Digital Transformation of “Legacy Firms”

— A New Competitive Strategy Leveraging Interactive Data —

Digital Transformation of “Legacy Firms”

In July 2022, NTT DATA set up a new division, “Consulting & Asset Business Transformation Headquarters” to support clients’ digital transformation through Foresight-based consulting. What competitive strategies do companies require in the digital era, where the nature of data and digital technologies are constantly changing? We asked this question to Professor Mohan Subramaniam of IMD Business School.

“Foresight Design Method™” Offered by NTT DATA

Companies are challenged to transform their business models to address the digital age. “Today, it is easy to give a new meaning to an existing function by applying another power,” says Daiki Nozaki, Deputy General Manager of NTT DATA's Consulting & Asset Business Transformation Headquarters. As an example, he poses a question, “Is it possible to move people and cars with your smartphone?”

Nozaki says, “We cannot physically move a car with a smartphone. But imagine Uber, for example. If I enter my destination into the application on my smartphone, and a cab will come to take me there. In other words, using digital technology, it is possible to move people and cars with your smartphone. This illustrates the concept of the digital society.”


In the physical business environment where we are, companies obtain a variety of data. Many firms do not see, however, how they can utilize this data or what business they can generate with it.

In these circumstances, NTT DATA has been working on Foresight-based industry/technology approaches to support clients and the market by presenting how they can utilize the data. NTT DATA has also developed assets of case studies from other industries/sectors and global cases that we have undertaken ready for clients.

“In light of the advancement of digital technology,” says Nozaki, “we will conceptualize and propose what the future image of clients should be like from Foresight’s point of view. Then we aim to give “meaning” to data and create new value utilizing the data. What is important here is not to start a business from scratch but to update an existing business with a digital business as its starting point. If we have missing data, we will acquire new data and combine it with existing data to build a business model.”

NTT DATA has developed a method called “Foresight Design Method™” to offer these solutions to clients at a high level. The method begins by unraveling the current business to visualize the customer journey, which represents the end-user’s value itself, and the value chain, which makes the customer journey possible. Next, we propose the client’s ideal future image, considering three aspects: how the customer journey and the value chain are impacted by changes of the environment and technology; how they would be impacted by changes of digital technology; and what value the client would offer to the marketplace. Then, with NTT DATA’s a rich variety of assets, the client and NTT DATA will work together to develop plans for the implementation.

Figure 1: Foresight Design Method™

Figure 1: Foresight Design Method™

As a specific example, Nozaki cites a case of a nonlife insurance company.

“Insurance companies have traditionally focused their business on preparedness for “emergencies” in areas such as mobility and cyber domains,” says Nozaki. “On the other hand, there is a growing need for insurance for “just-in-case” preparedness such as disaster and medical insurance, as well as insurance that supports “daily life,” such as insurance for energy and SME. We draw up what the future image of the business should be like for each theme, and then develop plans to realize the image, considering how solutions NTT DATA has accumulated can be utilized.”

Figure 2: Room for contribution to a nonlife insurer

Figure 2: Room for contribution to a nonlife insurer

NTT DATA will continue to promote value offering using “Foresight Design Method™” on a company-wide scale.

From Episodic Data to Interactive Data

Using interactive data is one of the keys to the digital transformation of companies and the evolution from their traditional asset-based businesses, according to Professor Mohan Subramaniam of IMD Business School in his book, “The Future of Competitive Strategy: Unleashing the Power of Data and Digital Ecosystems.” He calls companies that have built a legacy before the arrival of the Internet by “legacy firms,” and he explains how these legacy firms can create value by leveraging interactive data.

Mohan Subramaniam

According to Professor Subramaniam, three premises underlie the traditional thinking of competitive strategy: first, products and services are the source of revenues; second, value chains affect positioning of products within the market; and third, the nature of the industry determines value and positioning of products. Professor Subramaniam says, “these assumptions are not adequate for the modern digital world.”

“For legacy firms to grow, they need to leverage digital ecosystems with the power of data and digital platforms,” Professor Subramaniam discusses. “It is important to understand three key inputs for this. First, to understand what is new about data. Data has always been around us, but the meaning is largely different in the modern digital world. Second, to grasp the meaning of digital ecosystems for legacy firms. Then, third, to develop a new framework for competitive advantage based on this new understanding of data and digital ecosystems.”

Figure 3: Three key inputs for growth strategies in the digital world

Figure 3: Three key inputs for growth strategies in the digital world

Professor Subramaniam notes that the nature of data has also changed dramatically during the shift from the industrial age to the digital age.

“In the digital era, the meaning of data has shifted from being ‘episodic’ to ‘interactive.’ Episodic data comes through discrete events while interactive data comes through a continuous stream of events. For example, think that you went to a bookstore, spent one hour inside the store, and bought one book. The only transaction data the bookstore has is ‘someone bought one book.’ This is episodic data. On the other hand, imagine you spent one hour on Amazon, and you bought nothing. Amazon has a range of data including what other titles you searched, what interest you have, even though you bought nothing. This is interactive data.”

