Unlike the previous waves of competition driven by IT innovations in company processes, this wave is characterized by smart connected products that leverage embedded IT to create value.
The difference with smart connected products is that the products themselves are making the revolution possible. Their capabilities are unlocking new value and changing the company and competitive landscape.
Smart connected products represent the third wave of IT-driven competition. In the past, transforming company processes through value chain automation and integration was the mainstay of competition. However, smart connected products are different. Because IT is actually embedded in the products, it changes the nature of value creation and competition.
Figure 1: The Third Wave of IT-Driven Competition
As manufacturing companies become hybrid hardware and software companies, they must adopt new organizational structures.
Smart connected products are driving manufacturing companies to become hardware and software companies. This is significant because manufacturing firms, which have been pure hardware or hardware-centric companies, have been organized in similar ways for decades. Now, companies need new forms of collaboration and entirely new functional units.
Manufacturing companies must develop four key functional organizations:
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Unified Data Organization: Led by the Chief Data Officer, this organization captures, aggregates, and analyzes data across the entire organization.
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Tighter IT and R&D Collaboration: This reflects a new demand for IT in product development.
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Dev-Ops: The Dev-Ops group manages the product cloud; due to failures in the product cloud causing smart connected products to stop functioning, companies must diligently maintain, upgrade, and fix errors in the product cloud.
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Customer Success Management: Companies must ensure that customers derive maximum value from the products. Therefore, marketing is evolving into customer success management.
The following diagram represents a corporate organizational structure adapted to the new forms:
Figure 2: A New Organizational Structure
The competitive landscape is being reshaped by smart connected products that provide new functionalities.
New functionalities provided by smart connected products include:
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Monitoring: Products can monitor and report their own and their environment’s information in real-time, generating new data and insights.
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Control: Smart connected products can be controlled through embedded software or software residing in the cloud. Users have unprecedented capabilities to customize product functionalities and personalize interactions. Remote control of products increases employee safety and can reduce the number of employees needed.
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Optimization: Algorithms and analytics can optimize product operations, utilization rates, and predictive maintenance.
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Autonomy: Access to monitoring data, remote control, and optimization algorithms can enable product autonomy, allowing for self-operation, self-coordination, and self-diagnosis.
As illustrated in the following figure:
Figure 3: New Functions of Smart Connected Products
Many companies face a transformation that requires clearly defining their objectives and strategies in the realm of IoT. This strategy requires careful consideration and must be defined at the executive level to create a unique competitive position and communicate it with all relevant stakeholders. There are no right or wrong answers, only choices that must reinforce each other and define a coherent and unique overall strategic position for the company. The following 10 strategic choice frameworks can help define a company’s specific strategy (Figure 4).
Figure 4: Strategic Choices in IoT
The first series of questions revolves around product and service strategy, starting with: What capabilities should the company seek? Smart connected products greatly expand the number of potential product and service capabilities, but just because a company can offer many new features does not guarantee that it provides sufficient value to customers that generates profit for the company. The next question is how to best deliver these new product and service functionalities by determining how many features to embed in the product and cloud. Factors such as required response times, expected network availability, user interface complexity, and service events or product upgrades will influence these decisions. The next series of questions concerns the technological infrastructure needed to support smart connected products. The technology required to develop smart connected products is often something manufacturing companies have not encountered before, so companies need to invest heavily in specialized skills, technology, and infrastructure. Early pioneers like General Electric and Bosch invested heavily in internal roadmaps to gain first-mover advantages and retain better control over performance, functionalities, and product data. However, as seen with Intel in the microprocessor field and Oracle in the database field, new companies specializing in smart connected product technology combinations have emerged. Another relevant issue is whether to choose an open or closed system architecture; while closed models have clear benefits for companies controlling and optimizing systems, over time, as technologies become mainstream, the development of ecosystems and customer choices may also be limited, making closed approaches more challenging in the long run.
One of the biggest impacts of these choices is the continuous expansion and shifting of business boundaries. For example, in the agricultural equipment industry, products (like tractors) have become smart products with embedded technology that can connect with planters, harvesters, and tillage systems. More broadly, they can become farm management systems with data related to irrigation, seeds, fertilizers, weather patterns, etc. (“product systems”). Once singular-purpose products have now transformed into entire systems and platforms. When this happens, competition has expanded beyond agricultural equipment to broader industries, as illustrated in the following figure:
Figure 5: Expanding and Shifting Industry Boundaries – An Example from Agricultural Equipment
The foundation of IoT implementation: Digitalization of the physical world
The foundation for new business models enabled by IoT is the digitalization of the physical world. By leveraging state-of-the-art, horizontally scalable big data architectures, the massive amounts of information generated by billions of sensors can be managed efficiently, providing the basis for new Internet-based services. Cost-effectiveness may be the keyword here: from remote monitoring to M2M, connecting sensors and other components to back-end databases is not a new phenomenon. However, as we have discussed in other articles, previous solutions have been expensive and limited in scope and functionality. With advancements in technologies such as mobile device processors, (almost) ubiquitous wireless communication infrastructure, expanded cloud data management, and the emergence of IoT application platforms, it seems possible to lower the costs of creating real-time digital images of the physical world to a level that allows for the emergence of several new data-driven business models.
