Business Innovation and Strategic Management Concepts

Posted on Sep 20, 2025 in Business Administration and Management (BAM)

Value Analysis

Value Analysis can be defined as a process applied to existing product designs to compare the function of the product required by a customer to meet their requirements at the lowest cost, consistent with the specified performance and reliability needed. To better understand this technique, it is important to clarify the difference between two elements:

  • Use Value: Concerns the use of the product.
  • Esteem Value: The source of value comes from ownership.

In a general sense, the Esteem Value of a product can be understood as the difference between its price and its use value. Value Analysis projects are typically developed in groups through brainstorming, involving three phases:

  • Phase 1: Make the same product at a lower price (e.g., change of suppliers, outsourcing).
  • Phase 2: Given a function, can it be achieved in a cheaper way? (e.g., buy a component of a different material).
  • Phase 3: Given primary and secondary functions, it can be useful to reduce the cost of the main functions. This phase is similar to the previous phase but is more focused.

Dual-Ladder Career Paths

Dual-ladder career paths offer two different options (paths) for a worker, often involving roles known as gatekeepers. Gatekeepers are located at focal points of communication flows and are exposed to communication flows coming from beyond the firm’s boundaries. They continuously seek contacts (both external and internal) and translate external knowledge. However, some problems can occur due to this dual responsibility. The role of gatekeepers can easily disappear because of failed recognition, excessive recognition, conflicts with project and line managers, or promotion to management positions. The advantages of dual-ladder career paths stem from two key facts: they provide companies with an alternative career path to offer employees, and they can potentially reduce turnover among senior staff.

Disruptive and Radical Innovations

Innovation is radical when there is a high level of differentiation and a significant technological shift. It alters existing knowledge regarding both product architecture and components. On the other hand, innovation is disruptive when the shift is extremely high, leading to the creation of a new market with different needs. Therefore, radical innovations are not necessarily disruptive, but they can be if they generate a new market that disrupts an existing one.

Abernathy-Utterback Model

The Abernathy-Utterback model explores the relationship between product and process innovation, and this interaction defines three phases of the product life cycle: fluid phase, transitional phase, and specific phase. There is a predominance of product innovation at the beginning, and the predominance of process innovation from a certain point. When the process innovation rate becomes higher than the product innovation rate, the change between fluid and transitional phases is observed. This is the point where the “dominant design” emerges.

Fluid Phase

  • The main strategic challenge is to enter with the right technology to establish a dominant design.
  • Companies are structured informally.
  • The production process is flexible and often inefficient.
  • The competitive focus is related to functional performance.
  • Innovation is stimulated by opportunities in the market and technology.
  • There are many small firms, and radical product innovations are more likely to happen.

Transitional Phase

  • The main strategic challenges are managing growth and surviving possible shakeouts.
  • Companies are structured more formally.
  • The production process is more efficient.
  • The competitive focus is related to product variation.
  • Innovation is stimulated by opportunities in internal technological capability.
  • There is high competition, but it declines when a dominant design emerges.
  • Radical innovation happens mainly on process.

Specific Phase

  • The main strategic challenges are surviving in a commoditized environment and anticipating the next S-curve.
  • Characterized by a classic oligopoly, with few big players in the market.
  • There is a very efficient production process, capital intensive and rigid.
  • The product is characterized by heavy standardization in design.
  • Innovation is mainly incremental.

The model by Abernathy and Utterback also applies to non-assembled goods and services. However, for these, the model has specific considerations:

  1. It is more difficult to observe innovation because innovation is based on organization and technology.
  2. Dominant designs emerge in the process (not in the product).
  3. There is an inversion in the temporal relationship between rates of innovation for the product and the process.

Stage-Gate Process

The Stage-Gate process breaks the innovation process into a predetermined set of stages. The entrance to each stage is a decision gate (milestones), a checkpoint for a go or kill decision. It is necessary for project portfolio management. The typical steps include:

  1. Idea
  2. Concept Analysis
  3. Feasibility Analysis
  4. Development
  5. Post Release (Review)

The S-Curve Model of Innovation

The S-Curve is a useful way to represent innovation processes. At the beginning, innovation is driven by technology evolution (Technology Push), characterized by R&D investments. Later, innovation becomes driven by market needs, where both customer and market requirements are very important. Initially, performance growth is slow due to two factors:

  1. Technology: Implementation of radical innovation is very difficult because firms may lack the necessary competencies.
  2. Market: The players in the market do not fully understand the performance potential.

