Innovation Concepts and Techniques for Digital Transformation in Mid-Market Firms

It’s never about the tech. It’s always about your mindset and culture.

Innovation has been a driving force of economic and social development throughout history, evolving from the early inventions of the Industrial Revolution to the digital breakthroughs of the 21st century. Today, as firms navigate rapid technological change, innovation — particularly digital innovation — stands at the heart of competitive strategy and organisational transformation. This introductory chapter provides a comprehensive overview of innovation as a foundation for understanding digital transformation in mid-market firms. It explores the historical evolution of innovation, defines key concepts (with an emphasis on digital innovation), and examines why innovation is crucial for organisational competitiveness and societal progress. It then reviews the main types and classifications of innovation (product, process, radical, incremental, architectural, digital), outlines typical innovation processes and lifecycles (from exploration to exploitation and diffusion), and identifies the sources of innovation (spanning individuals, organisations, networks, and external shocks). Further, it discusses patterns and theories of innovation (such as S-curves, dominant designs, and technology cycles) and highlights effective innovation management practices and techniques, especially for mid-sized enterprises. The chapter also considers the role of collaboration and open innovation in modern innovation ecosystems. Throughout, real-world examples — with a focus on mid-market firms undertaking digital innovation — are integrated to illustrate these concepts in practice. By establishing this broad context, the chapter sets the stage for developing a general framework for digital transformation in mid-sized companies in subsequent chapters.

Historical Context and Evolution of Innovation

Innovation is often perceived as a modern imperative, but its roots run deep through history. From ancient tool-making and agricultural advances to the great inventions of the industrial age (such as the steam engine and electricity), humans have long sought novel solutions to improve life and work. The Industrial Revolution (18th–19th centuries) marked a turning point when systematic invention and mechanisation transformed economies, demonstrating how new technologies (like the power loom or the locomotive) could disrupt industries and spur growth. Early economic thinkers began to recognise innovation’s role in driving progress. Notably, Joseph Schumpeter in the early 20th century framed innovation as the engine of economic development, coining the term “creative destruction” to describe how waves of new innovations incessantly render old technologies and industries obsolete, clearing the way for new growth (Schumpeter, 1934). This historical perspective highlights that innovation has always entailed a cycle of renewal — new ideas challenge the status quo, leading to both the demise of outdated practices and the rise of improved ones.

Throughout the 20th century, the innovation process became more formalised. Large firms established R&D laboratories (for example, Thomas Edison’s Menlo Park lab in the late 1800s, or Bell Labs in the mid-1900s) to systematically explore new ideas. Governments and universities also emerged as key players in scientific research and technological innovation, especially during periods of intense need such as wartime. World War II and the Space Race, for instance, acted as catalysts for breakthroughs (radar, computers, rocketry) that later diffused into civilian use, underscoring how external pressures can accelerate innovation. By the late 20th century, the advent of computers and the internet ushered in the digital revolution, dramatically speeding up the pace of innovation and enabling entirely new domains (software, online services, personal electronics). The concept of innovation itself expanded beyond just technological invention to encompass changes in business models and services, especially as economies became more knowledge-based.

Entering the 21st century, innovation cycles have become faster and more global. Digital technologies allow ideas to spread and be adopted at unprecedented speed, forcing even mid-sized firms to innovate continually to keep up. At the same time, thought leaders began to stress that while the context and velocity of innovation are new (“old question, new context”), the fundamental challenge of turning new ideas into value remains the same. In short, innovation has evolved from sporadic, individual genius-driven events to a core organisational discipline. This historical journey sets the context for why today’s businesses — including mid-market companies — must actively manage innovation as a continuous process, learning from past patterns of industrial change while navigating the new digital landscape.

Definitions and Key Characteristics of Innovation

Defining “innovation” is the first step in understanding how to manage it. Numerous definitions exist in the literature, but they converge on two core elements: novelty and value. In simple terms, innovation is more than just having a creative idea — it is about implementing something new that creates value or advantage. Schilling (2023) defines innovation as “the act of introducing a new device, method, or material for application to commercial or practical objectives” (Schilling, 2023). This highlights that innovation involves introducing something new (a device, method, material, etc.) with a practical purpose or application. Similarly, Smith (2024) emphasizes that an innovation must be novel and viable as a business concept — in other words, it’s not just an invention, but a new product or service that can be successfully brought to market or used by consumers: “an innovation, as well as being novel and new, has to be ‘a viable business concept’… something new and its implementation into a viable product that consumers can purchase” (Smith, 2024). Tidd and Bessant (2018) likewise describe innovation as a process — “turning opportunity into new ideas and putting these into widely used practice” (Tidd & Bessant, 2018). This process view reinforces that innovation is not just the moment of invention; it includes the diffusion or uptake of the new idea in practice.

Other authoritative definitions echo these points. For example, the OECD’s Oslo Manual definition (OECD/Eurostat, 2018) specifies that an innovation is “a new or improved product or process… that differs significantly from the unit’s previous products or processes and that has been made available to potential users (product) or brought into use by the unit (process)”. This definition is useful because it underscores two key characteristics:

(1) innovations can involve products or processes (not only tangible products), and

(2) an innovation must be implemented or made available to others, not just an idea on paper.

Additionally, some definitions boil it down to “the successful exploitation of new ideas” (Tether et al., 2005), emphasizing success and application. Across these definitions, the dual themes of novelty (something new or significantly improved) and value realization (successful implementation, adoption, or commercialization) are constant.

Two implications flow from these characteristics. First, innovation is broader than invention — invention is the first occurrence of a new idea, while innovation includes the full process of developing the idea and achieving impact with it. Second, innovation is not only about high technology or products. As Tidd and Bessant (2018) point out, innovation “is not just high technology” and “it’s not just products” (Tidd & Bessant, 2018) — meaning that innovations occur in low-tech sectors and can take forms like new services, processes, or business models, not solely new gadgets or scientific breakthroughs. For example, a new customer service model or a novel supply chain process can be just as innovative (and competitively significant) as a new smartphone or pharmaceutical drug. Innovation also isn’t confined to R&D labs; it can emerge from shop floors, customer interactions, or any part of an organisation.

Digital innovation refers specifically to innovations that are enabled by digital technologies or that digitize aspects of a product/service or process. Digital innovation often exhibits some distinctive characteristics: it typically involves software, data, or connectivity which confer properties like easy replication, network effects, and rapid scalability. Examples of digital innovation include the creation of entirely new digital products (e.g. mobile apps, cloud services), the digitalization of previously analog processes (for instance, moving from paper records to an integrated software system), or new business models built on digital platforms (such as ride-sharing or e-commerce marketplaces). What makes digital innovation especially powerful in today’s context is how it can blur traditional boundaries — for instance, turning a physical product into a service (as seen with software-as-a-service models) or enabling platform ecosystems where third parties continuously contribute improvements. Digital innovations also tend to diffuse quickly due to global connectivity, and they can produce winner-takes-most dynamics (as seen in platform markets). However, despite these particular traits, digital innovation still aligns with the core definition of innovation: it must involve something novel (often a novel application of computing, algorithms, or data) and it must create value (through improved performance, convenience, cost savings, new revenue streams, etc.). In summary, innovation in the digital era retains the age-old essence of new ideas yielding value, even as the tools and speed of innovation have transformed. This understanding of what innovation means — especially digital innovation — provides a basis for examining why it is so critical to organisations and society.

