HOW SHOULD WE COMPETE IN THE FUTURE?!
In a recent interview with the magazine of the Exporters Assembly (İhbir Haber), I was asked, “What should manufacturers and exporters prioritize in their growth strategies?” Here’s how I responded: “First and foremost, the foundation of the business must be solid. Whether in the domestic market or exports, you need unshakable success and an inimitable competitive edge. Without this, sustainability is nearly impossible. On this subject, it’s essential to understand the works of Harvard’s renowned professor Michael Porter on competition and his ‘Five Forces Model.’ Porter emphasizes analyzing the intensity of rivalry among competitors in the industry, the bargaining power of customers and suppliers, the threat of new entrants, and the threat posed by substitute products before entering any market. If entering, one must also determine the appropriate strategies. Today, numerous analytical techniques have been developed, many of which can be seen as derivatives of Porter’s work” (1).
But wait! We often say, “It’s not as simple as that!” The world has changed; it’s now digital.
Take my father’s high school friend, Uncle Hüdai, for example, suffering from asthma. It’s such a difficult condition—sometimes it feels like they’re suffocating, and at that exact moment, they urgently reach for their inhaler, which works its magic almost immediately. Asthma is a chronic illness that obstructs the airways and hinders proper airflow. Triggers such as allergens, smoke, cold air, or exercise cause the muscles around the airways to contract and increase the production of sticky mucus, narrowing the airways further. It’s a critical condition, requiring patients to remain vigilant and rely on their inhalers.
Asthma impacts 340 million people worldwide, with the asthma inhaler market valued at $22 billion annually.
Now, however, we have smart asthma inhalers. Companies like AstraZeneca (with technology partner Adherium), GlaxoSmithKline (with Propeller Health), and Novartis (with Qualcomm Life) have introduced devices equipped with sensors and electronic chips embedded in the plastic activators. These inhalers track usage data—when and how often they’re used—and communicate via Bluetooth with smartphones and other wearable technology. The functionality remains the same, but the users of smart inhalers are now digital consumers.
These devices even measure their usage location, connect with other IoT-enabled home devices, assess surrounding levels of dust, mold, or pollen, predict the likelihood of an asthma attack, and detect emergencies, potentially saving lives. If such technology had existed years ago, perhaps Uncle Hüdai might have lived longer.
By 2025, the digital asthma inhaler market is projected to reach $1.5 billion, which brings us to today’s discussion: how can traditional products remain competitive in the digital era? We’ll turn to insights from Professor Mohan Subramaniam, an expert in digital transformation, and examine applications across various industries, particularly FMCG (Fast-Moving Consumer Goods).
Professor Mohan Subramaniam, a Strategy and Digital Transformation expert from IMD Business School in Lausanne, has authored a fascinating book titled The Future of Competitive Strategy (2). This book explores the ever-evolving nature of competitive strategy. According to Subramaniam, the fast-paced, data-centric business landscape renders outdated strategies ineffective, emphasizing that competition can no longer be conducted in the traditional manner.
The book is structured into three key chapters: The first chapter highlights the limitations of conventional competitive strategy frameworks, such as “Porter’s Five Forces” (3). The author argues that these frameworks fall short in a world increasingly dominated by data and digital ecosystems. This critique particularly struck a chord with me, as it challenges businesses like ours that rely on traditional brands, products, and structures!
The second chapter explores the role of data in shaping competitive strategy, underlining the importance of data-driven decision-making and the necessity for companies to embrace data-centric business models. Subramaniam also introduces the concept of data acquisition, underscoring how data has become a critical source of competitive advantage.
The third chapter of the book, in turn, focuses on the impact of digital ecosystems on competitive strategy. The author explores the rise of digital ecosystems, emphasizing the critical need for businesses to construct and engage with them. In this chapter, Subramaniam examines digital platforms, such as Alexa and Google Home, and discusses the enabling role of APIs (Application Programming Interfaces), blockchain, and other technologies in fostering these ecosystems.
Now, let’s take on the challenge—the first chapter:
Digital powerhouses like Amazon, Google, Facebook, and Apple leverage data to maintain their dominance, utilizing long-tail (4) and network effect (5) advantages to build digital platforms that derive significant value from user-generated interactive data. This interactive data acquired from platform users enables in-depth insights into users, facilitates real-time data sharing, and allows for the delivery of enriched digital experiences.
