Expanding the Scope of Data and Digital Ecosystems to Deliver New Value
As part of NTT DATA's new series focusing on the value of foresight, Senior Executive Vice President Shigeki Yamaguchi speaks with Professor Mohan Subramaniam of the International Institute for Management Development (IMD) to explore how companies can harness their data for a competitive advantage.
NTT DATA Senior Executive Vice President Yamaguchi has expertise in consulting business strategy, developing new business markets, and digital transformation in areas such as ERP, e-Commerce, customer experience, and payment services.
Mohan Subramaniam is Professor of Strategy and Digital Transformation at the IMD business school. His focus is on the digital transformation of legacy firms. He has experience identifying new competitive advantages and sources of value through data gathered by digital ecosystems. Mohan has also published the book "The Future of Competitive Strategy."
Expanding the Scope of Data and Digital Ecosystems to Deliver New Value
Defining Interactive Data
Advancements in digital technologies have increased the value that can be extracted from data. Shigeki explains how NTT DATA organizes technologies with the framework of Convert, Connect, Algorithm and Cognize, and shows how technologies make it possible to extract interactive data and insights. For example, Convert applies to technologies that enable data to be captured, while Connect involves technologies that make it possible to share data at any time and anywhere. Algorithm ties together the technologies found in Connect, while Cognize adds the value of data to services and products. Combining these four will allow a company to thoroughly utilize the data they obtain.
Mohan enhances this definition by stating that interactive data is a continuous stream of data that enables real-time use through the analysis of specific subjects or objects. Up until now, "episodic data" - meaning aggregated data from discrete events that is not used in real-time -has been much more commonplace.
To understand the differences and to illustrate how the change from episodic to interactive data is affecting companies, Mohan gives the example of McDonald's and Facebook. McDonald's used episodic data to measure how many burgers it sold because it needed to know how much stock they have left, how much it was producing, and where it was being produced. However, after the burger was sold, the data stopped. The data was simply kept and stored, and there was no interaction. In contrast, Facebook acquires a continuous stream of data from a user and knows detailed information, even to the extent of knowing a couple is likely to get engaged before they even know it themselves. Every action is recorded and used to connect the user to other interests, which allows further detailed insights into each user. This interactive data stream is then used to customize the user's experience.
What Kind of Impact will Interactive Data Have?
Mohan emphasizes that legacy firms must determine how to get interactive data and how to use interactive data in a digital ecosystem.
He first explains this by exploring the value chain of traditional companies and their complementor networks. For example, in the automotive industry, Ford is a manufacturer with a classic value chain; multiple parties were involved in the production and selling of products, including suppliers, their own factories, outsourced factories, and dealers. Once Ford sold a vehicle, the driver would encounter complementary goods, which contributed to increasing automotive demand. The more roads and petrol stations there are, the more demand there is for cars. These complementary goods form what is called a "complementor network."
However, when information technologies (IT) are incorporated into the value chain and systems are aligned, operational efficiency can be achieved through what Mohan calls the "Production Ecosystem." In this ecosystem, data flows throughout the value chain to create a network of data generators and recipients. By automating manual processes through IT, a company such as Ford could better see its inventory and sales figures at a glance while also utilizing sensors to better understand how customers use their vehicles. This makes data much more valuable and creates a Production Ecosystem.
By deploying this interactive data into the complementor network, along with AI and the Internet of Things, companies can achieve what is known as a "Consumption Ecosystem." The primary difference between Production Ecosystems and Consumption Ecosystems is that they are connected beyond the value chain and are evolved into a complete digital platform.
For Ford, cars can provide traffic data and even identify nearby gas stations when the car is low on gas. The vehicle can then connect to Alexa, creating opportunities such as ordering a coffee from the car while driving so it can be picked up without waiting.
Mohan summarizes that for legacy firms to understand their digital ecosystem, they need to think of their value chain as a combination of Production and Consumption Ecosystems.
How to Build Consumption Ecosystems
Mohan says Consumption Ecosystems are constructed by understanding a firm's traditional complements and determining which complements can be beneficial to connect with their interactive data. The firm will then consider how they could expand this in newly developed systems or existing platform strategies or APIs. An example of a Consumption Ecosystem is the network found between a refrigerator, microwave, oven and smart speaker. These items are not generally viewed as connected but are instead typically seen as discrete appliances. However, the app Yummly can scan a refrigerator, identify ingredients and determine a recipe the user can make with ingredients on hand. If any ingredients are missing, a smart speaker can automatically place an order while the oven can be automatically preheated if the recipe calls for it. Thanks to a Consumption Ecosystem, the kitchen experience can be transformed.
Looking at this situation, it becomes clear that identifying and prioritizing complementary goods providers is not easy. However, NTT DATA is working to address this from the customer's viewpoint. Consider an example of a customer's journey planning and making dinner. First, the individual typically will visit a shop to browse and then purchase ingredients, which they may request to be delivered. Then they return home and put the food away before finally cooking it.
This simple journey shows several possible complementary providers, from payment and delivery services to refrigerators and cooking utensils. NTT DATA will then enhance the value for the customer by choosing, adding to and optimizing complementary-goods providers in the system.
Navigating Digital Ecosystems
In digital ecosystems, competitors are no longer those who offer similar products or services but those who have similar data. Legacy firms can benefit from thinking about their competitive strategy through the four tiers of digital transformation:
- The first tier looks at operational efficiencies and takes the step to gather interactive data from assets to digital ecosystems. This is similar to Cognize in NTT DATA's framework.
- The second tier enables advanced operational efficiency, but it increases the difficulty as it shifts from interactive data collection from assets to products and users.
- The third tier is when you use interactive data to provide data-driven services from value chains. Up until this tier, the data is centered around Production Ecosystems.
- The fourth tier moves into Consumption Ecosystems. This is the most difficult tier as it opens the scope further to approach the product as a platform.
Competitive strategy can then be thought about by looking at where a company or product stands in these tiers and seeing if it can move into the next tier. Once the company determines a move is possible, they can then chart their objectives and course to achieve the next tier.
The Race to the Top
So, what determines the winners in increasingly robust Consumption Ecosystems? Shigeki explains that the determining factor is which competitor has the most impactful complementary providers, meaning providers that add levels of value that customers are willing to buy. Firms must have complementary providers to create synergy value from data generated by each product.
In terms of winning the overall leader position in a Consumption Ecosystem, Shigeki states that the value architecture of that ecosystem must be considered. Previously, the player with the most significant contribution value became the leader. They provided essential services and had the data to deliver customer values to become that leader.
However, technology deployments change the value of contributions and cost structures. This means the player making the greatest contribution in terms of providing the services and data to drive customer value will become the leader. The dependency and cost factors are separate, and this is where NTT DATA would like to enhance the provider's overall digital transformation framework, adding value to and supporting their client companies.