Moreover, there are two limitations when formulating an innovation strategy based on this concept:

  1. To consider performance just in relation to time can be very dangerous because this relation may not exist. It is not obvious that performance improves simply because time is passing (improvement is often related to investment).
  2. S-curves do not work well for disruptive technologies.

The S-curve typically plots Performance against R&D Investment, Industry Revenues, or Time (though time can be a misleading indicator).

Acquisitions for Competency Enhancement

Advantages include:

  • Results obtained are relatively quick.
  • Allows a high level of competency appropriability.
  • Provides a high degree of strategic autonomy.

Disadvantages include:

  • Competency appropriability can fail because of the inertia of both firms and if resource retention strategies are not defined.
  • Transition costs are quite high.
  • Integration of organizational routines of both firms can be difficult.

Key risks are:

  • “Integration paradox”: The integration of knowledge can disrupt the acquired firm and reduce its autonomy. The obvious consequence is the weakening of innovative capacity.
  • Winner’s curse: The buyer generally pays a higher value compared to the real value of the acquired firm.

Kotler’s Market Share Theorem

Demand forecast is usually based on Kotler’s Market Share Theorem. According to this theorem, a firm’s market share is proportional to the “marketing efforts” of its products. In a more applied sense, this theorem shows that the market share (si) of a firm depends on the “attractiveness” (Ai) of all competing goods. In mathematical notation: si = Ai / Σ Aj.

This theorem is a direct outcome from the following axioms:

  • Axiom 1: Ai ≥ 0, Σ Ai > 0
  • Axiom 2: If Ai = 0, then si = 0
  • Axiom 3: If Ai = Aj, then si = sj
  • Axiom 4: If Ai = Ai + Δ, then sj decreases as a function of Δ, but independently of i.

Product Cannibalization

If a line of products is vertically differentiated (the products aim to fulfill the same customer needs but are differentiated by quality), cannibalization occurs when a lower-quality segment presents higher attractiveness than its adjacent higher-quality segment. If the utility curves of two segments cross, cannibalization does not occur because the sensitivity to quality is different for the two segments. Conversely, if they do not cross, cannibalization may occur. (Note: This concept is often illustrated with Price x Quality graphics where utility curves for segments A and B do not cross, indicating cannibalization.)

The primary effect is competition between the different product segments. The consequence is that the market share of the higher-quality product is shifted towards its lower-quality adjacent product. To avoid cannibalization, the following actions can be adopted:

  1. Reduce the price of the high-quality product (potentially impacting profit).
  2. Make the sensitivity curve for segment A steeper (e.g., through marketing).
  3. Degrade the low-quality product.
  4. Differentiate A and B horizontally (e.g., give product B features that B’s target customers like and A’s target customers dislike).

Standards

A standard is a set of specifications that provide value to a product because of its conformity to a certain model. This concept can arise by agreement, de jure (by law), or de facto (by practice). Standards can provide economic value through:

  • Supporting the rapid growth of an installed base to achieve critical mass.
  • Penetration pricing.
  • Licensing.
  • Accelerating entry into the market.
  • Raising expectations in the market.
  • Declaring irreversible commitments.
  • Supporting the availability of complementary goods.
  • Exploiting the lock-in phenomenon.
  • Supporting “competitive migrations.”

When a company aims to make its proprietary solution a de facto standard, it must adopt the following strategies:

  • Be the first to achieve a critical mass of users.
  • Create a high expectation that the proprietary standard will win.
  • Make an irreversible commitment to a specific technology.
  • Adopt actions that lead customers to a lock-in effect.

Standards can provide value to compliant products by:

  • Promoting network externalities (e.g., fax, e-mail).
  • Enabling complementary features with other goods (e.g., hardware/software applications).
  • Conferring specific learning benefits (e.g., interfaces).
  • Achieving economies of scale (e.g., screws, threads).
  • Facilitating modularity (e.g., BUS architectures in PCs).

