Digital strategy – Platform Business Firms

Stages of Digital Transformation

A lot of people confound digital transformation with information technology and automation. Automation of processes would lead to increase in efficiency, quality, and additionally, transparency, and fairness in the case of services. Industries have been transformed in the last few decades in such a manner that what is visible to the outside world is the information technology. What is not so much visible is the painstaking work that goes on in the back-end to support this transformation. In this blog post, I will highlight the stages of digital transformation, building on my previous blog post on digital transformation (read it here).

Four stages of Digital Transformation

The transformation for digital transformation at any organization begins with the definition of a perspective plan. It is absolutely critical that the entire journey is considered an intrapreneurial action – a new business project/ plan. Within the confines of the existing business model, constrained by the extant resources and capabilities, it is highly unlikely that mature organizations can question their status quo. I would therefore suggest that organizations set up independent empowered venturing teams to take the digital transformation journey forward. With appropriate leadership commitment to change and a vision of the future, this venturing team should draw up the perspective plan.

A key component of this perspective plan is the definition of the value that you provide in your ‘transformed’ state. Value is an over-used word in this context, but I will risk using that again. What is that additional/ different value that the transformed organization intends to provide? Take the example of Airbnb.com, that competes with traditional hotel chains. Without owning a single hotel room, Airbnb.com transformed the entire travel/ hospitality industry through the provisioning of basic rooms. While traditional hotel chains behaved like legacy airline carriers, continuously improving “the experience”, Airbnb.com began providing just bed-and-breakfast, but with a different “experience”. The customers might meet more like-minded travelers and hosts at Airbnb.com than at traditional hotels. In just as much the same way low-cost carriers disrupted the legacy airlines industry, Airbnb.com changed the way people looked at travel – it was no longer luxury that one looked for, but something new and exciting. And with their business model, Airbnb.com had the ability to scale up capacity seamlessly in any city, town, village in any country (legal troubles notwithstanding).

Superior customer value cannot be provided unless the organization focuses on re-engineering its back-end processes. What may be visible to the outside world are the rejigs on the front-end, but the back-end process reengineering is the core to successful digital transformation. It is how efficient the back-end processes are, and how the front- and back-end processes talk to each other that matter the most. Imagine the world before the airline ticketing portals. One would have to call in to a travel agent, who would access the reservation systems of different airlines and provide the consumers with limited choices (and in most cases those choices that made him the most margins), and very little flexibility. What these online portals did was to provide consumers with unlimited choice and flexibility, including crazy organizations like https://skiplagged.com. The customer experience changed significantly, primarily because these airline ticketing aggregators could create back-end processes that would extract the schedules and fares, including connections and code-share agreements. It is the based on the strength of the back-end that supports the transformation of this industry. Same is the case with Uber (or any of its competitors or partners) – the back-end that seamlessly connects drivers and riders based on the geo-spatial data captured from their devices. Traditional taxis focused on automation of billing and other front-end services, whereas Uber disrupted the market with back-end re-engineering.

The importance of customer centricity could not be missed in this process reengineering. The customer experience has to be the center of any such reengineering. Good reengineering imagines the customer journey throughout her experience with the organization and its product/ service as it happens chronologically. Like a relay race, the customer “baton” has to be passed on from one organization unit to another seamlessly that the customer should not experience the passing of the baton at all. Organization design that promotes concepts like the key account management (KAM) or single point of contact (SPOC) facilitates such experiences, and it is critically important to keep these customer journeys in mind while redesigning the processes. For instance, take the case of how loyalty programmes work. You rake up your points/ airmiles from one product/ service and struggle to spend those points, as the options for redemption are highly limited. Yes, these days my credit card company and my airline frequent flier miles are merged, as I use an airline-co branded credit card. Even then, my credit card spends get added to my airmiles that I cannot redeem for anything else other than the limited choice provided. Here is where disruptions like WorldSwipe can help (read more about WorldSwipe here), where the platform has partnered with a variety of organizations from where consumers can earn their points, and a much larger variety of outlets where they can redeem their points. For instance, an electrician buying cables and earning points from his favorite electric cables brand can redeem his points by buying cellphone minutes from his favorite telco. [Disclaimer: I advise them]. Imagine the processes reengineering required from the cable company, as well as the telco in order for this loyalty to work; and the extent of consumer insights that could be captured as this platform grows and matures.

