MBA Technology Strategy Course Guide Template

Technology Strategy Course Guide: [Programme and elective]

A course guide for the second-year MBA elective in technology and innovation strategy: what the course is for, the competencies it builds, a 12-session roadmap, the key concepts with links to concept cards, an original mini-case on Corvane Robotics with four exhibits and a teaching note, how assignments are graded, an exam preparation plan and a self-test with an answer key. It covers technology life cycles and dominant designs, disruptive and architectural innovation, profiting from innovation (appropriability and complementary assets), network effects, standards and platforms, ecosystems, diffusion, innovation portfolios, real options and digital transformation. It builds on the core strategy course (mba/mba-strategy-guide) and on mba/mba-growth-strategy-card, and links to them instead of re-teaching them. It is for second-year students choosing or taking the elective, students heading to technology, product or strategy roles, and managers who want a structured self-study path. Source basis: the primary works of Utterback and Abernathy (1975), Tushman and Anderson (1986), Teece (1986, 2018), Henderson and Clark (1990), Christensen (1997), Katz and Shapiro (1985, 1994), Arthur (1989), Rochet and Tirole (2003), Adner (2017), Jacobides, Cennamo and Gawer (2018) and others named under further reading, all written up in original words and examples. Replace every [bracketed] value and every row marked Example.

Document control

Contents

• 1. What the course is for
• 2. Competencies it builds
• 3. Prerequisites
• 4. Session roadmap
• 5. Key concepts
• 6. The course in eight topics
• 7. Mini-case: Corvane Robotics and the open fleet platform
• 8. Typical assignments and how they are graded
• 9. Exam preparation plan
• 10. Common struggles
• 11. Self-test questions
• 12. My notes and next steps
• 13. Teaching note for the mini-case

1. What the course is for

The core strategy course asks why some firms earn persistently higher returns. The technology strategy elective asks the same question in industries where the technology itself keeps changing: how do firms create and capture value from new technology, and why do leaders so often lose when the technology shifts? Three facts make this a separate course. First, technologies follow cycles: a period of ferment ends with a dominant design, after which competition moves to process and cost, until a discontinuity starts the cycle again. Second, the value of many technologies depends on adoption by others (network effects, standards, complements), so strategy includes shaping what customers and partners expect. Third, the firm that invents is often not the firm that profits: imitators, owners of complementary assets or platform owners can capture the value.

The course is integrative. It uses microeconomics (network effects, pricing, game theory), finance (real options, portfolio valuation), marketing (diffusion and adoption) and organisational behaviour (why incumbents fail, how to organise exploration). Cases are often set in fast-changing industries where the evidence is incomplete; a clear recommendation with stated assumptions and signposts for changing course scores better than a survey of possibilities.

By the end of the course you should be able to:

1. Place a technology in its life cycle and explain what that implies for where competition will move next.
2. Diagnose whether an innovation is incremental, modular, architectural or radical, and whether it is sustaining or disruptive for a given incumbent.
3. Explain who will profit from an innovation using appropriability and complementary assets.
4. Analyse markets with network effects, standards and platforms, including pricing, launch and tipping.
5. Map an ecosystem and identify the complementors and bottlenecks a strategy depends on.
6. Design and defend an innovation portfolio, with staging and kill criteria.
7. Write a technology strategy recommendation with numbers, risks and signposts.

2. Competencies it builds

The table maps the elective to the broad competency areas that accreditation standards and leading programmes use for graduate business learning goals (analytical and quantitative reasoning, ethical decision making, communication, leadership and teamwork, global perspective, technology, data and AI). Your school's wording will differ; check the programme handbook.

3. Prerequisites

• Core strategy: five forces, VRIO, value creation and capture, network effects at the level of the core course (mba/mba-strategy-guide, mba/mba-resource-based-view-card, mba/mba-competitive-advantage-card).
• Growth strategy: three horizons, Ansoff, build, borrow or buy (mba/mba-growth-strategy-card).
• Finance: NPV, IRR, expected values, real options (mba/mba-npv-irr-card, mba/mba-options-real-options-card, mba/mba-decision-trees-card).
• Game theory: commitment, credibility and sequential games (mba/mba-game-theory-card).
• Spreadsheet skills: NPV, IRR, SUMPRODUCT, Solver with binary variables (mba/pre-mba-excel-modeling-drills).

4. Session roadmap

5. Key concepts

6. The course in eight topics

Technology life cycles and dominant designs. Utterback and Abernathy (1975) observed that in a new product category, early competition is about product performance and many designs coexist; once a dominant design emerges, the rate of product innovation falls and process innovation, scale and cost take over. Tushman and Anderson (1986) distinguished competence-enhancing discontinuities, which build on incumbents' know-how, from competence-destroying ones, which make it obsolete and favour new entrants; Anderson and Tushman (1990) described the cycle of ferment, dominant design and incremental change. Performance of a technology often follows an S-curve against cumulative effort, with diminishing returns before a new technology overtakes it (Foster 1986). Typical question: where is this technology in its cycle, and what will competition be about in three years?