Eliciting Tertiary Needs

Common techniques used to elicit tertiary needs include:

  • Focus Groups: A group of people (8-12) and a facilitator discuss in a neutral environment. The analyst must be able to codify tertiary needs by participating in the focus group and analyzing recordings.
  • Direct Observation: Similar to focus groups, but based on people using the product in an operational setting.
  • Scenario of Use: Similar to direct observation, but participants (5-20) act according to a script. Participants can work in groups, with the audience commenting on the scenes being represented.
  • User Trials: Customers (8-25) use products or prototypes by performing a sequence of planned activities. Participants are interviewed after the session (no direct observation).
  • Product-in-Use: Direct observation of the product being used in real settings by unsuspecting people.
  • Customer Diaries: Participants use products at home and record their comments. Low cost, but information gathered can be “shallow.”
  • Consumer Idealized Design: Customers are split into subgroups, design their “ideal product,” and present it to others.
  • Product Personality Profiling: Within a focus group, customers imagine the product as a person and describe its personality, lifestyle, etc.
  • Web of Associations: Concepts, brands, and products are shown to participants, who associate them with keywords. A powerful method for associating brands with “values.”

Henderson and Clark’s Innovation Matrix

Henderson and Clark argue that the traditional categorization of innovation as incremental or radical is incomplete and potentially misleading, as incumbents often tend to downplay their significance. Therefore, they proposed that innovation classification should consider two dimensions of product effects: relationships between components and reference technologies. This leads to four categories of innovation:

  • Reference Technologies (Not Changed) & Component Relationships (Not Changed): Incremental Innovation
  • Reference Technologies (Changed) & Component Relationships (Not Changed): Modular Innovation
  • Reference Technologies (Not Changed) & Component Relationships (Changed): Architectural Innovation
  • Reference Technologies (Changed) & Component Relationships (Changed): Radical Innovation

According to the authors, product architecture and organizational structure are coupled, and it is generally harder to change architecture than technology. Architectural innovation significantly affects the overall configuration.

Organizational Forms in Product Development

Functional Organization

  • Work is performed within functions.
  • Coordination is controlled by line managers and is simple (unique authority).
  • Internal efficiency is satisfactory.
  • Has some problems with information transfer.
  • Competencies are highly specialized.

Lightweight Teams and Project Managers

  • Has some similarities to functional organization.
  • Work is performed within functions and under line managers.
  • Project managers and liaison officers perform coordination.
  • Internal efficiency is satisfactory.
  • Presents some problems in coordination because of dual authority structure and lightweight project managers (often juniors).

Heavyweight Teams and Project Managers

  • Similar to lightweight organizations, work is performed within functions, but under the authority of project managers.
  • Line managers are responsible for the technical proficiency of resources assigned to the project.
  • Project managers are responsible for coordination.
  • Integrative competencies become more crucial.
  • Presents lower internal efficiency and coordination problems due to dual authority.

Autonomous Teams

  • Work is performed outside functions and under the authority of the project manager.
  • Coordination is performed by the project manager.
  • Integrative competencies grow, and specialist ones decrease.
  • Procedures are ad-hoc and “project based.”
  • Also presents lower internal efficiency and coordination problems due to dual authority.

Timing of Market Entry

First Movers

First movers offer a new category of product or service. They innovate, incur high research costs, and possess high technical competencies. They choose technological trajectories and create the project concept.

Early Followers

Early followers enter the market in the initial phases, but not as the first. They innovate, but mainly look for incremental improvements along the trajectories already chosen by the first mover, and contain R&D costs (e.g., reverse engineering).

Late Entrants

Late entrants enter when a product has already achieved significant diffusion. They focus on process innovation that allows for price strategies or on incremental innovation aimed at widening demand (e.g., ease of use).