The Importance of Innovation for Organisational Competitiveness and Societal Change

Innovation is widely recognised as a key driver of competitive advantage for firms and a fundamental engine of economic and societal progress. At the organisational level, innovation is crucial for competitiveness and long-term survival. Markets today are dynamic — customer needs evolve and new technologies emerge rapidly — so companies that fail to innovate risk obsolescence. Introducing new products, services, or processes allows a firm to differentiate itself from competitors, capture new markets, become more efficient, or reduce costs. In many industries, a significant portion of revenue comes from products developed in the past few years, reflecting a “innovation or die” reality. By continuously innovating, firms can respond to disruptive changes and even become disruptors themselves, rather than being left behind. Schilling (2023) notes that technological innovation is often the single most important factor driving the competitive success of firms, more than other factors like scale or location. A firm that innovates effectively can offer unique value that competitors cannot easily match, whether through superior product performance, better pricing from process efficiencies, or entirely new offerings that define the market.

Innovation provides multiple strategic benefits to companies. Smith (2024) outlines several mechanisms through which innovation translates to competitive advantage. For example, a company can gain an edge by: offering something competitors cannot offer (a unique product or feature set); offering the same product or service but in ways others cannot match (for instance, faster delivery or lower cost achieved through process innovation); leveraging legal protections like patents to reap monopoly profits from a novel invention; timing innovation strategically (being the first mover in a new market or technology); building a platform on which other products or services depend (thereby shaping an ecosystem to its advantage); or even disrupting the market entirely by introducing a radically new concept that changes the rules of competition. All these are facets of innovation-led strategy. A classic example is Apple’s innovation with the iPhone — it combined a unique product design with software platform elements (App Store) and arrived at the right time, yielding a formidable competitive position. In contrast, firms that stick only to existing offerings can be overtaken by those that innovate new solutions or business models. Mid-market firms, in particular, often find that smart innovation can allow them to compete with larger players by carving out niches or adopting new tech faster than lumbering giants.

Beyond individual firms, innovation drives societal and economic advancement. Technological and social innovations have historically led to higher productivity, economic growth, and improvements in quality of life. There is a well-documented correlation between innovation and macroeconomic indicators like GDP growth. For instance, the widespread adoption of innovations such as electrification, computing, or the internet has corresponded with surges in productivity and global GDP per capita. Schilling (2023) observes that while measuring innovation’s impact purely through GDP has limitations, the contribution of technological innovation to societal progress is undeniable. Simply put, innovation tends to enable us to produce more value with the same or fewer resources — whether it’s a new medical treatment improving health outcomes, or a process innovation like automation increasing manufacturing efficiency. This is why nations and regions place emphasis on innovation policy (funding R&D, protecting intellectual property, nurturing startups, etc.) to fuel economic development and address societal challenges.

Innovation is also a catalyst for societal change in a broader sense. Consider how the innovation of the smartphone not only created thriving businesses but also transformed daily life and communication globally. Social innovations (like microfinance or telehealth services) address pressing societal needs in education, finance, healthcare, and more. In the current era, digital innovation is enabling new solutions to global problems — from climate tech (e.g., innovations in renewable energy and storage) to public services (e-government, smart cities). However, innovation’s impact on society is double-edged: while it creates growth and welfare, it also disrupts labor markets and industries. Schumpeter’s “creative destruction” underscores that while innovation-driven progress raises overall prosperity, it can cause short-term dislocation for firms or workers tied to older technologies. For organizations, this reinforces the competitive imperative to keep innovating and adapting. For mid-sized companies, innovation can be a great equaliser — a way to leapfrog constraints and participate in shaping the future, sometimes outpacing larger firms in agility. Indeed, during recent crises such as the COVID-19 pandemic, innovation proved critical for resilience; many mid-market companies rapidly adopted digital tools (from e-commerce to remote work technologies) to survive and even thrive. The pandemic dramatically accelerated digital innovation initiatives that had been “wishes and dreams” for mid-sized companies, making them reality, and “by far, no other force is driving more significant change” in business today than digital transformation (Farren, 2023). Innovation is important not only because it fuels profits or growth for individual firms, but because it underpins progress and adaptability in the economy and society at large.

Classifications and Types of Innovation

Innovations can be classified in multiple ways. Understanding the types of innovation helps clarify the differing nature, scope, and impact of innovative changes. Below are several fundamental classifications of innovation commonly discussed in the literature:

Product vs. Process Innovation: A basic distinction is between what is being innovated. Product innovations involve changes in an organisation’s outputs — new or significantly improved goods or services that a company offers to its customers. For example, the development of an electric vehicle by an auto manufacturer or a new mobile banking app by a financial firm are product innovations. Process innovations, in contrast, are changes in the way an organisation conducts its operations or creates its products. These include new manufacturing techniques, improved logistics and supply chain systems, or new service delivery methods. For instance, Toyota’s introduction of the lean manufacturing system (just-in-time production) was a major process innovation in the automotive industry, and the adoption of automated chatbot support is a process innovation in customer service. While product innovations tend to get more public attention (since they directly impact consumers), process innovations can significantly improve efficiency, quality, or speed, providing competitive advantages behind the scenes. It’s also worth noting that service innovation can be seen as a type of product innovation (with the “product” being an intangible service) or process innovation depending on context — for example, a bank devising a new mortgage approval process is innovating a service process.

Radical vs. Incremental Innovation: Innovations differ in degree of novelty and impact. Incremental innovations are small-scale improvements or adjustments to existing products, services, or processes. They build on a firm’s existing knowledge and competencies, and typically refine or enhance something that already exists. An example might be a software company releasing a new version of a program with improved features, or a manufacturer using a slightly more efficient component in a device. Incremental innovations are continuous and are crucial for maintaining competitiveness and improving productivity over time. Radical innovations, on the other hand, are breakthroughs that are very new and different from prior solutions, often described as “new to the world” or at least new to an industry or market. Radical innovations may involve fundamentally different technology or business models and can create entirely new markets or value networks. Examples include the first smartphone (which redefined the phone and computer markets), or the introduction of genome editing in biotech. Because radical innovations can render existing skills or products obsolete, they are sometimes competence-destroying for incumbent firms, whereas incremental innovations are usually competence-enhancing (building on what the firm already does well). The distinction between radical and incremental is a spectrum rather than a binary: what seems incremental in one context might be radical in another. Both types are important — a company needs incremental innovation for continuous improvement, and occasional radical innovation to leap ahead or respond to major changes. Many mid-market firms focus on incremental innovation day-to-day, but they must also be mindful of radical changes on the horizon that could disrupt their business.

Architectural vs. Component (Modular) Innovation: This classification, introduced by Henderson and Clark (1990), looks at whether an innovation changes the overall design configuration of a system or just one or more components. An architectural innovation involves reconfiguring the way components of a product or system are integrated, without necessarily introducing wholly new components. It is essentially a change in the architecture or linkages between components. For example, the first portable transistor radio in the 1950s rearranged components in a novel architecture (miniaturised, battery-powered, handheld device) even though the components (transistors, speakers, etc.) already existed — this created a new product category. Similarly, shifting from traditional taxi services to a ride-sharing platform (like Uber) could be viewed as an architectural innovation in service delivery — existing elements (cars, drivers, riders, GPS) were reconfigured via a digital platform. Component (or modular) innovations involve changes to one or more components of a product system, without altering its overall architecture. For instance, using a new type of battery in a smartphone is a component innovation — the phone’s architecture remains the same, but a key module has improved. Component innovations can be significant (a much more powerful computer chip) but they keep the system design intact, whereas architectural innovations can be tricky for incumbents because they may require a shift in system design knowledge (firms competent in old architecture might struggle with the new architecture). Architectural innovations often catch established firms by surprise, as observed in cases like Xerox and the emergence of small desktop copiers (which were an architectural rethink of copier design).

