Business strategy as a concept has seen significant evolution over the past several decades, moving from traditional models of product-based advantages to more innovative approaches that blend physical and digital assets to solve customer problems. This shift underscores the essence of what Vijay Govindarajan, the Coxe Distinguished Professor, Tuck School of Business at Dartmouth College and a faculty partner in the Silicon Valley incubator Mach 49, calls the “fusion strategy”, a blend of physical and digital realms to generate economic value through data and insights. Interview by V. Keshavdev


The concept of strategy and strategic planning has evolved over the past several decades. Is the fusion strategy strictly better than traditional business strategies, or are there scenarios where traditional strategies still hold the upper hand?

Mike Porter in the late 1970s introduced the concept of competitive strategy. His concept is product-based. Porter advocated low cost or differentiation as two ways to compete. If you are in the automobile industry, you can either make a car cheaper (Hyundai) or make it better (Mercedes Benz). Even today, it is important for companies to focus on product-based advantages. If you are Mahindra & Mahindra, it is important that you make the tractor more reliable, higher quality, better design, and lower costs. These are product-based strategies. But what we are arguing in our book Fusion Strategy (Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future, co-authored with Venkat Venkatramanis) that there is another, perhaps more significant way, to create economic value: marry steel and silicon, physical and digital, to develop insights and solve customer problems.

There is a limit to how much you can improve the reliability of machines. There is a limit to economies of scale based on production volumes. In fact, there could be diseconomies of scale. Once a firm grows to a certain size, it becomes too complex to manage. In contrast, there is no limit to data scale. That is why fusion strategy presents an exciting frontier of new economic value. If you want evidence, see the value Tesla has created in the auto industry. Tesla is a data and AI company that makes cars. Its market cap is bigger than the next 12 automakers combined. Tesla’s competitive advantage is based on fusion strategy and is not explained by Mike Porter’s product-based strategies.

Does the fusion strategy apply equally effectively across industries, or are there sectors where it might not be as impactful? Based on its principles, can we predict the next major industry disruptor in the next five years?

Fusion strategy applies to every company in every sector. However, some industries will be faster to adopt compared to others. For instance, the auto industry is an early adopter. Any industry that produces things that move will be early adopters. This includes automobiles, two-wheelers, commercial vehicles, and agricultural tractors. It is easier to instrument a car with sensors and observe how the customer drives the car. Any industry that supplies products directly to end-consumers will be early adopters. Sectors that will be late adopters would be those which supply “intermediate” products that go into finished products (such as companies supplying steel, cement, etc., to other companies).

How can CEOs recognise from the outset that fusion strategies are primarily network-centric, in contrast to the traditional firm-centric approach of strategic thinking?

Consider John Deere. Its equipment is only 10% of the farmer’s cost. The other input costs of the farmer include seeds, fertiliser, herbicides, and so on. If John Deere wants to improve farmer’s yields, the company must form an ecosystem with fertiliser and seed companies. This is inevitable. Also, industrial companies may have to partner with digital start-ups. All of this means a network-centric approach. The industrial company must ask: What customer problem it wants to solve in the year 2030? That will force them to take an ecosystem approach.


In India, industrials prefer buying digital assets as adjacencies to “widen” their business ambit, and not really creating an ecosystem to “fortify” their core businesses. Besides, creating ecosystems with partners outside the immediate supply chain needs a collaborative mindset from the CEO. How many CEOs would be really thinking out of the box or are in that “zone”?

This calls for a totally different mindset, from “me” company to “we” company. Historically, companies thought of vertical integration as a way to own and diversify. What we need is virtual integration. Forward-thinking CEOs understand the importance of ecosystem approach.

One of the interesting things I find in Indian culture is that we believe in co-existence. For centuries, diverse people with different economic backgrounds and religious beliefs have co-existed in the same neighbourhood. That is not the case in the West. In New York City, for example, the rich live in one part and the poor live separately away from the rich and do not co-mingle. Therefore, partnering in an ecosystem might be more natural in the East than in the West.

How might India’s decade-long digitalisation drive, indicative of Industry 4.0’s global spread as seen in South Korea and Germany, position the country to transition from being the world’s back-office to an advanced manufacturing powerhouse, with digital technology serving as the catalyst?

India has three advantages to make fusion strategy the vision for India@100. First, the world needs factories. Given the strained U.S.-China relations, the world needs another country to manufacture products at scale. That is India’s opportunity. However, we cannot manufacture products using the 20th century industrial-era principles. Products must be made with digital at the core. This is where India can shine. Second, India has made investments in digital infrastructure: digital identity (Aadhaar), digital storage (Digi Ledger), and digital payments (UPI). Finally, India has plenty of digital talent.