Modular vs. Integral Architecture

The basic difference between the two architectures is that integral architecture components are functionally interdependent, while in modular architecture, components are functionally independent. Regarding product performance, integral architecture favors global performance (cost, mass, reliability) because performance apportionment is a critical point, and functions can be shared. On the other hand, local performance is favored by modular architecture because product changes are easier, and it “opens the door” to third-party suppliers. Both architectures enable product variety, but this is simpler and more common with modular architecture. Integral architecture can enable variety in the case of very simple products or flexible manufacturing systems. Moreover, the choice between the two architectures leads to a trade-off between innovation and imitation. At the same time, modular architecture stimulates innovation because it is easier to improve the performance of components and makes imitation easier because components can be replicated by competitors without significant effort.

The choice between modular and integral architecture can be guided by considering the following implications:

  • What sort of performance is important?
  • What level of flexibility should be given to the product?
  • What support is needed across different versions?
  • How can product variety be achieved?
  • What role does standardization have?
  • What kind of organization is possible or desirable?

Porter’s Five Forces Model

Porter’s model allows a company to strategically position itself within an industry by analyzing five competitive forces:

  • Threat of New Entrants
  • Threat of Substitute Products or Services
  • Bargaining Power of Suppliers
  • Bargaining Power of Buyers
  • Rivalry Among Existing Firms

The firm is represented as part of a value chain and a competitive context, requiring consideration of the entire supply chain and market. Analyzing the Five Forces model, competitive advantage can be achieved in two primary forms:

  1. Decreasing Production Cost: Competitive advantage is expressed through economies of scale (in Net Present Value and production), learning economies, and radical innovations in production and process.
  2. Product Differentiation: A company can opt for vertical or horizontal differentiation, design before sales (e.g., make-to-order, make-to-stock), design contextual to sales, or long-term contracts.

Outsourcing R&D Activities

In many cases, technology required for industrial purposes is available in the market for a certain price. Instead of performing R&D activities internally, a company can choose to outsource partly or completely these activities. R&D is an important and strategic point of a company. Outsourcing occurs because the firm does not have sufficient resources to perform this activity by itself. Outsourcing can occur in design and production, and it is equivalent to “giving up” the idea of developing competencies. Through outsourcing, a firm can obtain off-the-shelf components that are often less than “leading edge” and do not differentiate the firm against competitors.

Advantages include:

  • Resources become available for other activities that can be more important to the firm.
  • Protection of intellectual property through specific constraints on contracts.
  • Achievement of R&D activities outside the firm without initial investments.

Disadvantages include:

  • Outsourcing activities can be expensive.
  • Incurrence of transition costs.
  • Risk of losing learning and analytical capabilities.
  • Suppliers may have little incentive to pursue innovation further.

Bass Diffusion Model

The Bass diffusion model is a mathematical approach that models how a new product is adopted by a market. This model starts from the following hypotheses:

  • Monopoly or market-level demand.
  • Innovative (no substitutes or complements) and durable good (no replacement sales).
  • Constant marketing actions.
  • Binary adoption process (consumers and firms).

Mathematically, the adoption rate n(t) is given by:
n(t) = dN(t)/dt = p[M-N(t)] + q[N(t)/M] [M-N(t)]

By solving the above equation, the adoption rate n(t) and cumulative adoptions N(t) are:
n(t) = (Mp(p+q)²e[-(p+q)t]) / (p+qe[-(p+q)t])
N(t) = M*(1 – e[-(p+q)t]) / (1+ (q/p)* e[-(p+q)t])

It is important to note two key results from these equations:

  • If q=0, diffusion is primarily innovative.
  • If p=0, diffusion is primarily imitative.
Key Bass Model Formulas
  • Sales Peak (n(t*)): n(t*) = [M * (p + q)2] / (4*q)
  • Penetration Level (N(t*)): N(t*) = M * [1/2 – p/(2q)] ≈ M/2

Reasons Not to Patent an Innovation

The main reasons for not patenting an innovation can be related to:

  • Fragmented Market: Where an idea can be difficult to demonstrate, and it is easy to fall into infringement.
  • Varying Patent Laws: Primarily related to geographic coverage.
  • Time and Cost: Significant time and cost are required to file and enforce patents.

Therefore, an industrial secret can be used to protect intellectual property. This choice is often related to a lack of investment to cover patent costs. The most important advantage is the unlimited duration of this protection. However, industrial secrets have drawbacks, such as a lack of legal protection and risks and costs associated with security management.