In the process of defining and reengineering the processes, it is important to keep the employee experience as well in mind. When customer experience dominates process redesign without regard for the employee experience, the whole system collapses. Take the case of your ecommerce grocer’s last mile delivery persons. These employees, are possibly the lowest paid in the entire chain, and yet, they represent the face of the company to the consumers. The consumer interacts with the company only through her mobile phone or tablet, and then these delivery persons land up at her door. Fullstop. Consumer experienced your product/ service. How critical is it to understand and design the processes that traces the employee experience journey! I have heard horror stories of how these employees in cities like Bangalore are provided with unrealistic delivery targets, without proper consideration of traffic situations, parking issues, and consumer non-availability at home situations. Add cash-on-delivery complications where these employees have to not just deliver goods, but collect cash for the same as well. Complicate this a little further with card-on-delivery and associated network connectivity issues. Once you live through the employee experience journey, you would realise how important it is to balance the process reengineering effort between the customer experience and employee experience. A lot of time, basic training and skill-development may be sufficient, but training on customer service orientation, attitude, and service quality would go a long way in enhancing the employee experience and engagement. Just make sure that your organization does not go towards employing two monkeys (as below).

On Tuesday this week (06 September 2016), The Mint newspaper carried a special issue on the digital future. One of the articles in that edition was by Jaspreet Bindra from the Indian automotive major Mahindra & Mahindra, titled “The 10 Commandments of Digital Transformation (read it here). Coming from someone with a varied experience like him, it is worth reading through. His 10 commandments does touch upon what I have elaborated plus much more.

Enjoy your digital transformation journey!

Digital disruption – drivers, symptoms and scenarios

My students, colleagues, and leaders in firms who I mentor have been asking me to share my views on digital disruption of businesses. In this post, I try to define the contours of digital disruption and what it holds for the future of businesses, in my opinion.

What is digital disruption?

Disruption refers to a fundamental change in the value proposition of the business. When digital technologies form the basis of such a change, I call it a digital disruption.

Drivers of digital disruption

There are three primary drivers of digital disruption (adapted from this article). First, is the maturity of digital tools and technologies that uncover inefficiencies in traditional business models. Take for instance the sharing economy characterized by business models like Airbnb.com and Uber. These business models highlighted the underutilization of fixed assets in residences and cars, and shifted the consumer behavior from traditional business models of exclusive hotels and owned cars to shared residences and cars. A recent example of this sharing economy is www.flightcar.com, that allows for individual car owners to rent their cars parked idle in airports to other visitors to that city as self-driving cars!

The second driver of digital disruption is the increasing evaluability of performance parameters. In a traditional business like car hiring services, it was difficult to evaluate the quality of cars. In the sharing economy, ratings/ reviews/ recommendations from other users can help evaluate various parameters of the products and services. Uber allows for mutual rating of drivers and riders, alike. Such improvements in technology that increase the evaluability of parameters, hitherto not evaluable can significantly contribute to unique customer value addition.

The third driver of disruption is the increased dominance of mobile apps. What the transition from traditional PC-based software applications to mobile apps contributes is lower costs of customer adoption, richer data collection by the apps leading to better customization of experience, and mobility. Imagine using Uber through only a PC-based or a browser-based communication!

When do you know your business is being digitally disrupted?

The following table describes the characteristics and symptoms of digital disruption with some examples (adapted from this article).

Symptoms	Examples
A proliferation of free or nearly free digital technologies in the value creation process	Digital photography eliminating paper photography
Such technologies are provided by multi-sided platform firms	Products like Gmail eliminating the need for organizations investing in their own email servers
Conscious shifting of value creating activities outside the firm, including open and user innovation processes	Evolution of 3D printing enabling democratization of design and prototyping
Rapid prototyping and product development/ market entry made possible as a result of user/ open innovation	Proliferation of platforms and forums like tech-shops that enable businesses and consumers to rapidly prototype and customize their products in low volume production contexts
Use of direct and indirect network effects to leverage economies of scale and scope	Evolution of aggregators and marketplaces like Alibaba.com that leverage network effects for economies of scale and scope

Most digital disruptions are visible when the industry/ market is characterized by one of more of the above symptoms. If any of these symptoms are visible in your business context, organizations beware. Begin preparing to face/ counter these forces.

Planning for the digitally disrupted future

Prof. Mike Wade from IMD, Lausanne describes four scenarios of digital disruption (read the full report here).

The global bazaar – industry and geographic boundaries blurring due to internet and mobile
Cautious capitalism – data security concerns limit firms’ ability to monetize consumer data
Territorial dominance – regional industry boundaries persist, with tight regulation
Regional marketplaces – world divided into regional clusters with their own rules and governance, innovation fostered in regions with little or no international competition

The following figure summarizes the four scenarios with examples of firms that will dominate their respective markets.

