Today they are there. So how do people build a relationship with their mobile phones and applications and consumption in this new digital era? How has that changed? An understanding of these becomes more critical.
I think middle and senior-level managers would benefit a lot from more explicitly understanding their consumers' world, which has changed a lot in the last generation. Compared to when a middle or senior manager would have started their career, how people search for and evaluate products and services today has changed so much. Advertising used to be traditional, but nowadays, digital word of mouth has become critical. So, these changes across the entire product purchase, consumption, and the post-purchase cycle have changed. And so, an eye on that would benefit managers and organizations.

RG: What is the most exciting market research problem you have worked on so far, and what were the key takeaways from that?

SV:When this is ongoing research, what we are trying to do is try to see marketing as an area, marketing as a function, and marketing as a discipline. How has it contributed?

The marketing focus and orientation of an organization, the signals given out in earnings calls, and how markets as equity markets respond or react to these signals. Once there is such a signal, what we do is it significant? Do markets catch it? Do they respond to it? So, these are the kind of questions that I'm asking. It's not a traditional marketing research project, though. In some sense, marketing research is about marketing itself, and to that extent, I think it's a little different from the other problems I have worked on.

RG: According to you, what is the most gripping marketing trend in today’s time?

SV:This entire trend toward personalization is where the behavioral histories and preferences are driving the ability of a consumer to create their world effectively. Which is basically what music I want, what programs I will watch, what articles I will read, and who I will interact with online and offline; the number of choices has grown so much now.
And you have AI and data on the other side, which can now give a coherent picture, a cohesive world for a person. And this has impacted all aspects of their consumption. Everything has changed from search to consumption to post-purchase evaluation. Based on that, I believe it is the most gripping trend in today's time towards personalizing goods and services. And of consumption itself to such an extent that markets have become fragmented, traditional segments that we previously had may not make sense anymore and are constantly changing.

RG: Please elaborate on how real-time experience tracking (RET) addresses the marketing challenges of identifying and influencing what drives customers’ attitudes and behaviors.

SV:Real-time experience tracking addresses marketing challenges and identifies and influences what drives customers' attitudes and behaviors. In the past, we had data and theories on how this might work, and we would do some surveys and studies here and there. Still, now the extent and the granularity of available data we have can peek below the consciousness threshold. So, for instance consider what happens when we use facial sentiment detection software during a video play. I'm watching a video; the video is also watching me. It's looking at my reactions and doing eye-gaze tracking. It's looking for any sentiment-related reactions on my face and it is doing so in real-time, effectively. We have a granularity of data, and with so much data coming in and higher-level constructs already theorized in the past, we will be able to bridge the micro and the macro of sorts. I think it is an exciting area.

MV: Please give us some insights on using various algorithms and data maps to solve business problems, while aligning with the overall organization’s goals.

SV:Aligning with an overall objective well is management’s primary responsibility. Corporate and organizational leadership must do problem formulation to define what the problem is. Everything else follows from there. What is the objective? What question are we trying to answer? What problem are we trying to solve? Unless that is defined clearly, we will miss the forest for the trees. There's too much variety and choice in AI and ML algorithms and tools. Unless we are clear about what we want, we may run up and end up running after some new shiny object here and there without paying heed to whether it helps in what we are trying to do and whether it gives us a good ROI. So, I believe the most crucial thing a manager in organizational leadership can do is define problems correctly. After that, a bunch of algorithms, data maps, and ML tools and techniques can then be applied to solve that problem. Once the problem is defined, we will find the tools to tackle the problem. If I take the whole lot, it just builds up baggage here. If the problem is defined, I can choose my tools accordingly.

About us

The ISB-Centre for Business Markets (ISB-CBM) has evolved from the need for dialogues, insights and course offerings that can provide practitioners with the skills to understand, create, deliver and capture value in the marketing world. This is the first-of-its-kind initiative in Asia. ISB-CBM is committed to helping organisations based in India and Asia find innovative next-generation pathways to grow their businesses profitably, especially in the era of rapid change that is a reality of today’s world.

For more details contact:
Ratna Geetika: ratna_geetika@isb.edu

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