Not limited for websites, the recent development of sensors and IoT has made it possible for legacy firms to capture and utilize this interactive data for their business. However, this requires new strategic thinking. While with episodic data, the role of data was to support products, with interactive data, the role becomes reversed. Professor Subramaniam states, “your products become conduits or ways by which you can capture interactive data, and firms will need to make a shift to address this change.”

Furthermore, Professor Subramaniam describes digital ecosystems for legacy firms as a combination of production and consumption ecosystems. Production ecosystems are a development of the existing value chain. In the old value chain, generated data was used mainly to improve operational efficiencies. Now that it is possible to obtain interactive data from products owing to the arrival of sensors and IoTs, firms can use production ecosystems and generate new revenue streams.

“For example,” says Professor Subramaniam, “if you can analyze interactive data from your machines and predict a component failure, you can introduce subscription services of predictive maintenance.”

Figure 4: Production ecosystems

Figure 4: Production ecosystems

Consumption ecosystems, on the other hand, are a network of “complements” of products. These complements here are entities or objects that increase the demand for a product. In the case of automobiles, “complements” are roads and gas stations. In the old world, although firms were aware of the existence of these complements, they did not try to incorporate them into their business models. In the modern world, however, these complements get connected one another over a network to form a consumption ecosystem. For instance, when you order coffee from inside your car through AI, the cashless payment will be done automatically, and a flesh brew of coffee will be served as soon as you arrive at the coffee shop. This stream of events is based on consumption ecosystems. Growing consumption ecosystems are transforming an automobile from a mere vehicle into a new value-added mobility.

Figure 5: Consumption ecosystems

Figure 5: Consumption ecosystems

The Four Tiers of Digital Transformation for Legacy Firms

Then how could legacy firms build these ecosystems and drive digital transformation? Professor Subramaniam introduces the four-tier model for digital transformation.

The first tier is to achieve operational efficiencies using interactive data from existing assets. For example, improving efficiencies in paint inspection using AR and VR is the first tier. The second tier starts from collecting interactive data from customers, who are users. By identifying customer needs more accurately you can improve efficiencies in product development and operations. The third tier is to collect interactive data from products and create new revenue sources such as a predictive maintenance service as mentioned above. Finally, the fourth tier is to convert products into digital platforms and to share interactive data with various external companies and entities for transactions.

“Think what tier your firm is in now, what tier you should be in, and what you should do to get there. This is the basic way of thinking in digital ecosystems,” says Professor Subramaniam.

Figure 6: Four tiers of digital transformation

Figure 6: Four tiers of digital transformation

As an example of digital transformation in the real world, Professor Subramaniam cited the insurance industry.

The data that insurance companies had was mainly episodic. Insurers calculated average risk ratios based on archived data such as health status and demographics, and generated profits by having a larger pool of customers to lower the average risk.

Using interactive data, however, they can predict risk of individual customers and design new business to address the risk for each. The idea is not trying to compensate risk after something happened but trying to avoid risk before it happens. Moreover, another characteristic of interactive data is that you can use it in real time.

“For example, when water pipes have risk of freezing due to a sudden temperature fall, sensors can pinpoint risks from specific homes, and preventive action can be taken, such as running some hot water through the pipes, to avoid freezing.” Professor Subramaniam provides another example: “When a car accident occurs, sensors installed in the car instantly assess the damage and insurance claims can be immediately processed.”

In the digital transformation process he advocates for legacy firms, Professor Subramaniam says that the fourth tier, transformation from products to digital platforms, is the most challenging.

“The key is to identify objects that complement your product. In the case of automobiles, for instance, roads, gas stations, and service providers play complementary roles. You can create new services by identifying these complements and combining them with your existing services,” says Professor Subramaniam.

Figure 7: How to construct consumption ecosystems

Figure 7: How to construct consumption ecosystems

Furthermore, you need to build a digital platform, for which you also need “open API policy.”

“In legacy firms, APIs are typically used to share data just internally. In consumption ecosystems, however, APIs should be open so that external complementary entities can be connected. In the case of automobiles, parking spots, gas stations, any service providers and even retailers, which are relevant when you a driving a car, need to be connected on digital platforms. By this, transformation from traditional value chains to digital ecosystems will be achieved,” says Professor Subramaniam.

The keys for “legacy firms” to grow and win in the ever-changing digital world, would be whether you can correctly comprehend the changes in the nature of data, and whether you can successfully expand the network of data and transform collected interactive data into business.

This article is based on the session by Professor Mohan Subramaniam and Daiki Nozaki given at the NTT DATA Innovation Conference 2023 on January 24 and 25, 2023.