Architectural and disruptive innovation. Henderson and Clark (1990) showed that innovations that change how components are linked (architectural), while leaving the components themselves largely intact, can defeat established firms, because their organisation, communication channels and problem-solving routines mirror the old architecture. Christensen (1997) explained how disruptive technologies, initially worse on the attributes mainstream customers value but cheaper, simpler or more convenient, take root in overlooked segments and improve until they meet mainstream needs; incumbents that listen closely to their best customers rationally ignore them. The two ideas answer different questions: Henderson and Clark explain why incumbents cannot see or execute the change; Christensen explains why they choose not to fund it. Typical question: is this innovation disruptive for this incumbent, or only for some?

Profiting from innovation. Teece (1986) asked why innovators often fail to profit. His answer has three parts. The appropriability regime: how well the innovation can be protected by patents, secrecy or the nature of the knowledge (tight or weak). The phase of the industry: before a dominant design, flexibility matters; after it, scale and cost do. And complementary assets: manufacturing, distribution, service, brand and complementary technologies needed to commercialise the innovation, which may be generic, specialised or co-specialised. In a weak regime, owners of specialised complementary assets often capture the value. Teece (2018) revisited the framework for the digital economy, with enabling technologies, standards and licensing. Typical question: who will capture the value of this innovation, and should the innovator integrate, contract or license?

Network effects, standards and lock-in. Katz and Shapiro (1985, 1994) showed that in network markets, consumer expectations and firms' compatibility choices shape which technology wins, and that markets can tip. Arthur (1989) modelled how increasing returns let small historical events lock a market into a technology that need not be the best. Strategies include pre-emption of the installed base, penetration pricing, commitment to a standard, alliances to build a standard coalition, and backward compatibility. Typical question: should the firm fight for its own standard, join a coalition or adopt the rival's?

Platforms and pricing. When a technology connects distinct groups, it becomes a multi-sided platform. Rochet and Tirole (2003) and Armstrong (2006) showed that the price structure across sides matters and that one side may pay less than cost; Caillaud and Jullien (2003) analysed the chicken-and-egg launch problem; Boudreau (2010) analysed openness; Eisenmann, Parker and Van Alstyne (2011) described envelopment. The full treatment, with a pricing model and a launch example, is in mba/mba-platform-strategy-card. Typical question: which side do you subsidise, and how open should the platform be?

Ecosystems. Many innovations create value only if partners move too: complementors must build, intermediaries must adopt, regulators must approve. Adner (2017) defined the ecosystem as the alignment structure of partners needed for a value proposition to materialise and stressed mapping the activities, actors, positions and links it requires. Jacobides, Cennamo and Gawer (2018) argued that ecosystems are distinguished by complementarities that are unique or supermodular and by the non-generic investments partners make. Gawer and Cusumano (2014) described industry platforms as foundations for outside innovation. Typical question: who else has to change for this innovation to work, and what if they do not?

Adoption and portfolios. Diffusion follows an S-curve shaped by innovators and imitators (Bass 1969; Rogers 1962); the gap between early adopters and the mainstream can be wide (Moore 1991). Inside the firm, innovation competes for a budget: March (1991) explained why exploitation crowds out exploration, Cooper (1990) proposed stage-gates, and portfolio methods value and select risky projects (mba/mba-innovation-portfolio-card). Staging and the option to wait or abandon are valued with real options (mba/mba-options-real-options-card). Typical question: how much should the firm invest in exploration, and how will it decide what to stop?

Organising for technological change. Incumbents need dynamic capabilities (Teece, Pisano and Shuen 1997), absorptive capacity (Cohen and Levinthal 1990) and often an ambidextrous structure (O'Reilly and Tushman 2004) to explore while exploiting. Digital transformation and AI adoption are current forms of the same problem (mba/mba-digital-transformation-card, mba/mba-ai-strategy-card). Typical question: should the new business sit inside the existing unit or outside it, and who protects it?

7. Mini-case: Corvane Robotics and the open fleet platform

7.1 Situation

In November 2026, Priya Raman, chief executive of Corvane Robotics (fictional), was preparing for a board meeting at which she would ask for a decision she had postponed for a year. Corvane sold autonomous mobile robots and fleet-orchestration software to mid-market warehouses. Revenue had grown from USD 92.0m in 2025 to a forecast USD 140.0m in 2026, and the software share was rising (Exhibit 1). A year earlier, the board had decided to keep buying the drive module rather than make it, and to run a small pilot that let third-party robots run under Corvane's orchestration software (the background is in the mini-case of mba/mba-strategy-guide).