Disruptive Innovation: Though not explicitly listed in the prompt, it’s worth mentioning disruptive innovation as a concept closely related to radical and architectural innovation. Coined by Clayton Christensen (1997), a disruptive innovation is one that initially may underperform on traditional metrics but offers other advantages (often being simpler, cheaper, or targeting an unmet need), and eventually upends incumbents by reshaping market expectations. A classic example is how digital photography disrupted film photography (Kodak’s core business) — early digital cameras had lower image quality (a “weakness” by old standards) but offered the new convenience of instant image sharing and zero per-picture cost, which over time destroyed the film market. Disruptive innovations often arise at the low end or in niche markets and improve over time to challenge the mainstream. For mid-market firms, understanding disruptive innovation is important: they can be victims if they cling to older models, or beneficiaries if they themselves exploit a disruptive niche strategy against larger competitors.

Digital Innovation: As noted earlier, digital innovation can cut across the above categories but deserves emphasis. Digital innovation might manifest as a product innovation (e.g., a new AI-powered software tool), a process innovation (e.g., implementing machine learning to optimize supply chain logistics), or a business model innovation (e.g., moving from selling products to offering a subscription service via an app). What unites these is the use of digital technology (software, hardware, networks, data) as a key enabler. Digital product innovations include things like developing a mobile payment app or a cloud-based analytics platform. Digital process innovations might include adopting robotic process automation in back-office operations or using big data analytics to improve decision-making. Many digital innovations are also platform innovations — creating a digital platform that connects multiple user groups (like Airbnb connecting hosts and travelers) — or ecosystem innovations, where firms innovate new roles or collaboration models in a digital ecosystem. For mid-sized firms, leveraging digital innovation can be a way to scale services or reach global customers without the heavy asset investments that older models required. However, digital innovation also demands new capabilities (such as cybersecurity, software development, data analysis) that mid-market companies must often build up or acquire through partnerships.

These classifications are not mutually exclusive — any given innovation may be described along several dimensions. For example, the introduction of electric vehicles by Tesla was a radical and product innovation, which also forced architectural changes in car design (electric drivetrain instead of combustion engine architecture) and proved disruptive to the auto industry’s traditional players. The key takeaway is that innovation comes in many flavors. An effective innovation strategy will consider all types: improving internal processes and core products incrementally, while also scanning for opportunities to make bigger leaps (radical or architectural changes), especially through digital technologies in today’s environment. Notably, innovation is not confined to technology or manufacturing — it can be in organisational structures or marketing methods as well (sometimes called administrative or managerial innovation). For instance, a mid-market firm might innovate by adopting a new organisational design that empowers cross-functional teams (a managerial innovation), or by implementing a novel marketing campaign on social media that goes viral (a marketing innovation). In sum, by classifying innovations, we gain a richer understanding of the terrain of change that organisations must navigate and the varied approaches they can employ.

Innovation Processes and Lifecycle (Exploration, Exploitation, Diffusion)

Innovations do not usually emerge fully formed in a single moment; rather, they go through a process or lifecycle from initial idea to widespread adoption. Understanding this process is crucial for managing innovation effectively. While models vary, a typical innovation lifecycle involves stages of exploration, exploitation (development and implementation), and diffusion.

Exploration (Ideation and Invention): This is the starting point of innovation — the search for new ideas and opportunities. Exploration involves creative processes such as research, brainstorming, experimentation, and risk-taking to generate novel concepts. It often requires an environment that tolerates failure and encourages curiosity. In this phase, organisations engage in activities like basic R&D, market research for unmet needs, or simply encouraging employees to suggest improvements. The output of exploration is an invention or a pool of promising ideas. James March (1991) famously contrasted exploration (activities aimed at new possibilities) with exploitation (activities aimed at refining and implementing known ideas), arguing that firms need to balance both. During exploration, a firm might be asking questions like: What if we tried a completely new approach? Is there a different way to solve this customer problem? For example, a mid-market tech firm’s exploration might involve prototyping a new software algorithm in its lab, or a manufacturer experimenting with a novel material.

Exploitation (Development and Implementation): Once a new idea has been conceived, the next step is turning that concept into a viable innovation. This stage includes development, engineering, testing, and market introduction. It’s about exploiting the idea’s potential by investing resources to make it practical and valuable. In product development terms, this covers everything from design and engineering to pilot testing and commercial launch. Many firms use structured innovation processes or new product development (NPD) processes to manage exploitation, such as Stage-Gate models (where an idea must pass through a series of “gates” or checkpoints — concept, feasibility, prototype, etc. — before full launch) or agile development cycles (especially for software, using iterative sprints to develop and refine the product). During exploitation, the innovation is refined: prototypes are built and improved, business models are defined, and go-to-market strategies are prepared. For example, after coming up with a new gadget idea in exploration, a company in exploitation mode will design the device, test it in-house and perhaps in a focus group, iterate on the design, and prepare manufacturing and distribution. This stage requires different capabilities than exploration — more project management, engineering discipline, and attention to detail in execution. It also often involves organisational learning — initial assumptions get tested and feedback is used to improve the innovation. Both exploration and exploitation benefit from feedback loops, but exploitation is where the concept truly becomes an innovation through implementation.

Diffusion (Adoption and Spread): Having developed an innovation and introduced it, the final part of the lifecycle is its diffusion — the process by which the innovation spreads through a market or society and is adopted by users or other organisations. Not all innovations diffuse successfully; some remain niche or even fail to catch on. Diffusion is influenced by factors studied in classic diffusion of innovations theory (Rogers, 1962), such as the innovation’s relative advantage over existing solutions, its compatibility with existing practices, its complexity (ease of use), trialability (ability to experiment with it), and observability (visible results to others). Typically, diffusion follows an S-curve pattern: initial adoption is slow as the innovation is unfamiliar and perhaps unrefined; then if the innovation is worthwhile, adoption accelerates rapidly as more people or organisations become aware of it and its benefits, and it eventually slows as the market becomes saturated. In other words, there is usually a small group of innovators and early adopters who try it first, then a big uptake by the early majority and late majority once the innovation has proven itself, and finally laggards who adopt last or never. This technology diffusion S-curve has been observed in everything from consumer products (e.g., the spread of smartphones) to industrial process adoption. Schilling (2023) notes that technology diffusion often takes longer than information diffusion — meaning hearing about a new idea is quick, but actually implementing it (which may require new knowledge or complementary resources) can be much slower. For instance, many people might hear about a new AI tool today, but firms may take years to fully adopt it into their processes because they need skilled personnel and system integration (complementary resources).

In practice, the innovation process is not strictly linear; it can be iterative and feedback-rich. Often, after initial diffusion, feedback from the market will lead back to new ideas (exploration) or modifications (further exploitation). Additionally, some models describe an upfront idea generation stage, followed by concept development, prototyping, commercial evaluation, launch, and post-launch learning. Tidd and Bessant (2018) describe the innovation process in four phases: search (for opportunities), select (choosing an idea to pursue), implement (developing and launching), and capture value (ensuring the innovation’s benefits are realised and measured). In all cases, the goal is to manage innovation from the fuzzy front-end of ideation to the tangible back-end of result delivery and uptake.

A critical part of the innovation lifecycle in organisations is managing the exploration-exploitation balance. Exploration is necessary to bring in new ideas, but it can be uncertain and not immediately profitable; exploitation of existing knowledge is more immediately fruitful but can lead to stagnation if done in isolation. Successful innovators, especially mid-sized companies with limited resources, often adopt strategies for balancing these, such as dedicating a portion of time to exploratory projects (e.g. Google’s famous “20% time” for employees to tinker with new ideas) while maintaining focus on core business exploitation. Some firms establish separate units or teams — one to explore disruptive innovations and another to exploit and incrementally improve core products (the ambidextrous organisation approach).