As you can see, these are just my preliminary thoughts, and I would strive to develop on them subsequently.

Comments, feedback, and experiences welcome.

Durability of network effects – importance of multi-homing costs

In their recent HBR article, David Evans and Richard Schmalensee argue that winner takes all thinking does not apply to the platform economy. In the article, they cite instances of how popular multi-sided platforms like Facebook, Google, and Twitter haven’t won every market. In fact, in spite of being near monopolies social networking, internet search, and micro-blogging, they compete very hard for the advertisement revenue. They also posit that network effects are not durable enough in the case of digital goods, as compared to physical networks like railroads and telephones. In this blog post, I am going to discuss these two assertions.

In the meantime, I ordered their book, Matchmakers, and my favorite ecommerce bookseller just delivered it to my desk, as I begin writing this blog. Will read the book in the coming week, and possibly update the note; but for now this blog post is based on their HBR piece. Now, if you have not read their HBR post, please read it.

Winner-takes-all markets

In their very popular HBR article Eisenmann, Parker, and Van Alstyne elucidate three conditions for a market to exhibit winner-takes-all (WTA) conditions. One, the network effects should be strong and positive; two, multi-homing costs should be high; and three, there should not exist any special needs by the users.

Network effects

In the case of the three multi-sided platforms that Evans and Schmalensee quote, the network effects are very strong. You signed up to Facebook because all your friends, family, and acquaintances were on Facebook (same side network effects); you use Google search because Google has learnt enough about you and only pushes “relevant” advertisements to you (cross-side network effects); and you micro-blog using Twitter because everyone who you want to reach are already looking for you at Twitter, as well as everyone who you want to follow are micro-blogging using Twitter (a combination of same and cross-side network effects).

Multi-homing costs

Multi-homing costs imply the costs of affiliating/ maintaining presence on multiple platforms at the same time. My most popular example is the case of internet-based email services. Even though it is literally free for anyone with an internet to have an unlimited number of email accounts, most of us cannot really maintain more than three email accounts. The monetary costs of creating and operating multiple email accounts may be zero, but the effort required to remember passwords, periodic logins to each of the accounts, and ensuring that you are communicating using the right email account is too much for most people. These are multi-homing costs.

Multi-homing costs exist in all the three markets we are discussing – social networking, internet search, and micro-blogging. In the case of social networking, it is difficult to maintain multi-home as the updates that we are likely to share in multiple networks are likely to be the same. And, the strong network effects (all my friends are on Facebook) make sure that there is virtually no-one else who is active in any other competing social networking site who is reading my updates. Multi-homing costs in internet search manifest in the form of the search engine’s ability to customise its advertisements and offers to my preferences and behaviour, which is based on my behaviour over time – with my past preferences, I have actually trained the search engine to customise. Search on the same key words across different internet search engines are unlikely to provide different results, but it is the overall experience including advertisements and personalisation that matters in the case of Google. This is somewhat similar to being loyal to a particular airline and gaining miles in that frequent flyer program; as splitting one’s travel across multiple airlines’ loyalty programs would ensure that one does not remain a frequent flyer anywhere! Similarly, having invested sufficiently in training Google on my personal preferences, I would rather stick with Google search. Similar is the argument for Twitter – the network of micro-bloggers and followers exist on Twitter; and I have carefully curated the list of which micro-bloggers I want to follow. Multi-homing costs include creating multiple lists of people I want to follow, and getting others to follow me.

Special preferences

The third condition for a market to exhibit winner-takes-all characteristics is the absence of any special preferences. Let us take the case of social networking – when professional networking and sharing of professional thoughts is a special need, different from social networking, LinkedIn thrives. Most people with a need to separate out their personal networks from the professional networks will maintain a Facebook account, as well as LinkedIn account. And, when a LinkedIn user turns into an active job seeker (from being a passive expert), she would open an account with a focused careers site like Monster.com. Similarly, someone’s work/ passion may require sharing large sized file attachments over email, and therefore push her to open multiple accounts for different kinds of uses.