Of course, the data from the entire physical world will not just be a “mining” model – we expect to see many different digital models emerge, triggered by different application scenarios, company boundaries, partner ecosystems, and other parameters. We also expect these different digital models to evolve along the direction of IoT we have described earlier. Using hybrid technologies, different isolated digital models can be integrated to form more complex models, which also helps drive the transformation from subsets of things to IoT. These real-time digital models of the physical world enabled by sensors and big data will provide the foundation for many different application scenarios, many of which are currently even unknown.
The key to IoT success: Security and data privacy
Initiatives around establishing digital models of the physical world, including collecting application data and product data from new customers, have also raised concerns for many users. Security is one such concern. We not only need to ensure that all this “big” data in the back-end is managed securely; in a distributed environment like IoT, we need to ensure that the connections between different participants and the hardware and software running on the assets are also secure. The Stuxnet virus, the recent global outbreak of ransomware, and the hacking incident involving the Tesla Model S electric vehicle in 2014 illustrate how important this issue will become. Imagine a scenario where criminals hack into a hostage’s pacemaker or take control of an aircraft in flight…
The other side of the situation is less about external intruders and hackers and more about the company policies and governance processes for managing the newly acquired customer and product data. One aspect here requires compliance with regulatory requirements in different countries. On the other hand, transparency and respect for customer rights and privacy are critical. Many users rely on social networks like Facebook and LinkedIn to generate relevant updates and recommendations using their social media data. However, these users often feel frustrated by the complex and constantly changing data usage policies implemented by these companies.
Given the nature of the potential data that IoT solutions could acquire – not just voluntarily submitted social data, but data captured by possibly hidden sensors and other critical systems – it is crucial for the IoT industry to respect users and protect data privacy to alleviate user concerns. Otherwise, customers will not accept the significant risks associated with these new IoT solutions.
The timing of IoT implementation: Why now
Many people may ask: Why now? For the past decade, we have been waiting for the hockey-stick growth curve of the M2M market. Why is IoT taking off now? The answer to this question is partly about timing, partly about business models, and partly about technology. In recent years, we have seen IoT gather momentum that M2M never had. Business magazines like “Forbes” and “Der Spiegel” have begun publishing lengthy articles focusing on this topic, creating high levels of awareness. Now, many large enterprises have instructed their strategy departments to design IoT-based business models – even though we are still in the learning phase in this regard, we are seeing early business successes, such as ZipCar, DriveNow, Car2Go, and China’s shared bicycles like Mobike and ofo. Most major IT players now offer dedicated IoT implementation services, IoT middleware, and IoT hardware (or a combination of all three). Finally, the combination of different technologies seems to have reached a critical point where managing the complexity of IoT solutions has become more feasible and cost-effective, which includes:
Moore’s Law
The continuously improving hardware performance has raised the level of abstraction in the embedded space, providing the basis for semantically rich embedded applications and decoupling the hardware and software lifecycle of assets. The application revolution of smartphones will soon be replicated in the embedded space.
Wireless Technologies
From ZigBee to Bluetooth LE, from LTE/4G to dedicated low-power wide-area (LPWA) IoT communication networks, the foundation for “always-on” assets and devices is either available or being deployed.
Metcalfe’s Law
As the number of nodes connected to IoT increases, information and its value grow exponentially. As more remote assets are connected, it appears we are reaching a critical point.
Battery Technology
Improving battery quality has made new business models possible, from electric vehicles to battery-powered beacons.
Sensor Technology
Increasingly smaller and more energy-efficient sensors integrated into multi-axis sensors and sensor clusters, many of which are pre-installed in devices and assets.
Big Data Technologies
Technologies that enable the acquisition, processing, and analysis of vast amounts of sensor-generated data at an affordable cost.
Cloud
Scalable global platforms offering data-centric services to enable new IoT business models.
Conclusion
While no one knows exactly how many billions of devices will be connected by 2020, it seems that the underlying technological foundation for this growth is rapidly maturing, inspiring new business models and making it a very exciting field of work.
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