Finally, after an innovation is launched, the diffusion phase sometimes loops back into new innovation cycles: as the innovation spreads, competitors react (perhaps spurring further innovation), or users suggest enhancements (feeding into the next incremental innovation), and so on. Part of managing innovation is also managing its diffusion — for example, firms may use marketing, demos, or standard-setting efforts to accelerate adoption of their innovation in the industry. They may also plan for sequential diffusion (target lead adopters first, then broader market). In summary, innovation should be viewed as a journey from novel idea to implemented change to widespread impact. Each stage of this journey — idea generation, development, and diffusion — requires different management approaches and metrics for success. Mid-market companies, in particular, need to be adept at guiding limited promising ideas through this pipeline efficiently, as they cannot afford a high failure rate in exploitation or very slow diffusion of their innovations.

Sources of Innovation

Where do innovations come from? Understanding the sources of innovation helps organisations cultivate and tap into those sources proactively. Research and experience show that innovation can originate from various levels and actors — ranging from lone inventors to broad networks and even unexpected external events. Key sources include individuals, organisations (internal efforts), collaborative networks, and external shocks or changes in the environment.

Individuals: Often, innovation begins in the minds of creative individuals. Throughout history, individual inventors and entrepreneurs have been the spark behind major innovations — from Thomas Edison to modern tech founders. Within organisations, employees are a critical source of ideas. Schilling (2023) distinguishes between individual creativity and organisational creativity. Individual creativity is influenced by a person’s expertise, creative thinking skills, and motivation. Some individuals, especially those who are curious, passionate, and willing to challenge norms, generate innovative ideas prolifically. In practice, individuals as sources of innovation can be independent inventors, users, or employees. Independent inventors might work solo or in garages, contributing inventions that companies later commercialise (for example, the invention of the Post-it adhesive by a 3M scientist, or the invention of the World Wide Web by Tim Berners-Lee). Lead users (a term from Eric von Hippel’s work) are those pioneering customers or users who modify products to serve their needs — their innovations (such as mountain bikers inventing new bike suspensions) can become mainstream. Employees inside a firm often come up with improvements because they see problems and opportunities first-hand. For mid-sized companies, harnessing individual innovation means creating channels for employees to propose ideas (e.g., internal idea contests, suggestion systems) and empowering “intrapreneurs” within the company.

Organisations (Internal R&D and Development): Organisations themselves can systematically generate innovation through dedicated research and development (R&D) activities and an innovation-friendly culture. A firm’s internal R&D labs or innovation teams are deliberate sources of new products and technologies. Companies invest in R&D to develop new knowledge that can lead to innovations — this is often measured by R&D spending or number of patents as a proxy for innovation capacity. Beyond formal R&D, companies can source innovation from any department: marketing might innovate on customer engagement strategies, production might innovate in processes, etc. Organisational factors such as a culture that encourages experimentation, leadership that sets innovation as a strategic priority, and incentives for innovation (like rewards for successful ideas) all contribute to making the organisation a fertile source of innovation. Tidd & Bessant (2018) describe how management can foster innovation by setting strategy, allocating resources, and building effective processes for moving ideas to market. Importantly, organisations also gather market intelligence — feedback from customers, analysis of competitors, and market trends — to inform innovation opportunities (often called demand-pull innovation, as opposed to knowledge-push from R&D). For mid-market firms with limited R&D budgets, smart organisation of innovation might involve focusing on customer-centric innovation (leveraging insights from sales or support teams) or incremental improvements that differentiate them in niches.

Inter-organisational Networks and Collaboration: Innovation frequently arises from the intersection of ideas and capabilities that reside in different organisations or domains. Networks of collaboration — such as partnerships, alliances, joint ventures, consortiums, or informal communities — are powerful sources of innovation. Many high-technology innovations now result from collaboration between firms, universities, and research institutes. For example, the development of new pharmaceuticals often involves biotech startups (with novel ideas), larger pharma companies (with development and marketing capabilities), and university research (for cutting-edge science). These networks allow sharing of knowledge and complementary assets. The concept of open innovation, popularised by Chesbrough (2003), encapsulates this idea: firms should not rely only on internal ideas, but tap external sources and also allow their own unused ideas to flow out to others for mutual benefit. In practice, open innovation means working with suppliers, customers, or even competitors, and using external R&D (licensing, acquisitions, crowdsourcing ideas from the public etc) to supplement internal efforts. Collaborative innovation networks can be formal (like a strategic alliance where two companies co-develop a product) or informal (like industry gatherings, or the open-source software community where volunteers globally contribute to a project). According to Schilling (2022), firms often collaborate to gain speed, cost efficiencies, access to expertise, and risk-sharing in innovation. For mid-sized enterprises, networks are particularly valuable sources of innovation because they may not possess all necessary resources in-house. By partnering with a university for research, or joining an industry consortium, a mid-market firm can leverage cutting-edge knowledge without bearing the full cost. User communities and customer co-creation are another network source: for instance, a mid-market outdoor gear company might involve enthusiastic customers in designing new products (community-sourced innovation).

External shocks and environmental changes: Sometimes, innovation is triggered by external events or crises that force organisations to adapt rapidly. External shocks include things like economic crises, wars, pandemics, natural disasters, or significant regulatory changes. These events can create urgent new problems that demand innovative solutions or remove old constraints that held back change. For example, the COVID-19 pandemic in 2020 spurred a wave of innovation in remote work technologies, virtual services, and medical devices (such as rapid development of mRNA vaccines) as organisations and societies scrambled to respond. In the mid-market segment, companies that had been slow to digitize were suddenly pushed to implement e-commerce, automation, or digital collaboration tools to survive lockdowns — effectively accelerating their digital transformation by years. Wars and defense needs have historically accelerated innovation in areas like aeronautics, computing (the first digital computers were aided by WWII codebreaking efforts), and the internet (originally a DARPA project for robust communications). Similarly, changes in consumer preferences or social movements can act as external catalysts — for instance, rising environmental awareness has driven many firms to innovate in sustainable products and cleaner processes. While external shocks can be devastating, they also “reset” the competitive landscape and reward innovators: those mid-sized firms agile enough to pivot and innovate under external pressure often emerge stronger (as seen with companies that switched to producing sanitizers or PPE during COVID-19, or those that seized new market gaps created by the crisis). Therefore, scanning the external environment for threats and opportunities is a key part of innovation strategy. Some innovations are directly born from such scanning — e.g., anticipating a new law that will demand lower emissions, an automotive supplier might proactively develop cleaner engine technology.

It’s important to note that these sources often interplay. For example, an individual inventor might rely on a network to commercialise an idea they developed, or an organisation’s internal R&D might be guided by insights from users (individuals external to the firm). A healthy innovation ecosystem in a company leverages all sources: encouraging individuals internally, investing in internal R&D and idea management, engaging with external collaborators and networks, and remaining adaptable to external stimuli. Mid-market firms typically have fewer slack resources than large firms, so they benefit greatly from tapping external sources (networks, partnerships) and from fully utilising the creativity of their people.

In sum, innovation can originate from anywhere — a lone genius tinkering in a garage, a cross-functional team inside a corporation, a startup partnering with a big company, or a sudden jolt from the outside world. Knowing this, organisations should consciously cultivate these sources: hire and develop creative talent, build a culture that motivates employees to innovate, connect with the broader innovation network in their industry, involve customers and suppliers in ideation, and stay vigilant to external changes. By doing so, mid-sized companies can punch above their weight in innovation, accessing ideas and technologies beyond what their size might traditionally permit.