The pilot had gone better than expected (Exhibit 2). Eight third-party robot models were certified, eleven customer sites ran mixed fleets, and the number of third-party robots managed by Corvane's software had grown each quarter. "Customers want one brain for the whole warehouse," said Tomás Ekwueme, head of sales. "Pilots used to be a price fight about robots. Now the conversation starts with the orchestration layer, and we are the only mid-market vendor that manages other people's robots well."

Rafael Santoro, the chief technology officer, proposed to open the platform fully: publish the interface, certify any robot maker that met the specification, open an application store for picking and analytics applications, and charge an annual fee per third-party robot managed. He estimated USD 9.0m of up-front investment in interface tooling, certification labs and developer support, plus USD 3.0m a year to run the programme (Exhibit 3). "The orchestration layer is becoming the control point of the warehouse. Robots are converging; the software and the data from thousands of missions are not. If we do not become the open layer, someone else will."

Daniel Achterberg, the chief financial officer, was sceptical. "The base case does not pay back within five years. Every third-party robot we manage is a robot we did not sell, and our hardware still earns most of our gross profit. At USD 1,500 a robot we are paying to help competitors sell robots into our own customers." He pointed out that Corvane's interface could be copied quickly: software patents in fleet orchestration were narrow, and two engineers had already left for a rival.

The question that worried Priya most came from outside. Competitor A, the segment leader with about a quarter of the market, was rumoured to be preparing its own open orchestration programme, bundled free with its robots. An association of logistics equipment makers was also drafting an open interface specification for robot fleets. If Competitor A's layer became the de facto standard, Corvane's software could become one option among many inside a rival's ecosystem (Exhibit 4). Mei-Ling Novak, vice president of operations, added a practical worry: certification of third-party robots needed field engineers who were already stretched by Corvane's own installations.

Priya had to recommend one of three paths: keep the platform closed (Corvane robots plus a few hand-picked partners), open it fully as proposed, or something in between. She also needed to tell the board what evidence over the next year would make her change course.

7.2 Exhibits

Exhibit 1. Corvane Robotics revenue mix, USD m (fictional).

Software revenue grows 87.2% in 2026 (=C3/B3-1), hardware 36.6% (=C2/B2-1). The 2026 forecast matches the business units in mba/mba-growth-strategy-card (Worked example A: robots 82 and conveyor retrofits 6, software 31, service 21).

Exhibit 2. Platform pilot, 2026 quarters (fictional).

Quarter-on-quarter growth in third-party robots managed: 137.5%, 89.5% and 72.2% (=C4/B4-1 and across).

Exhibit 3. Open platform proposal, incremental cash flows, USD m (fictional). Investment of USD 9.0m at the end of 2026; fee USD 1,500 per third-party robot per year; programme cost USD 3.0m a year; cannibalisation counted at USD 12,000 gross profit per Corvane robot not sold; discount rate 12%.

With the net cash flows for 2027 to 2031 in C7:G7 and -9 in B7, NPV at 12% is USD -5.869m (=NPV(12%,C7:G7)+B7) and IRR is -5.0% (=IRR(B7:G7)). If third-party adoption is only half of the base case (cannibalisation unchanged), NPV is USD -17.815m. The team puts a 40% probability on low adoption.

Exhibit 4. Risk that a rival's open orchestration tips the segment (fictional). If Competitor A's layer becomes the standard, the team estimates that Corvane loses software and hardware gross profit of USD 2.0m, 5.0m, 9.0m, 13.0m and 16.0m in 2027 to 2031 (present value USD 29.518m at 12%, =NPV(12%,C2:G2) on the losses). The strategy team's judgement of the probability of tipping:

7.3 Discussion questions

1. Where is warehouse robotics in its technology life cycle? Is the shift to a separate orchestration layer an architectural innovation, and for whom?
2. Using Teece's framework, which assets let Corvane capture value from its orchestration software if the interface is easily copied?
3. Compute the expected value of the open path and the closed path, including the tipping risk. Which assumptions drive the comparison? Find the break-even values of the two most important ones.
4. How would Competitor A respond to each path? Use the platform concepts of envelopment and multi-homing.
5. What does the ecosystem need for an open Corvane platform to work, and where are the bottlenecks?
6. What should Priya recommend, and what signposts over the next year would make her change course?

8. Typical assignments and how they are graded

Technology strategy electives commonly combine class participation, short case write-ups, a team project on a live technology decision (often with a company sponsor) and a final exam or final paper. Weights vary; typical ranges are participation 20 to 35%, written cases 20 to 30%, team project 25 to 40% and final 20 to 35%. Your syllabus is the authority.