Project Portfolio Management (PPM)

Project Portfolio Management (PPM) plays an important role in corporate strategy. Not formalizing PPM leads to a lack of strategically aligned criteria for project selection. As an obvious consequence, the project portfolio does not have a clear direction, and synergies between projects are not exploited. Therefore, projects are not aligned with the overall strategy, and R&D resources are not profitably utilized. Furthermore, to better align projects with strategy, a top-down approach should be adopted (instead of bottom-up) because decisions are based on budget allocation and made by managers. PPM is also related to the resource-based approach. Failure in project portfolio selection leads to two issues:

  • Resources are thinly spread among projects.
  • Mediocre projects are selected.

The consequences are a lack of resources and insufficient resources allocated to promising projects. To select projects in project portfolio management, there are mainly four categories of methods:

Financial Methods

These methods use financial tools for economic evaluation of a project, such as Net Present Value, Internal Rate of Return, Payback time, productivity indicators, etc. They can be divided into deterministic and stochastic approaches. In the latter case, statistical tools such as the Monte Carlo method or decision trees can be used.

Key Financial Formulas
  • Expected Commercial Value (ECV): ECV = (NPVPc – CP)Pt – DC
  • Productivity Index (PI): PI = ECV/DC

Multicriteria Methods

These frequently take into account many other aspects beyond economic evaluation, such as technical and market risks, strategic alignment, cohesion with competencies, complexity, and ease of implementation.

Visual Methods

These establish graphic visualization of project measurement variables, such as bubble diagrams or graphs, regarding risks, economic indicators, etc. Even though they may not be sufficient for project selection support, they are valuable because they provide a complete picture of alternatives.

Optimization Methods

This type of method uses mixed-integer mathematical programming (selection of a project is modeled with Boolean decision variables) and can be computationally demanding. It is very unlikely that a company uses only one method to evaluate alternatives in a project portfolio, since they often provide different information, all of them have different value. They are complementary.

Learning Curve and Boeing-Crawford Model

The “Learning curve” is a theory based on the idea that the time required by a worker to perform a task decreases as the worker’s experience increases. As the time required by a task decreases, its costs decrease as well. In many situations, productivity increases as a function of the cumulative volume of output of a product. Certain costs tend to decrease, per unit, in a predictable pattern as employees become more familiar with their work. This decreasing production cost is a function of the learning process, which may result in:

  • A reduction of unit variable cost.
  • A better and more skilled use of equipment.
  • Lower fixed overhead costs allocated per unit of product.

Boeing-Crawford proposed a mathematical model in which this phenomenon is expressed. The model starts from the idea that a cost C(n) to produce n products can be expressed by the relation between C(1) and b. Mathematically: C(n) = C(1) * n-b. C(1) is not the “real” cost of the first unit; it should be estimated from data and not by taking the recorded cost. b is the learning parameter. The average cost and average cost between two points are given by:
Cavg = C(n)/(1-b)
Cavg(n1,n2) = [C(1)/(n2-n1)] * [(n2(1-b) – n1(1-b))/(1-b)]

Moore’s Chasm Theory

Moore’s Theory argues there is a “chasm” between the early adopters of a product (the technology enthusiasts and visionaries) and the early majority (the pragmatists). The author believes visionaries and pragmatists have very different expectations, and he attempts to explore these differences and suggest techniques to successfully cross the “chasm,” including:

  • Choosing a target market.
  • Understanding the whole product concept.
  • Positioning the product.
  • Building a marketing strategy.
  • Choosing the most appropriate distribution channel and pricing.

The theory is closely related to the technology adoption lifecycle, where five main segments are recognized:

  • Innovators
  • Early Adopters
  • Early Majority
  • Late Majority
  • Laggards

According to Moore, the marketer should focus on one customer group at a time, using each group as a base for marketing to the next. The most difficult step is making the transition between visionaries (early adopters) and pragmatists (early majority).

Dominant Design and Standards

A standard is a set of specifications that provide value to a product because of its conformity to a certain model. This concept can arise by agreement, de jure (by law), or de facto (by practice). A dominant design is one that wins the allegiance of the marketplace, the one that competitors and innovators must adhere to if they hope to command significant market share. Dominant designs may not be inherently better than other designs, but they emerge because of the lock-in effect caused by a widely adopted design. Three factors are deeply related to the emergence of a dominant design:

  • Superior technology.
  • Relationships with complementary assets.
  • Reputation of the firms.