Patterns and Theories of Innovation (S-Curves, Dominant Design, Technology Cycles)

While innovation can sometimes seem random or chaotic, research has identified certain patterns and theoretical models that describe how innovations evolve and how industries change over time. Key among these are the S-curve models of innovation and diffusion, the concept of a dominant design, and the idea of technology cycles in an industry. These frameworks help in understanding and anticipating the trajectory of innovations.

S-Curves in Technological Improvement: When we plot the performance of a technology against the effort or time invested, we often see an S-shaped curve. In the early stages of a new technology, progress is slow — performance is low and improving it is difficult because the underlying principles are not well understood (the low, flat “toe” of the S-curve). As the technology matures a bit, a tipping point is reached where understanding improves, the design becomes refined, and performance increases rapidly for a given amount of effort — this is the steep middle part of the S-curve. Eventually, the technology approaches its inherent limits (physical or practical limits), and further improvements become harder to achieve, yielding diminishing returns despite high effort — this is the upper flattening of the S-curve. For example, consider the improvement of internal combustion engine efficiency over decades: initially gains were slow, then engineering breakthroughs led to big jumps in power and efficiency, and in recent years improvements have slowed as the engine nears thermodynamic limits. Schilling (2023) illustrates this S-curve behavior, noting that plotting performance vs. time can be misleading unless effort is accounted for, since effort may not be constant over time. One implication of the S-curve is that a technology will eventually plateau, and further significant advancement may require a shift to a completely new technology (a new S-curve). This guides strategic thinking: firms riding a current technology must be ready to switch to or develop the next technology before improvements run out. A classic case is lighting: incandescent bulbs improved incrementally (approaching their limit), and then a shift to fluorescent and later to LED technology allowed a jump to new S-curves of efficiency.

S-Curve of Diffusion (Adoption): Separate from the performance curve is the S-curve of innovation diffusion, which tracks how an innovation is adopted in a population over time. As noted earlier, diffusion starts slow (only a few innovators adopt initially), then picks up speed as the early majority join in, and finally slows down as the market saturates and only laggards remain unadopted. This too forms an S-shape when cumulative adopters are plotted over time. Understanding diffusion patterns is crucial for strategy: for example, if a firm is introducing a new product, they might expect low sales at first, then rapid growth if the product gains traction, then eventual leveling off. Companies also classify adopters (innovators, early adopters, early majority, late majority, laggards) to tailor marketing strategies at each phase. One should also note factors that influence the steepness of the S-curve (how fast diffusion happens) — such as network effects (products that become more valuable as more people use them, e.g. social networks, tend to diffuse very fast after a point) or requirement of complementary infrastructure (e.g. electric cars need charging stations, which initially slows diffusion). Schilling points out that technology diffusion can be slower than information diffusion because adopting a new technology may require learning and investment, whereas information (knowledge of an innovation) can spread very quickly in the internet age. The S-curve model of diffusion helps firms anticipate and plan: for instance, a mid-market firm adopting a new technology internally might plan for an initial pilot (small scale use), then broader rollout as confidence grows and benefits are proven, and finally full integration.

Dominant Design and Technology Cycles: Research by Utterback, Abernathy, and later Tushman and Anderson has shown a pattern in many industries of technological change proceeding in cycles. The cycle often begins with a technological discontinuity — a radical innovation or a big technological change that disrupts the status quo (for example, the invention of the digital camera in the photography industry, or the emergence of the smartphone in mobile devices). This discontinuity initiates an Era of Ferment (also called a fluid phase) characterized by high uncertainty and experimentation. During this period, many different designs compete as firms and entrepreneurs explore the new technology’s potential. There is often a proliferation of variants and a lack of consensus on the best configuration. For instance, in the early years of automobile development (1900s), there were steam, electric, and gasoline cars in all shapes and styles — a ferment of innovation.

Over time, as the industry and customers learn what works best, one design (or a set of design features) emerges as the most popular or effective solution — this becomes the dominant design. A dominant design is essentially a standard architecture for the product that most producers and consumers accept. For automobiles, the gasoline internal combustion car with four wheels, similar controls and layout, became the dominant design by the 1920s. When a dominant design emerges, it tends to end the era of ferment; the industry enters an Era of Incremental Change, where the focus shifts to refining and improving the established dominant design rather than inventing fundamentally new architectures. Firms concentrate on process innovation (to produce the design more efficiently) and incremental product innovation (to add features or improve quality on the basic architecture). This phase is marked by consolidation in the industry (some firms drop out if they bet on losing designs, others scale up around the dominant design) and more predictable, routine innovation. The dominant design concept explains why innovation often comes in bursts — a flurry of radical invention and then a period of stability. It also highlights how early in an industry, being flexible and experimental is key, whereas later, efficiency and incremental improvement dominate.

The cycle completes when a new discontinuity eventually comes along, starting a new era of ferment that might overthrow the previous dominant design. In other words, the cycle is:

Discontinuity -> ferment -> dominant design -> incremental evolution -> next discontinuity.

A modern example: in the phone industry, the introduction of smartphones (particularly the iPhone’s design integrating a full touchscreen, app ecosystem, etc.) became a dominant design around 2007–2010, and since then most innovation in smartphones has been incremental (better cameras, faster processors, etc.). We might now be on the cusp of a new discontinuity with technologies like wearables or augmented reality devices that could eventually replace the smartphone paradigm.

For managers, these patterns provide strategic insight. In a ferment phase, the ability to experiment and pivot is crucial; there is an opportunity for new players to leap ahead. In the dominant design phase, the basis of competition shifts to cost, quality, and distribution around the standard design; large firms often excel here with economies of scale. Mid-sized firms must decide whether to adhere to the dominant design and compete on refinement or to try to introduce the next disruptive change. Being aware of where the industry stands in the cycle can inform innovation portfolio choices (e.g., invest in radical innovation if a paradigm shift seems imminent, or focus on process improvement if the current design is king). It’s also notable that dominant designs are not always purely “the best” technically — they sometimes gain ground due to network effects, timing, or complementary products (for instance, the QWERTY keyboard layout is a dominant design that persists despite claims of more efficient layouts, due to historical lock-in).

In addition to S-curves and tech cycles, there are other innovation theories and patterns scholars have identified, such as long waves or Kondratiev cycles (the idea that major technological revolutions drive ~50-year economic cycles, e.g., the age of steam, age of electrification, age of information), or innovation ecosystems theory (focusing on how a network of actors collectively enable innovation, especially relevant in digital platform contexts). Another concept is path dependency in innovation — the notion that past choices commit industries to certain trajectories (like how the layout of a city can constrain what transportation innovations make sense).

For digital innovation, one important pattern is the role of network effects and platform dynamics — innovation on platforms can happen rapidly because of positive feedback loops (the more adopters, the more attractive the innovation, which begets more adopters). This has led to winner-take-most outcomes in some tech markets, which is a deviation from some older industries where multiple competitors could coexist with similar designs.

Nevertheless, the core theories of S-curves and cycles remain highly useful. They remind us that innovation is not a linear, steady process but often comes in surges and plateaus. They also underscore why timing matters: introducing a new technology too early (before the world is ready) can fail, just as introducing it too late (after a dominant design is set) can mean playing catch-up. Mid-market companies can use these insights to decide when to invest in radical innovation versus when to focus on incremental improvements. For example, a mid-sized firm might observe that their industry’s main technology is plateauing in performance (upper S-curve flattening) and thus decide to invest in a next-generation technology to get ahead of larger competitors who are still focused on squeezing the last gains from the old one. Conversely, if a dominant design is still reaping returns, a firm might choose to innovate around that standard (perhaps finding a niche specialization) rather than deviate too far.