For traditional firms (like us), Subramaniam offers some key takeaways:
• Utilize sensor and IoT technologies to generate interactive data from customer interactions, creating new insights and value.
• Share interactive data with external stakeholders to unlock the potential of digital ecosystems and derive greater value from data.
• Build digital platforms using interactive data, moving beyond traditional value chain models focused on standardization and economies of scale, to create new business models driven by long-tail and network effects.
Subramaniam argues that while digital powerhouses initially capitalized on data for e-commerce, they solidified their dominance by leveraging interactive data from user interactions. This data provided deep insights, supported data sharing, and enabled enriched digital experiences. Traditional firms must learn to leverage sensors, share data, and transform their data utilization by building digital platforms, he says, thus presenting me with my first assignment.
Subramaniam also discusses the role of APIs (6) in enabling digital platforms and experiences. APIs facilitate communication and data sharing between various software programs, providing a structured pathway for connecting digital services. Digital powerhouses use APIs in two primary ways: Internal APIs, which integrate distinct software products within the company, enhancing efficiency and streamlining user data; and external APIs, which expand the capabilities of digital services by providing data and functions to developers and business partners. However, APIs also raise privacy concerns.
For traditional firms, APIs offer a valuable opportunity to unlock data and compete within digital ecosystems. By integrating internal systems and supply chains through APIs in the production ecosystem, companies can boost agility. Moreover, new APIs can be developed within these ecosystems to share data and create new experiences. In both instances, APIs serve as data channels that underpin digital ecosystems. Traditional firms can learn from digital powerhouses how to leverage APIs both internally and externally to generate value. This, too, is something I must address as the second assignment.
In the following chapter, the author explains how traditional companies can create digital ecosystems to derive more value from their data. Digital ecosystems consist of production ecosystems and consumption ecosystems. Production ecosystems stem from a company’s value chain network and focus on enhancing operational efficiency, while consumption ecosystems arise from a company’s complementary network, delivering new data-driven services through external connections. And this, as the author notes, is our third assignment!
Production ecosystems leverage internal capabilities, whereas consumption ecosystems rely on external innovations. While production ecosystems focus on internal APIs, consumption ecosystems require external APIs. The value generated by production ecosystems is limited to internal strengths, but consumption ecosystems create value serendipitously through external connections.
Industry 4.0 goes beyond production ecosystems, enabling new user experiences through consumption ecosystems. To fully capture the scope of Industry 4.0, companies must interact with both production and consumption ecosystems. Digital ecosystems help companies not only boost efficiency but also generate new revenue streams through data-driven services. Companies need to prioritize how data and digital ecosystems, alongside products, can create new value. In short, a mindset shift is essential!
The author asks a key question: How can production ecosystems help traditional companies derive value from data through greater operational efficiency and innovative data-driven services? He responds as follows: Operational efficiencies stem from the use of data within value chains to boost productivity and reduce costs, while data-driven services generate new revenue streams. And here’s the critical part: It’s about money. So, I’ve added the fourth assignment to my to-do list.
Production ecosystems guide companies through the first three stages of digital transformation. Stage One involves using data from assets to enhance efficiency. Stage Two capitalizes on data from products and customers, while Stage Three leverages data to introduce new services.
Take the FMCG sector, for example. A common issue in demand-supply matching is the bullwhip effect, where minor fluctuations in customer demand lead to amplified changes in supply due to poor communication across the supply chain. This negatively impacts production and logistics processes. Today, AI technologies combined with sensors have the potential to eliminate this effect via digital platforms.
If we focus on supply chain/logistics challenges, there are two key issues we can address using digital sensors/AI technologies and digital ecosystems. The first solution involves optimizing orders and coordinating product distribution between branches in a franchise-based, multi-branch retail operation, focusing on time and quantity efficiency. This can be regarded as predictive order preparation through the interactive data exchange between sensors placed in warehouses, digital environments, and other data sources.