Standards can be dominant designs or not. Standards are agreements, while dominant designs often emerge from network externalities. Modularity affects the emergence and makes the dominant design less important. This occurs because specialization and economies of scale are found at the module level. Moreover, the role of organizational learning is reduced by functional independence, and network externalities are reduced by “plug-and-play” modules.

Standards War

A “standards war” is a battle for market dominance between incompatible and rival technologies. That is, firms compete to impose their standards and dominate the market. A famous example of such a war was fought by Adobe Systems, which invested heavily in developing a ‘page description language’ (PDF). Competition between different standards can lead to the “standards’ war dilemma.” In this context, a firm must decide between agreeing to the domination of another firm or fighting. Analogously, a firm must choose between two situations:

  • Ensuring there is one large market (“big cake”) and then competing for a slice of it.
  • Securing 100% of a market (“cake”), which might end up being small.

To avoid a standards war and competition between standards, a firm can negotiate with its rivals and reach an agreement. If a war occurs, a standard leader emerges, and follower firms must adapt. Strategies a firm can adopt in a standards war include:

  • Penetration pricing.
  • Alliances with complementary firms.
  • Expectations management.
  • Commitment to low prices.

Allen’s Studies on Technology Flow

The theory proposed by Allen aims to understand the management of technology flow within a firm. It is conducted in two phases:

  1. Twin Projects: To study the application of different problem-solving strategies on similar problems.
  2. Communication Network Analysis: To study interactions between people involved in product design and development.

In the second phase, it is important to emphasize the importance of creating information links, both internally and externally. For external links, the role of gatekeepers (persons responsible for translating external knowledge) is fundamental. The emergence of the internet changed the second phase by altering how information is acquired. With the internet age, more sophisticated information channels emerged, and the firm and its gatekeepers must adapt to these changes and new requirements.

Functional Analysis

Functional analysis examines the relationship between product functions, their perceived value to the customer, and their cost of provision. It aims to evaluate benefits and coexistence with other functional models. Understanding product functions is a key aspect of the work undertaken by engineers involved in complex system design. Functional analysis can be represented by a Function Tree, Data Flow Diagram, and Function Structure.

Economies of Learning

Learning economies refer to reductions in unit costs due to the accumulation of experience and know-how over time. This concept is closely related to the Learning Curve, which describes how average costs decline as cumulative production output doubles. The Boeing-Crawford Model provides a mathematical framework for this phenomenon.

Evolutionary (Resource-Based) View of the Firm

The theory argues that firms possess two types of resources: a subset of which enables them to achieve competitive advantage, and a subset of those that lead to superior long-term (sustainable) performance. Resources that are valuable and rare can lead to the creation of competitive advantage. It is important to distinguish between two views of a firm:

  • Static View: The firm is seen as an organized association of complementary resources. The economic value produced by grouping these resources is greater than the sum of the values that would be created individually.
  • Dynamic View: The firm is seen as a bundle of organizational routines that involves a common language.

Organizational Learning (Huber, 1991)

An organization learns through its processes. In a firm, people’s knowledge progresses, and consequently, processes also evolve. This leads to the evolution of the entire firm, creating competitive advantage. Huber’s theory describes four types of learning:

  • Innate Learning: The first knowledge base in the firm, a contribution of individual founding members, tied together by a common “vision of the world” or objective.
  • Experiential Learning: Means “learning by doing,” and its consequence is the modification of company routines.
  • Vicarious Learning: The acquisition of knowledge outside the firm, a two-step process involving the reception of external knowledge and its internal diffusion. It depends on the existence of “gatekeepers” and effective internal communication channels.
  • Learning by Grafting: Knowledge is obtained by hiring people or buying other companies. It is a fast method, but integration can be difficult.