Innovation patterns like S-curves and technology cycles provide a “big picture” view of how innovations develop and succeed over time. They complement the firm-level view by putting it in an industry and technology context. By studying these patterns, firms (including those in the mid-market) can better strategize their innovation efforts and avoid pitfalls — such as clinging to a dying technology or missing the emergence of a game-changing design.

Innovation Management Practices and Techniques for Mid-Sized Enterprises

Effectively managing innovation is a challenge, especially for mid-sized enterprises that must innovate with limited resources and organizational capacity. Innovation management encompasses the strategies, structures, and processes that organisations use to encourage and steer innovation. Large firms often have formal R&D departments, innovation funnels, and significant budgets, whereas mid-market firms may not have those luxuries — but they can still excel at innovation by adopting appropriate practices and a supportive culture. Here, we discuss key innovation management practices and techniques, with an emphasis on their relevance to mid-sized companies.

Leadership and Strategy for Innovation: Successful innovation management starts from the top. In medium-sized companies, leadership commitment is often the decisive factor in whether innovation thrives. Unlike in a multinational where some innovation may happen in spite of lukewarm leadership, a mid-market firm’s CEO or executives typically wear multiple hats and set the tone for all operations. Therefore, making innovation a clear strategic priority is crucial. This means leaders should articulate how important innovation is for the company’s future, allocate time and funding to innovation initiatives, and personally engage in innovation projects (to champion them and remove roadblocks). Strategic alignment is also key: the firm should have an innovation strategy that aligns with its overall business goals. For example, if a mid-sized firm’s strategy is to become a leader in a certain niche market, its innovation efforts should focus on products or services for that niche, rather than scattered experiments. A clear innovation strategy helps decide the balance between incremental and radical projects, and between internal and external sourcing of innovation.

Creating an Innovative Culture: Culture is often cited as a make-or-break element in innovation. An innovative culture is one that encourages employees to share ideas, experiment, and not fear failure. Mid-sized enterprises can cultivate such a culture through practices like: giving employees dedicated time for creative projects (even if only a few hours a week), recognising and rewarding innovative suggestions or successful implementations, and training employees in creative thinking and problem-solving. Since mid-market firms might not have formal R&D, every employee can be seen as a potential innovator. Some companies implement programmes like internal idea competitions or hackathons to stimulate creativity and surface ideas from all corners of the business. Involving as many employees as possible not only generates more ideas (leveraging what some call the “swarm intelligence” of the workforce), but also builds buy-in and enthusiasm for innovation. When staff at all levels feel they have a stake in innovation, execution of new ideas tends to be smoother. Additionally, fostering cross-functional collaboration is important — many innovations happen at the intersection of different knowledge areas, so breaking down silos (for instance, having marketing, operations, and IT work together on a new service idea) can enhance creativity. Mid-sized firms, due to their smaller scale, sometimes have the advantage of more fluid communication across the organisation, which should be leveraged to build an innovation-friendly environment.

Structured Processes and Tools: Even though innovation benefits from creativity, it also needs some structure to move ideas to outcomes. Mid-sized firms can adopt lightweight versions of innovation processes tailored to their size. For example, using a formal idea management system (even a simple one) to collect and evaluate ideas ensures promising suggestions aren’t lost. Some mid-market companies use innovation management software to track ideas, ongoing projects, and results. Others may establish an “innovation committee” or assign innovation champions who shepherd ideas through the development process. Techniques like Stage-Gate (proposed by Robert Cooper) can be scaled down for a mid-sized context: the idea is to have clear stages (idea, concept development, business analysis, prototyping, testing, launch) and criteria at each “gate” to decide whether to continue the project. This avoids pouring too many resources into flawed ideas and helps focus on the most viable ones. However, heavy bureaucracy can stifle a small company, so it’s about finding the right balance — enough process to maintain discipline, but not so much that it quashes creativity or speed. Many mid-sized tech firms opt for Agile project management for innovation — using iterative development (as in software sprints) to quickly test and refine concepts. Agile methods emphasize flexibility, customer feedback, and rapid prototyping, which can be very suitable for the resource constraints of mid-market companies (fail fast, learn fast, without huge sunk costs). Alongside process, having the right tools is beneficial. For digital innovation especially, tools for collaboration (like Slack, Confluence, or digital whiteboards for brainstorming) and rapid prototyping (software frameworks, 3D printers for hardware prototyping, etc.) can accelerate innovation.

Lean Innovation and Resource Efficiency: Mid-market firms often cannot afford large-scale, long-term R&D projects with uncertain payoffs. They must be shrewd in how they invest in innovation, practicing what is sometimes called lean innovation. This concept, akin to the Lean Startup methodology (Ries, 2011), involves testing the market or technical feasibility of ideas with minimal resources, iterating based on feedback, and killing off ideas that don’t show promise early (to conserve resources for others). For instance, instead of fully developing a new product in secret, a mid-size company might release a minimum viable product (MVP) or pilot to gauge customer interest, then pivot or persevere based on the response. Lean innovation also encourages “small bets” — running a portfolio of small experiments rather than betting the farm on one big project. This approach can actually de-risk innovation: it accepts that not every idea will succeed, so it’s better to learn which ones won’t quickly and cheaply. Culturally, it goes hand-in-hand with allowing failure in the short term as long as it yields learning. Many mid-sized firms have found success by closely involving customers in this lean process, effectively co-creating solutions and validating them in real time.

Employee Engagement and Skill Development: Innovation management for mid-sized enterprises should include developing the innovation capabilities of their people. This means training employees in creative problem-solving methods (like design thinking, TRIZ, etc.), encouraging diverse teams (diversity can spark creativity by bringing different perspectives), and hiring for traits like curiosity and adaptability. It also means giving employees the resources and time to innovate. Even a modest budget for employee-led projects or some “slack time” can yield dividends in useful improvements or even new products. Some mid-market companies implement internal incubators or labs where employees can work on new ideas temporarily outside of their regular job duties. Others rotate staff through different roles to broaden their perspective (leading to cross-pollination of ideas). Ensuring that employees have up-to-date skills, especially digital skills, is crucial for digital innovation. The mentioned digital skills gap often affects mid-sized firms disproportionately, as they may struggle to attract top tech talent against larger competitors. Addressing this via training or creative hiring (e.g. partnering with local universities or offering interesting projects as a lure) is important for building an internal engine of innovation.

Metrics and Incentives: “You get what you measure” is a common saying in management. Mid-market firms should think about how to measure innovation performance. This could include tracking the number of new ideas submitted, number of projects in the pipeline, percentage of revenue from products introduced in the last 3 years, improvement in process KPIs due to innovations, etc. While smaller companies might not need complex dashboards, having some metrics helps keep innovation on the radar and justifies investment. Coupled with metrics, incentives should be aligned to encourage innovation. This doesn’t necessarily mean large financial rewards (which might not be feasible), but recognition, career advancement for those who contribute to successful innovations, or team-based bonuses when innovation targets are met. Even non-monetary rewards like public recognition in company meetings for innovative efforts can motivate employees.

Overcoming Mid-Market Constraints: Mid-sized enterprises face unique constraints — limited capital, fewer specialized staff, less formalised processes — but these can be mitigated with smart practices. One technique is outsourcing or partnering for innovation: if a company lacks an internal capability (say, data analytics expertise to develop a new digital service), they can partner with a specialist firm or consultant, or join a cooperative research initiative. Another practice is tapping government grants or innovation programs targeted at SMEs (many regions have funding to support small and medium business innovation, recognizing their resource constraints). Additionally, mid-sized firms can use their size to their advantage by being more nimble than large corporations: they can often make decisions faster and implement changes more quickly (less bureaucracy). To capitalise on this, the organisation should keep decision-making around innovation relatively flat and decentralized — empower the innovation project teams to make calls without having to run everything up a long chain of command. This agility is one of the best “weapons” a mid-market firm has in innovation contests against bigger rivals.