Similarly, in retail, the calculation of sales and stock turnover through sensors, decisions on waste, inter-store transfers, depletion of unsellable products from inventory, and the ordering or production of new products can all be made possible through artificial intelligence technologies operating within digital environments.
Another example comes from the pharmaceutical industry. On average, pharmaceutical companies allocate 25% of their annual revenue to R&D—the highest across all categories. This is because the pharmaceutical business is heavily dependent on new product development. However, developing new products requires seamless data integration across a wide range of laboratory suppliers, from kit manufacturers and laboratory animal producers to protein purifiers and genome analysts. Operational efficiency improvements in such an environment can create significant impacts.
Data from products, sales, users, and supply chains can drive remarkable advancements in R&D, marketing, and supply chain efficiencies. Companies have various ways to optimize production by harnessing their ecosystems to enhance operational efficiency. Today, AI-powered data analytics enable more precise forecasting, boosting auxiliary revenue streams such as maintenance services, spare part sales, and subscription models across categories like machinery and software.
Take P&G and Red Bull, for example. These FMCG companies utilize creative CRM programs and web-based IoT sensors to capture interactive data. Red Bull’s F1 initiative, for instance, collects sensor data from race cars and shares it on its website, offering viewers an unparalleled, immersive experience (7).
In the fifth chapter, the author explores how traditional firms can leverage consumption ecosystems by integrating digital platforms with their products.
Consider today’s smart appliances—microwaves, washing machines, and dryers—equipped with numerous sensors and connected to platforms like Alexa and Google Home. While these devices allow voice-activated commands, the real value lies in the digital platforms, not the data exchange between the devices themselves. The author presents a case: imagine a lightbulb company embedding motion sensors in its products to utilize digital opportunities. These sensors transmit data to a digital platform, which is then shared with third-party security firms that integrate it with smartphones and alarm systems. The result? A competitive edge that benefits all stakeholders.
For traditional companies, equipping existing products with sensors is no longer optional; it is essential for survival and growth.
Companies are now defining new frameworks for their consumers by determining the most suitable digital platform strategies based on the scope, uniqueness, and control of the sensor data from their products. Key takeaways include:
1. Sensor data facilitates seamless data exchange among users on connected digital platforms, enabling new data-driven services.
2. The scope, uniqueness, and control of sensor data determine the feasibility of digital platforms. Scope reflects overall market potential, uniqueness defines how differentiated the data is, and control measures a firm’s ability to share data freely.
3. Based on these attributes, companies can create collaborative, efficient, or hybrid digital platforms within their competitive edge, tailored to the strengths and weaknesses of their sensor data and products.
Activating consumption ecosystems requires companies to attract digital customers, counter emerging digital competitors, and cultivate new capabilities to operate effectively on digital platforms.
In this chapter, the author explores the significance of digital customers for traditional companies navigating the shift to the digital economy. Digital customers interact with sensor-enabled products, generating interactive data that empowers companies to offer innovative, data-driven digital services. However, converting existing customers into digital customers presents a formidable challenge for many companies.
Digital-based customers stand apart due to their preference for sensor-equipped products and their ability to provide interactive data, which forces companies to transform both their business processes and mindsets. As traditional companies undergo this evolution, they must define the tangible benefits of their digital services and earn customers’ trust in granting access to their data. While scale influences standardized products, network effects benefit smart products. Companies must be willing to invest in improvement costs to foster network effects.
For companies, digital customers represent a critical source of interactive data that helps develop digital capabilities and competitive strategies. Yet, the ethical collection and use of customer data—with a strong emphasis on privacy—should be guaranteed.
The author then turns to the competition between traditional companies and digital rivals in the digital ecosystem.
To remain competitive, traditional companies must understand the ecosystem parity created by the symmetrical ecosystem strengths of their digital rivals. Identifying potential digital competitors, assessing whether competition will arise within production or consumption ecosystems, and predicting whether threats will be incremental or disruptive are crucial steps. While traditional companies can still leverage their legacy strengths, succeeding in the digital ecosystem requires the acquisition of new digital capabilities.
The author then underscores the digital capabilities of companies, highlighting how they differ from traditional ones. Digital capabilities enable legacy firms to compete in the digital world by focusing on the strengths of data rather than products.