Forms of Knowledge

  • Factual (Know-What): Contains data relating to facts and events; it is explicit, codified, and embeddable in capital.
  • Causal (Know-Why): Expresses the cause of phenomena through scientific methods or empirical approaches; depending on the process that generated it, may be tacit and codified, or explicit and not codified.
  • Procedural (Know-How): The form that allows one to perform tasks.
  • Positional (Know-Who): Relates to the position and place of incorporation of other knowledge; it allows one to locate within an organization or broader context who possesses certain knowledge.

Open Innovation vs. Open Source

Open Innovation is the use of external and internal flows of knowledge to accelerate innovation. With knowledge now widely distributed, companies cannot rely entirely on their own research but should acquire inventions or intellectual property from other companies when it advances their business. It means innovating with partners by sharing risks and recompense.

Open Source is a development model that promotes universal access via a free license to a product’s design or blueprint, including subsequent improvements by anyone. It means “open collaboration.” Open source gained importance with the rise of the Internet and open-source code in computing. The collaboration between programmers made it possible to improve software and operating systems without dependence on large corporations.

The difference between Open Innovation and Open Source consists in their decision orientation. While Open Innovation often seeks solutions through a top-down approach, Open Source involves many solvers helping one another through a bottom-up approach.

Dimensions of Knowledge

  • Built-in Human/Capital: It is stored and used by humans or embodied in physical media (e.g., books, manuals, files, databases).
  • Coded/Uncoded: Coding allows one to clarify, store, and transmit it. Uncodable knowledge can only be transmitted through imitation or observation of the acts of those who transmit it from the receiving end (learning by doing).
  • Tacit/Explicit:
    • Tacit: The owner is able to use it but not express it formally.
    • Explicit: The holder is able to recognize and express it.
  • Public/Private Good:
    • Public: Its enjoyment by one individual does not reduce enjoyment by others (the ability to enjoy it depends on the marginal cost of duplication and related constraints).
    • Private: Not codified and tacit knowledge, as its availability to other individuals depends on their ability to interact.

Concurrent Engineering

Concurrent Engineering involves exploring different solutions in parallel, which can increase initial development costs but reduces overall risk in terms of cost and time, as multiple alternatives are pursued from the outset. Upstream and downstream activities are overlapped in time, and information flows between them occur in small packages. Advantages include improved quality and reduced project completion time. Disadvantages include designers needing to learn to operate with early (vague and changeable) information, potential repetition of work, and the difficulty of establishing and sustaining inter-functional working groups for complex projects. It is appropriate when technical uncertainty is high, and testing is fast and low-cost. It is not recommended for serial learning experiments where the classical Western method, accepting iterations up to a satisfactory stopping point, might be more advantageous.

Acquisition and Development of Technological Skills

  • Internal R&D: Establishes a direct link between R&D investments and company performance, allowing a greater degree of appropriability.
  • Acquisition: Delivers results relatively quickly, but transaction costs are quite high and it requires the integration of organizational routines.
  • Corporate Venturing: The company behaves as a venture capital investor, taking stakes in small, innovative firms.
  • Hiring Experts: A “hybrid” between internal R&D and acquisition. Hiring experts creates challenges due to the ability to integrate individual skills. Integration difficulties grow with the number of resources acquired.
  • Strategic Alliances (Non-Equity Agreements): Based on contracts, where the relationship’s strength determines outcomes. Can create value when participating firms have complementary competencies.
  • Joint Ventures (Equity Agreements): Can create value through size and/or complementarity.
  • Co-Development: One form of co-development is Open Innovation. Traditionally, development is a funnel, completely internal to the firm.
  • Acquisition of Licenses: While seemingly giving up competency development, it is often a first step to develop them later.
  • Total Outsourcing (Design and Production): Equivalent to “giving up” the idea of developing competencies. Outsourcing requires caution because it can lead to losing the capability to specify, buy, and verify.

Value Engineering

Value Engineering (VE) is a systematic and organized approach to provide the necessary functions in a project at the lowest cost. Value engineering promotes the substitution of materials and methods with less expensive alternatives, without sacrificing functionality. It focuses solely on the functions of various components and materials, rather than their physical attributes. (Also known as Value Analysis).

VE is a creative, organized effort that analyzes the requirements of a project to achieve essential functions at the lowest total costs (capital, staffing, energy, maintenance) over the project’s life. Through group investigation, using experienced, multi-disciplinary teams, value and economy are improved by studying alternate design concepts, materials, and methods without compromising the client’s functional and value objectives.