But UPI, Aaadhar, and DigiLedger are all non-profit government-owned public networks which are now being used as diplomatic “tools” to empower India’s geo-political ambitions. We are yet to see a genuine digital product at scale being created by Indian companies. It’s still Big Tech calling the shots. So, can India really make the big leap in digital products?

It is not necessary for India to create a digital product such as a foundation AI model to win in fusion strategy. Sure, Open AI, Google, and other digital giants are developing large language models. What India needs is AI talent to build applications on top of these large language models. That kind of digital talent is abundant in India. That is enough to win in fusion strategy.


Can having too much data be a disadvantage for a company trying to implement a fusion strategy?

Many companies have too much data. They drown in data lakes. This is not about Big Data. Competitive advantage will not be based on the volume of data. What companies need is Smart Data, not Big Data. Smart data is value-adding data. Smart data is about tracking how your product is used by consumers.

In an increasingly privacy conscious era, consent-driven data is the key to forming the right data but if consent is not given how can companies build on data that is not holistic or complete?

In the consumer sector (music, travel, etc), individuals gave permission to digital giants to collect data — knowingly or unknowingly. We quickly checked the box “I Agree” so that we could access the app. That will not happen in the industrial sector. Consider the M&M tractor. Once M&M sells the tractor, it belongs to the farmer. The company no longer owns the tractor. M&M must embed sensors in the tractor to collect product-in-use data. The farmer will allow M&M to put sensors on the tractors under three conditions. First, the company must have the farmer’s trust. Second, M&M must invest to protect the integrity of the data. Third, the company should provide the customer with valuable insights based on analysing the data.

Can you elaborate with examples the point made on how the combination of AI and real-time data will lead to a new generation of strategies that will turbocharge their products, strategies, and customer relationships?

Take the case of John Deere. Historically, Deere built its competitive advantage through faster, stronger, and bigger machines. There is a limit to how much Deere can improve its tractors and make them faster, bigger, and stronger through R&D led investments. Today, Deere is combining its equipment with data and AI to create new pockets of value. Deere’s See & Spray is an example of a smart industrial product. See & Spray revolutionises herbicide use, moving from blanket spraying to targeted spot spraying. Its self-propelled sprayer uses a large carbon-fibre boom lined with 36 cameras, scanning at incredible speeds.

Powered by 10 vision processing units (VPUs) handling four gigabytes of data per second, this system utilises deep learning to distinguish crops from weeds. Once a weed is identified, a command is sent to turn on and off a nozzle to spray and kill it even as the sprayer moves through the field at up to 15 miles per hour. While the initial versions detected only green weeds in bare fields, the newer version detected weeds of any colour standing next to crops. The result: customer profits are boosted while reducing the use of herbicides by 60%.

This innovation is not in industrial machinery but entails merging the digital and industrial domains with data and AI.(4)

Would pure digital platforms such as Uber, Netflix, or Airbnb want to shift away from asset-light to asset-heavy strategies , despite data insights? In that context, should traditional industries really feel threatened?

It is not clear why Uber would want to own its fleet of cars. Or, for that matter, why Swiggy or Zomato would want to own restaurants. By having data hooks on other people’s cars (in the case of Uber) and other people’s restaurants (in the case of Swiggy and Zomato), these digital players have built viable business models. It is true Netflix and Amazon own physical assets. Netflix has invested in creating content, both movies and TV shows. For that matter, Amazon bought MGM Studios. MGM’s catalogues include over 4,000 films (including James Bond, Rocky, and The Pink Panther franchises) and more than 17,000 TV shows. Thus, both Netflix and Amazon have become “physical assets” heavy. Why did they do this? Because content creators like Disney will not license their content to Netflix or Amazon Prime. That is why they had to buy or build studios to develop their own content. That is not the case for Uber since car owners will come on to the Uber platform to make money from their under-utilised assets. There is no need for Uber to own its fleet of cars.

Considering the context of fusion strategy, how does the situation where California criticised GM’s autonomous driving business for “misrepresenting” the safety of its technology, particularly when the business has faced $8 billion in losses despite significant investment in AI, what are the challenges and strategic considerations for companies pursuing innovative fusion strategies in emerging technologies?

We’ve only solved 80% of the challenges in self-driving technology. It has taken us almost 25 years to get to that 80%. It will probably take another 25 years to solve the remaining 20% of the challenge since the last 20% is a tough nut to crack. I do not foresee 100% self-driving cars (without steering wheel and without a driver) for the next few decades.

However, fusion strategy does not require fully self-driving capability. Tesla today has autopilot but does not have a full self-driving option. Yet, Tesla is able to observe how the customer is driving the car every day. Tesla has installed sensors that enable the company to observe product in use data. That is the key to unlocking value with fusion.

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