In sum, winner-takes-all markets are characterised by the presence of strong network effects, high multi-homing costs, and the absence of any special needs. What Evans and Schmalensee ignore in their HBR post is the presence of high multi-homing costs. Yes, these firms do contest in the market for advertising revenues, but in one side of their respective markets, their strategies have been to continuously raise multi-homing costs. Take Facebook’s acquisition of WhatsApp for example. When more and more people took to social networking using a mobile phone than the ubiquitous desktop, and were increasingly constraining the breadth of audience for their posts, it was important for Facebook to be present on the users’ mobile phones, not just enabling broadcast social networking (with its Facebook mobile App), but also including narrowcasting or unicasting social networking using WhatsApp. Same is with Google – over the years, Google has come to dominate the internet search in more ways than one – YouTube and Maps to name a few.

Durability of network effects

The second thesis of Evans and Schmalensee is that network effects in multi-sided platforms are not durable. They cite how easy for a new entrant to challenge these leaders with little or no physical investments. Digital goods like software have high fixed costs and almost zero marginal costs for every additional unit produced. Economics has taught us that in markets with near-zero marginal costs, prices will fall continuously to eventually make the product free. There are a variety of other goods where such cost structures prevail. Take for instance, news media. The cost of replicating (or is it plagiarising) a news article across multiple outlets is close to zero, and therefore news producers are under tremendous pressure from consumers to respond to the threat of potential new entrants to provide news at prices cheaper than free. Yes, cheaper than free, which means that you may actually be paid to consume news! Like what Google did to the handset makers to use its mobile OS (for more details, read here). In the initial days of building the platform, firms are under severe pressure to kick-in network effects, and adopt pricing strategies that are cheaper than free. For instance, the Indian cab aggregator OLA Cabs, incentivises drivers handsomely (as the markets mature, the incentive rates are falling) to undertake a certain number of rides per day. This is apart from the amounts they earn from the passengers. In the entire bargain, drivers get paid by both the riders and the aggregator, and OLA keeps the rider fare low to encourage more usage, leading to faster growth of network effects.

Evans and Schmalensee argue that faster the network effects grow, faster they will disappear. I contend that this may not be true in markets with higher multi-homing costs. Take the OLA Cabs business model for instance. At the rider’s side, there are no significant multi-homing costs; at best it is limited the real estate available for multiple apps on the rider’s smartphone. It is the drivers’ multi-homing costs that are of interest here. OLA Cabs and its primary competitor Uber, have been working hard on increasing the driver’s multi-homing costs by limiting the incentive payouts only when the driver completes a certain number of rides per day. And as the market grew, this number of rides required to earn incentives has risen sharply. That means, a multi-homing driver has to ensure that he completes at least the minimum number of rides on one of the aggregator platforms before accepting rides on another. And soon, drivers who cannot meet the minimum required for earning incentives on both platforms would choose one of the two, and those drivers who cannot even meet the requirements of one aggregator would leave the market. Even though the cost structure of cab aggregation is similar to digital goods (high fixed sunk costs incurred upfront) and close to zero marginal cost of adding a new driver/ cab to the fleet, these firms have sustained the winner-takes-all characteristics by increasing the multi-homing costs of the drivers.

To sum up, network effects are durable when the platforms invest in increasing multi-homing costs of at least one side of the platform. Better so, the money side (not the subsidy side) that has the highest switching costs. These multi-homing costs arise out of asset-specific investments that the participants make in affiliation with the platform. In the case of OLA Cabs, multi-homing costs do not arise out of having to carry multiple devices, but in ensuring minimum number of rides per day on a particular platform to earn incentives. And these incentives are significant proportion of the drivers’ earnings, as the aggregators keep the rider prices low.

The importance of multi-homing costs

Evans and Schmalensee write:

With low entry costs, trivial sunk capital, easy switching by consumers, and disruptive innovation showing no signs of tapering off, every internet-based business faces risk, even if it has temporarily achieved winner-takes-all status. The ones most at risk in our view are the ones that depend on advertising, because even if they dominate some method of delivering ads, they are competing with everyone who has or can develop a different method.

In this post, I argue that creation and maintenance of high multi-homing costs is an effective insurance against low entry costs, trivial sunk capital and easy switching by consumers. Fighting disruptive innovation requires platform firms to understand the economics of envelopment, which we will discuss next week.

Cheers

About this blog

Hi: I have been wanting to write a blog for a long time. Thanks to my students and collaborators who have pushed me to write regularly, I start.

There are three things I would write about:

Strategy, in general; Indian firms in specific
Digital strategy, and what it means for the Indian firms, especially start-ups
Platform business models, with a focus on Indian firms

Suggestions and comments welcome.

Reach me at srini108@gmail.com

Share this:

Like this:

Share this:

Like this:

Share this:

Like this:

Like this: