Combine physical and digital domains to unlock value: Venkat Venkatraman

The author and information systems professor speaks about how to leverage the power of real-time data and AI to develop new sources of competitive advantage

By Anitha Moosath

Published: Jun 19, 2024 02:05:18 PM IST

Updated: Jun 19, 2024 02:17:28 PM IST

Venkat Venkatraman, Author and Professor in Information Systems at the Questrom School of Business, Boston University

Venkat Venkatraman is the David J McGrath Jr Professor in Information Systems at the Questrom School of Business, Boston University. He is also the co-author of Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future. In an interview with Forbes India, he explains why going forward, industrials will need to combine what they do best with what digitals do best.

Q. What are the fundamentals of fusion strategy? Why is it imperative to adopt it now?

The fundamentals of fusion strategy are that opportunities for value creation and capture lie at the intersection of physical and digital domains, hence the word ‘fusion’. Since the introduction of smartphones, we have digitised information-rich, asset-light products such as music, movies, advertising, financial services (payments), newspapers, etc. These analog products became apps inside the smartphone, and the leaders from the analog era lost out to born-digital new entrants (think Spotify instead of Warner Music; Netflix instead of Columbia Pictures).

The next wave of digital shifts will be in asset-heavy, information-rich sectors such as transportation, agriculture, trucking and logistics, construction and buildings, healthcare, energy, etc. Here, the analog versions may not disappear. Still, the value might accrue to those companies that master the new business models that combine physical and digital domains (think Uber in mobility or John Deere in farming).

Why now? Faster and cheaper computing makes sensors and software affordable at price points, making industrial products digital (fusion) products. Tesla is designed as a computer on wheels connected to the cloud with the functionality of over-the-air (OTA) software updates to improve the car's performance long after it has been designed and delivered to individual drivers. Every automaker must develop a roadmap where their machines are designed to resemble computing architecture more than industrial combustion machines. The same logic can be extended to tractors (John Deere, Case IH, Mahindra). The next decade will see such shifts in many other areas, but companies must start now.

Q. Companies like Amazon, Tesla, etc. leverage real-time data to diversify their businesses and add value. How do they create this virtuous cycle?

Elon Musk at Tesla believes that the competitive advantage for his company is in ‘fleet learning’. In his words: “When one car learns something, the whole fleet learns it.” It is because of the virtuous cycle of data on observations when the cars are drivenà training data for algorithmsà better driving rules àsafer driving à better data for training and the cycle continues till we get to full self-driving. This is not about programming proficiency but about data superiority. Tesla now has over 1 billion miles of data using its supervised full self-driving software; as this increases exponentially, their algorithms get better, and they get closer to autonomous driving. Tesla can use the data to get into insurance because they have more precise real-time driving data than insurance companies with aggregated historical data.

The same logic applies to Google as it refines its algorithms with more data stream on how billions of individuals interact with its search engine; this data helps them develop better ways to target advertising and improve features on related services such as YouTube and Maps.

Q. What do asset-heavy companies need to do differently in order to win?

Asset-heavy industrial companies must think beyond the attributes that made their products leaders in the analog world. Reliability, quality, cost, and related attributes differentiated physical products (trucks, tractors, trains, aircraft, construction equipment, buildings). These are necessary today but insufficient; they are table stakes, not differentiators. They must think about products-in-use data and create the capability to understand how their products perform for individual customers.

Observing products in use across diverse conditions helps industrial companies to develop hyper-personalised recommendations based on collective learning (analogous to fleet learning in the case of Tesla). In the past, asset-heavy companies mastered their physical value chain—from inputs to processes to outputs—to lead. They must also master the data value chain from descriptive analysis (what happened) to diagnostic analysis (why did it happen) to predictive analysis (what could happen) to prescriptive analysis (what should be done). They can become fusion strategy leaders when they simultaneously integrate product value chain with data value chain.

Also read: From enterprise to aam aadmi, Satya Nadella's plan for Microsoft AI

Q. Where will India be positioned in the fusion future?

India is on a trajectory to go from being the fifth-largest economy in the world today to becoming the third by 2030. I believe manufacturing’s share of the country’s GDP, roughly 17 percent, must increase to 25 percent or more. This should happen with advanced manufacturing practices that combine physical and digital infrastructure. India’s manufacturing might have been stereotyped as “low cost, low quality, human-intensive”. An oft-leveled criticism is that India produces thousands of engineering graduates and IT software professionals yearly who contribute to global firms. Still, it hasn’t created significant industrial machinery and equipment breakthroughs.

India’s manufacturing renaissance is right in front of leaders who would seize this moment to transform from its historical reliance on analog infrastructure to becoming digital leaders. Many underlying pieces are already in place—e.g., a renewed focus on ‘Make in India’, increased inflow of global financial capital into Indian companies, a vibrant startup ecosystem including entrepreneurs and venture capitalists, and rapidly digitising infrastructure in payments, logistics, roadways, ports, rail, and airports.

Q. What are the attributes of a fusion leader?

A fusion leader sees value creation at the intersection of physical and digital domains, combines industrial engineering principles with the possibilities of information sciences, rejects past definitions of functional boundaries and accepts the fact that the future is not a linear extrapolation of the past.

Satya Nadella’s bold embrace of Gen AI to transform what Microsoft offers to enhance productivity stands out. He went beyond accepting software as helping professional productivity (Windows and Office) to thinking about the role of software in maximising every individual’s potential (Copilot). John May at Deere’s vision to transform the venerable industrial giant into a smart industrial company to enhance farm productivity by fusing mechanical engineering with software competency is another.

More generally, I see a fusion leader as one who accepts that digital technology will unlock significant value trapped in analog, siloed ways of working and is prepared to lay the foundation for an industrial company to become ‘post-industrial’ with digital technologies.

Q. Augmented Intelligence Vs Artificial Intelligence…

I believe that the role of corporate leaders (and policymakers) is to distinguish between zones of automation from zones of augmentation.

Automation is where machines carry out activities with limited human oversight. Much of factory and knowledge work can be automated. Augmentation is where advanced computing machines do the ‘heavy lifting’, but humans make the final decision. Healthcare is a prime example of how physicians could be more effective with AI acting as intelligent interns, but the doctors still have the final say.

A successful company will have effectively identified the automation zone and rapidly adopted AI to manage those activities efficiently while freeing scarce human talent to work collaboratively with newer AI tools to unlock new value.

Also read: What Indian managers should know about Generative AI

Q. Partnerships and overlapping ecosystems—how important will these be, especially in gaining competitive advantage?

It’s time to go from being an ‘I’ company to a ‘we’ company because solving major thorny problems requires vibrant coordination among companies competing and collaborating simultaneously. This is particularly true as industries become infused with digital functionality. Here, the computer industry offers valuable lessons for industrial companies. Microsoft’s software requires complementary offerings from Dell, Lenovo, and Samsung. Google needs Samsung to make Android-powered phones but also competes with its line of Pixel phones.

Every company must ask and answer this question: What unique value do we bring to the ecosystem that our partners cannot get from anyone else? They do not possess a lasting strategic advantage if they cannot answer that question clearly and truthfully.

Q. Three must-dos for organisations that embrace a fusion approach…

One—go beyond thinking about your products as designed and manufactured to understand how your products operate in customer locations in real-time.

Two—think beyond narrowly defined functions. Where does R&D end, and where does digital begin? Where does marketing end, and where does analytics begin? Where does your firm end, and where do partners begin?

Three—attract human talent fit for the fusion future. You may be an employer of choice for professionals who see and know your company for who you are (and who you have been in the past). Now is the time to position yourself in the talent marketplace to attract the talent you need to win in the fusion future.