Digital capabilities leverage various resources, such as those from digital ecosystems, rather than traditional value chain resources. Production ecosystem resources assist in improving operations and delivering data-driven products and services while maintaining the company’s core activities. On the other hand, consumption ecosystem resources help extend the company’s strategic reach beyond its primary business area through digital platform services.
Moreover, digital capabilities rely on processes like API networks instead of functional and inter-functional routines. These API networks structure the creation and sharing of data, introducing flexibility and dynamism. They infuse old routines with dynamism.
Digital capabilities can enhance a company’s strategic scope from products to data-driven services. Production ecosystem resources broaden the scope of a company’s core activities, while consumption ecosystem resources extend their reach beyond the company’s primary business area.
Traditional companies are increasingly developing phygital capabilities—an integration of conventional and digital resources and processes. Achieving this requires visionary leadership, a workforce with new skills, and an emphasis on employee engagement. Success in this realm hinges on the ability to harmonize traditional and digital capabilities effortlessly.
According to Mohan Subramanian, traditional companies need to evolve their competitive strategies to thrive in the digital age. Instead of focusing solely on products and industries, companies must embrace strategies centered on data and digital ecosystems. They should identify strategic options for Digital Foundations, Digital Ecosystems, and Digital Competition.
Digital foundations encompass connecting products, generating data through sensors, and building API networks. A digital ecosystem, on the other hand, represents the maximum value a company can derive from its interconnected networks.
In the concluding chapter, Subramanian provides examples from a range of industries to demonstrate how companies tailor their strategies based on where they perceive opportunities and competitive risks. Stating that companies can be categorized as digital adapters focused on production, early digital pioneers in consumption, later digital evolutionaries in consumption, or digital defenders focused on preserving what they have, Subramanian offers an action plan:
1. Map your digital ecosystems.
2. Assess your digital foundations.
3. Envision the boundaries of your ecosystem.
4. Choose a strategic point.
5. Develop the necessary capabilities.
Finally, the author stresses the importance for traditional companies to adopt new mindsets, frameworks, and skills to both compete in and seize opportunities in the digital era.
Let me remind you, according to Porter’s model, some industries with higher entry barriers include telecommunications (network infrastructure), pharmaceutical manufacturing (patents), and air travel (permits, fleet acquisition, and maintenance). Ultimately, these high entry barriers will reduce competition, as Porter asserts.
Subramanian, however, explains through examples that without the need for scaling or significant capital requirements, competitors can pose a threat in certain markets by leveraging digital platforms and the power of their technology to benefit from ecosystems, stressing the need for traditional companies to be prepared.
Bring it on! I’m taking all these insights to heart as I move forward…
But let’s be clear—while I’ve updated my to-do list, figuring out how to tackle these tasks is an ongoing challenge. I have some ideas, though, but time will tell. And don’t expect me to have all the answers—everyone will need to find their path. Maybe one day, after accomplishing something remarkable, I’ll write about it!
Sources:
(1) https://ihbir.org.tr/wp-content/uploads/ihbir-ekim.pdf
(2) Subramaniam, M. (2022). The Future of Competitive Strategy, The MIT Press, ss. 301.
(3) https://www.koclukmerkezi.com/porter-in-bes-guc-modeli/
(4) https://tr.wikipedia.org/wiki/Uzun_kuyruk
(5) The network effect is an economic phenomenon where additional users add value to a product or service. When a network effect is present, each new user joining the network increases the value of the product. This encourages even more users to join the network, contributing further value.
The best example of a network effect is the telephone. In the early days of technology, very few people had a phone in their homes. Moreover, for the network to be useful, their homes had to be physically connected.
As technology advanced, more people were able to get a phone, which increased the value of the entire telephone network. As the number of users grew, the value and utility of the entire network increased. This created a positive feedback loop where more people joined, adding more value to the whole network. Further, the increased usage led to exponential growth.
(6) https://bulutistan.com/blog/api-application-programming-interface-nedir/
(7)https://www.networkworld.com/article/963791/how-red-bull-racing-uses-iot-to-win.html
*The background in the cover image was designed with ChatGPT.
Note: This open-source article does not require copyright and can be quoted by citing the author.