Competitive Advantage Based on Differentiation

Differentiation can be vertical or horizontal. Importantly, considering the timing of development activities relative to sales, we identify three types of companies:

  • Design Precedes Sales: These companies must anticipate customer needs and prepare a range of products. Sales are driven by product quality, which reflects design quality. Business priorities include managing a high number of projects and reducing the duration and degree of customization to allow for acceptable assembly times.
  • Contextual Design to Sale: These companies deliver highly customized goods. Contracts are awarded based on reputation or skill in achieving a good project (customers judge not only results but also the design process, skills, and methodologies used).
  • Design Analysis Under Long-Term Agreements: Companies undertake agreements with customers covering the design and supply of goods within a given time. This approach aims to supplement their R&D with that of the client and to work collaboratively to maintain long-term agreements.

Competitive Advantage Based on Technological Skills

Essential for long-term sustainability, achieved through the following methods:

  • Patent: Guarantees legal protection, giving the company exclusive rights to use the innovation. The objective is to provide an incentive that justifies necessary investments in product and process innovation. Use rights may be exercised by the company or by selling the patent. However, there is a risk of making the technological content public.
  • Secret: A risky choice, but a tool that allows a company not to reveal the contents of an innovation and maintain a competitive edge for an unlimited period. The secret implies that innovation cannot be decoded through product observation (reverse engineering).
  • Disclosure: It gives competitors the opportunity to observe and imitate products, with the confidence that the time needed to develop the technology will enable the company to maintain a continuous competitive advantage.

Competitive Advantage Based on Cost

  • Economies of Scale in R&D Activities: Can be obtained through:
    1. Standardization
    2. Outsourcing component design
    3. R&D agreements
  • Economies of Scale in Production Activities: The use of larger plants leads to reduced variable costs and an increase in fixed costs of investment and management, so the cost per unit (CU) decreases with increased production.
  • Learning Economies: The accumulation of experience in manufacturing a good increases efficiency (lower unit cost of production). This strategy assumes that, due to the learning curve, the primary objective is to increase market share, even if it means adopting lower prices (penetration pricing) and making large investments in production capacities.
  • Radical Innovation: Operating on product or process, radical innovation can provide a business with a competitive advantage on costs. These innovations are often proposed by new entrant companies that leverage acquired skills in other areas.

Quality Function Deployment (QFD)

QFD is a tool to support design across enterprises and sectors. It was created to meet customer needs and is used in the initial phase of product planning. It can be driven by marketing or design. It is also a communication tool that requires strong partnership for successful results. Quality Function Deployment (QFD) is a “method to transform qualitative user demands into quantitative parameters, to deploy the functions forming quality, and to deploy methods for achieving the design quality into subsystems and component parts, and ultimately to specific elements of the manufacturing process.”

Design for Manufacture and Assembly (DFMA)

Methods for Design for Manufacture and Assembly include: authorizations from the value chain, past projects database, computer-aided processes, design manuals, checklists, and design scorecards. DFMA stands for Design for Manufacture and Assembly. DFMA is the combination of two methodologies: Design for Manufacture, which focuses on designing for ease of manufacturing product parts, and Design for Assembly, which focuses on designing the product for ease of assembly. The objective is to unify components that should not be in different materials and to prevent a large number of assemblies.

Lock-in Effect

Once a standard has emerged, a superior product that does not comply with it would not have much chance of success on the market. This phenomenon, called lock-in, is due to the fact that purchasing a product conforming to a standard involves an investment that is only partially recoverable if one were to change standards. These investments discourage the introduction of alternative standards unless they provide very high benefits or low switching costs. For this reason, the attempt to replace one standard with another can only succeed if, alongside technical performance, attention is paid to facilitating the transition by ensuring, for example, compatibility or integration with the previous standard. Lock-in is a problem for industrial policy, as a technical standard can hinder the development of a sector. It is also a problem for the economic efficiency of the sector, as quickly fixing a standard anticipates sector growth but simultaneously carries the risk that a superior technology may emerge but then be rejected.