In essence, innovation management in mid-market firms is about creating the right environment (culture and leadership commitment), using smart processes (structured but lean), engaging and enabling people, and leveraging the firm’s agility and external resources. Tidd and Bessant (2021) note that managing innovation requires attention to organisational context — there is no one-size-fits-all. A mid-sized company must tailor known best practices to what works in its context. For example, a 200-person company might not need a dedicated R&D lab, but it might benefit from an innovation task force that meets monthly to review progress on key projects. It might not afford a full-time Chief Innovation Officer, but could assign a respected senior manager to coordinate innovation initiatives part-time. The goal is to embed innovation into the company’s DNA — part of “how things are done” daily — rather than a one-off program.

One real-world example is German Mittelstand companies (mid-sized, often family-owned industrial firms renowned for innovation). Many of these companies excel by focusing on a narrow product domain and continuously innovating within it, involving frontline engineers and customers in iterative improvements. They often have flat hierarchies and an engineering-oriented culture that prizes problem-solving. Another example: a mid-sized UK retail company might set up a digital innovation team to develop an e-commerce platform, using agile sprints and involving store employees to integrate online-offline experiences. By doing so, they can implement a digital transformation relatively quickly compared to larger competitors, as was the case with several retail and hospitality firms during the pandemic that pivoted to online ordering and delivery using small, dedicated innovation teams.

Ultimately, for mid-market firms, effective innovation management can be the difference between gradual decline and robust growth. It allows them to differentiate, to find new efficiencies, and to occupy valuable strategic positions that might otherwise be dominated by larger players. And because mid-market companies form a substantial part of many economies (often referred to as the “middle market” that collectively generates significant GDP and employment), their innovation success has wide-reaching implications. That is why understanding and improving innovation management in this sector is so important.

The Role of Collaboration and Open Innovation Models

In the contemporary innovation landscape, no firm is an island — and this is especially true for mid-sized firms that may lack extensive in-house resources. Collaboration and open innovation have become critical approaches to extend a company’s innovative capacity by tapping into external ideas, knowledge, and markets. This section examines how collaboration, in various forms, contributes to innovation and why open innovation models are so valuable, with examples relevant to mid-market companies.

Open Innovation is a paradigm introduced by Henry Chesbrough (2003) which posits that companies should use external as well as internal ideas, and internal and external paths to market, as they seek to advance their technology. In an open innovation model, the boundaries of the firm become more permeable: ideas flow in from outside and flow out from inside. This is a shift from the traditional “closed innovation” model where R&D was done in-house, and the company would attempt to vertically integrate the whole process from idea to market. For mid-sized enterprises, open innovation can be a game-changer because it allows them to leverage a broader ecosystem without having to own all the pieces. For instance, a mid-market pharmaceutical company might in-license a promising drug compound from a university startup (external idea coming in) rather than discover it themselves, and then use their own development and marketing capabilities to bring it to market. Conversely, a firm might out-license or sell ideas that it developed but cannot pursue, thus monetizing innovation that would otherwise sit on the shelf.

The forms of collaboration for innovation are diverse, ranging from informal networking to formal strategic alliances. Schilling (2022) identifies several modes of collaborative arrangement that firms use, including: strategic alliances (two or more firms cooperating in a project without a new legal entity, often to share complementary assets or enter new markets), joint ventures (creating a new entity jointly owned by partners for a specific innovation activity), licensing agreements (one firm obtains the rights to another’s technology or product to develop or sell, as a quick way to acquire innovation), research consortia (multiple organizations, sometimes with government or academic participation, pooling resources for pre-competitive research), supplier partnerships (co-developing innovations with key suppliers or customers), and participation in innovation networks or platforms (for example, contributing to open-source projects or industry-wide technology platforms).

Collaboration offers many advantages for innovation. It can enable firms to achieve innovation faster and at lower cost or risk by sharing the burden. For example, a mid-sized engineering company might partner with a specialist materials firm to develop a new product — the partnership means each side focuses on what they do best and they split the costs. Collaboration also provides access to capabilities a firm lacks: through partnering, a company can quickly obtain knowledge, talent, or physical assets (like labs, test equipment) that would be expensive and time-consuming to build internally. Additionally, working with external partners can spur creativity; different perspectives can lead to new insights and cross-pollination of ideas that wouldn’t emerge in isolation. Joint problem-solving often yields innovative solutions neither party would have developed alone. In sectors where technology is complex and converging (such as electronics and software, or healthcare and IT), collaboration is almost necessary because no single firm has all expertise.

Another important collaborative model is engaging with customers and users — often termed co-creation or user innovation. By collaborating closely with lead users or key clients, companies can tailor innovations that better meet market needs and even let those users contribute to development (as seen in enterprise software where clients might pilot and suggest features, or consumer goods companies running crowdsourced design contests). For mid-market firms, deep customer collaboration can be a differentiator against larger firms that are less agile in customising solutions.

Open innovation networks can also involve intermediaries — platforms or organizations that connect those who have problems with those who have solutions. Examples include crowdsourcing platforms (InnoCentive, for instance, where companies post R&D challenges and individuals around the world submit solutions for a prize), or startup accelerators where corporations mentor and then license/acquire startups. Mid-sized firms might not run their own accelerators, but they can participate in industry hackathons or incubators to spot and engage with innovative startups. Another avenue is collaborating with academic institutions — partnering with a university lab on research can yield cutting-edge innovations, and many governments encourage this with grants matching industry funds.

Of course, collaboration is not without challenges — it requires sharing control and rewards, which can be difficult. Risks include intellectual property (IP) leakage (partners might appropriate knowledge for their own benefit), dependency on partners, and potential conflicts or culture clashes between organisations. Companies have to manage these issues through clear agreements (on IP ownership, confidentiality, etc.), careful partner selection (aligning incentives and ensuring a good strategic fit), and ongoing relationship management. Despite these challenges, the trend toward open innovation has grown because the benefits often outweigh the risks if managed well.

A pertinent example of collaboration in a mid-market context is the case of the National Center for the Middle Market (NCMM) observations on digital transformation: mid-sized firms that lacked internal digital skills collaborated with external technology providers or consultants to implement new digital systems, thereby overcoming internal resource gaps. Another example is how many mid-sized manufacturers form consortia or join regional innovation clusters to collaborate on pre-competitive research (for example, a cluster of aerospace supply chain companies working together on new lightweight materials research, possibly with government and university support). By sharing the costs and findings, all members of the consortium benefit, and they can then individually commercialize the results in their own products.

Open innovation in the digital era often takes the form of platform ecosystems. If a mid-sized firm can position itself as a platform leader (even in a niche), it can invite others (developers, complementary product firms) to build on its platform, thereby accelerating innovation. Conversely, a mid-sized firm might choose to build on someone else’s platform (for example, developing an app for a larger company’s app store) as a collaborative approach to reach new customers. These ecosystem strategies are essentially collaborative — they require thinking beyond firm boundaries and leveraging a network of contributors.

In summary, collaboration and open innovation broaden the scope of what a mid-sized firm can achieve. Instead of being limited by its own headcount and budget, the firm can access a multitude of external ideas and capabilities. For mid-market companies that often find themselves “between” large corporations and startups (with more heft than startups but fewer resources than large firms), open innovation is a way to punch above their weight. They can be agile and attractive partners for both ends: larger firms might partner with mid-sized specialists for niche innovations, and startups might partner with mid-sized firms to gain industry-specific know-how or access to markets. By serving as a bridge or integrator, mid-market companies can carve out an important role in innovation ecosystems.

To leverage collaboration, mid-sized firms should create strategies for partnering: identify what core competencies they have and what they need from outside, then actively seek partnerships or network memberships to fill those gaps. They should also be open internally — encouraging their teams to scout external ideas (attending conferences, monitoring startups, engaging in professional networks). Managing open innovation might even involve new roles like an alliance manager or ecosystem manager, but even without formal roles, it requires a mindset that innovation can come from anywhere, not just inside our own four walls.

Real-World Examples of Digital Innovation in Mid-Market Firms

Integrating real-world cases helps illustrate how mid-market firms undertake digital innovation and transformation in practice. Below are a few examples and scenarios, with references, that demonstrate the principles discussed in this chapter:

• Edmunds.com — Transforming a Traditional Business through Digital Innovation: Edmunds is a company known originally for publishing printed automobile pricing guides (the “Blue Book” values for car prices). It began as a fairly traditional mid-sized publishing firm. However, Edmunds successfully navigated a digital transformation by reinventing its business model as an online platform. According to a report by the National Center for the Middle Market, “Edmunds.com, for example, began as a publisher of Blue Book guides to used car prices and transformed itself into a digital market-maker that connects shoppers to auto dealers.” This shift was a major digital innovation — the company leveraged emerging web technologies to create a platform offering car listings, reviews, and pricing tools in real-time. The innovation was not just the technology but the business model: moving from selling guidebooks to generating revenue through online advertising and lead generation for dealerships. Edmunds’ case highlights how a mid-market firm in a traditional sector can adapt to the digital age by rethinking its value proposition and using digital tools to scale it. The transformation allowed Edmunds to compete nationally (even globally) with a service that today is indispensable to car buyers, illustrating the theme that digital innovation can unlock new levels of competitiveness for mid-sized companies.
• Harbor Path — Scaling Nonprofit Services with Digital Systems: Harbor Path is a U.S. nonprofit (mid-market in size) that helps uninsured patients access free prescription medicines. As it grew, its existing manual processes and legacy system struggled to keep up with demand. The organisation undertook a digital transformation by implementing a new cloud-based system to manage patient applications and drug distribution. A case study indicates that after the transformation (supported by a tech partner), Harbor Path could scale its operations significantly, handling more patients with faster turnaround times. This example demonstrates digital process innovation in a mid-sized context: by automating and modernizing their core process through a new software platform (essentially a custom CRM/ERP for their operations), Harbor Path achieved greater efficiency and impact. It also underscores collaboration — Harbor Path worked with an external technology consultant (BrainSell) to design and implement the solution, showing open innovation in action (bringing in external expertise). While a nonprofit, the scenario is analogous to a mid-market business going digital to improve service delivery and capacity. The result was not only internal efficiency but also better user (patient) experience, which is crucial for any organisation’s success.
• A Mid-Sized Manufacturer’s Industry 4.0 Upgrade: Consider a hypothetical but representative example of a mid-sized manufacturing firm, say a company making industrial parts with a few hundred employees. Such a company might embark on a digital innovation journey by introducing IoT (Internet of Things) sensors and data analytics to its production lines. By outfitting machines with sensors, the firm can collect data on equipment health and product quality in real time. Suppose they implement a software platform (perhaps in partnership with an IoT solutions provider) that analyzes this data for predictive maintenance — anticipating machine failures before they happen — and for process optimisation — identifying inefficiencies or quality variation sources. This digital process innovation could dramatically reduce downtime and defects. If we look at reported trends, many mid-market manufacturers are pursuing exactly this: leveraging Industry 4.0 technologies to remain competitive with larger rivals. A mid-sized food processing company, for example, used IoT and advanced planning software to improve its supply chain performance, achieving better on-time delivery and inventory management. Real-world trend reports find that mid-market manufacturers see digital transformation as key to competing with both giant firms (which have scale) and smaller firms (which may be more niche/agile). By focusing on an IoT/analytics innovation, our example manufacturer improved efficiency (cost competitiveness) and responsiveness (ability to customize or adjust production quickly), thereby strengthening its market position.
• Digital Platform for a Mid-Market Service Company: Another illustration is a mid-sized service enterprise, such as a regional healthcare provider or an educational services firm, developing a new digital platform. For instance, a mid-sized hospital network might innovate by creating a telehealth platform that allows doctors consultations via video and AI-driven triage for patients. During the pandemic, many such healthcare providers (often mid-sized systems, not the biggest hospitals) rolled out telemedicine apps within months — a feat of rapid digital innovation spurred by necessity. One case is a regional clinic network that partnered with a health-tech startup to implement a telehealth system, enabling them to continue seeing patients virtually and even expand their reach beyond their immediate geography. This is an example of open innovation (partnering with a startup) and shows how mid-market firms can leapfrog via digital tech; suddenly a regional firm was competing (in patient convenience) with larger networks. The societal benefit is also clear — more accessible healthcare — tying back to innovation’s role in societal change.
• Failure to Innovate — A Cautionary Tale: It’s also instructive to note examples where lack of innovation hurt mid-market firms. One such case is Blockbuster Video — though larger than a typical mid-market firm at its peak, by the late 2000s it was essentially a struggling mid-sized company. Blockbuster failed to innovate its business model in time (specifically, it lagged in digital innovation like streaming), and was outcompeted by Netflix’s innovative online and streaming model. While Blockbuster’s downfall is often cited in general innovation discussions, for mid-market context the lesson is that even firms with an established brand can quickly become irrelevant if they ignore digital trends. Many local or regional retailers, for example, suffered a similar fate if they did not build an e-commerce presence when customer behavior shifted online. On the flip side, those who did innovate — for instance, a mid-sized retail chain that invested early in a good online store and omni-channel experience — managed to survive and sometimes even thrive by capturing new markets. These contrasting outcomes reinforce why the introduction highlighted innovation as key to both competitiveness and survival.
• Statistical Insight — Growth Through Digital Vision: To complement the narratives, consider data from the National Center for the Middle Market’s research. One finding was that middle market companies with a clear and comprehensive digital vision grew on average 75% faster than their less digitally sophisticated peers. However, only a minority (9%) of mid-market executives said digital transformation was at the core of their strategy, even though over half acknowledged its high importance. This suggests that many mid-sized firms are still grappling with how to execute digital innovation. The high growth of the digitally savvy group is a real-world validation that digital innovation pays off. It also indicates a gap — an opportunity for mid-market firms to step up innovation and for frameworks (like the one this thesis aims to develop) to guide them.

These examples show that mid-market firms are indeed capable of significant innovation — from reimagining business models, to deploying cutting-edge technologies, to swiftly responding to crises with new services. Key success factors observable in these cases include openness to new ideas (Edmunds transforming from print to digital), leveraging partnerships (Harbor Path working with a tech firm, the hypothetical manufacturer using IoT vendor solutions), a focus on customer experience (telehealth platform meeting patient needs), and leadership willingness to invest in change. They also illustrate that digital innovation is a broad concept: it can be about creating platforms, using data intelligently, automating processes, or connecting stakeholders in new ways.

The technology is easy however, its the culture and leadership that is the key to success.

Jamie is founder at Bloch.ai, Visiting Fellow in Enterprise AI at Manchester Metropolitan University and teaches AI programming and Innovation on the MSc AI Apprenticeship programmes at Northumbria University. He prefers cheese toasties.

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