For write-ups use mba/mba-case-write-up; for participation, track contributions with mba/mba-class-participation-log; for a sponsor project, mba/mba-field-project-sow and mba/mba-field-project-report.

9. Exam preparation plan

More detail on spacing and retrieval practice is in mba/mba-exam-prep.

10. Common struggles

1. "Disruptive" used for any big change. Disruption has a specific mechanism: entry in an overlooked segment with an offer that is worse on mainstream attributes. Many breakthroughs are sustaining for incumbents.
2. Assuming the inventor profits. Without tight appropriability or control of complementary assets, imitators or asset owners capture the value.
3. Winner-takes-all by default. Network effects do not always tip a market; check multi-homing and differentiation.
4. Ignoring the ecosystem. A great product fails if complementors, channels or regulators do not move.
5. Technology enthusiasm without numbers. At least one quantitative test (pricing model, expected value, break-even) should support the recommendation.
6. Static thinking. Recommendations need signposts: what would make you change course, and when.
7. All-or-nothing options. Most technology decisions can be staged; a staged path is often the best answer.
8. Hedging in class. Instructors reward a clear position with reasons and a willingness to update it.

11. Self-test questions

1. What is a dominant design, and what happens to competition after one emerges?
2. Distinguish competence-enhancing from competence-destroying discontinuities, with an example of each.
3. What is an architectural innovation, and why is it hard for incumbents (Henderson and Clark 1990)?
4. State the three elements of Teece's (1986) profiting-from-innovation framework.
5. In a weak appropriability regime, who tends to capture the value of an innovation, and what should the innovator do?
6. Why do network markets sometimes lock in an inferior technology (Arthur 1989)?
7. What does Adner (2017) mean by an ecosystem, and what is a bottleneck in it?
8. In the mini-case, what is the expected value of the open path including the tipping risk? Show the Excel formula.
9. In the mini-case, at what probability of tipping under the closed path would the two paths have equal expected value?
10. In the mini-case, what fee per third-party robot would make the open proposal break even in the base case, ignoring tipping?
11. Why do incumbents that listen closely to their best customers miss disruptive technologies?
12. Give two ways an incumbent can organise to explore new technologies while exploiting its core.

12. My notes and next steps

13. Teaching note for the mini-case

Question 1: life cycle and architecture. Warehouse robots are past the era of ferment for hardware: the robots are converging (the core course mini-case already noted this), which is a sign of an emerging dominant design for the vehicle. Competition is shifting to cost and to the layer that coordinates fleets. Separating orchestration from the robot is an architectural change in the sense of Henderson and Clark (1990): the components (robots, sensors, warehouse systems) are largely the same, but how they are linked changes from integrated single-vendor fleets to a modular, layered system. It threatens vendors whose organisation and sales model assume a single-vendor fleet, including Corvane's own hardware business, and favours whoever controls the coordinating layer. A draft open interface specification is a sign that the industry is moving towards a standard interface, which would make robots more interchangeable still.

Question 2: Teece. The appropriability regime for the interface is weak: narrow patents, code that can be reimplemented, mobile engineers. If the interface itself cannot be protected, value goes to owners of specialised complementary assets. Corvane holds several: the installed base of sites and integrations with warehouse management systems (switching costs), field service capacity, certification know-how, and mission data from thousands of robots that improves congestion analytics (mba/mba-resource-based-view-card). The strategy should therefore make money on those assets (analytics, certification, service, application marketplace) rather than on the interface, and should treat the interface as something that may become a standard anyway.

Question 3: the numbers. The open proposal alone has a negative NPV in both adoption cases, and its expected value is $0.6 \times (-5.869) + 0.4 \times (-17.815) = -10.647$ (USD m; =0.6*-5.869+0.4*-17.815). That is the CFO's point. But the closed path is not worth zero: it carries the tipping risk.

On the team's estimates, the full open proposal is worse by USD 4.743m. Two break-evens matter more than the base case. First, the closed path's tipping probability at which the two paths are equal: $p = (-10.647 + 0.15 \times (-29.518)) / (-29.518) = 0.511$ (=(-10.647+0.15*-29.518)/-29.518). If Competitor A's programme makes tipping more likely than about one in two, opening wins. Second, the fee that makes the open proposal break even in the base case is USD 1,868 per robot per year (solve NPV = 0 for the fee, for example with Goal Seek on the fee cell): the proposed USD 1,500 underprices the layer by about a fifth on the team's own volumes. The payback of the base case is longer than five years (cumulative cash flow still USD -2.37m at the end of 2031).

Question 4: Competitor A. Competitor A can envelop the orchestration function: bundle its layer free with its robots, which most of the segment already buys (Eisenmann, Parker and Van Alstyne 2011). Sites with large Competitor A fleets will single-home on its layer; sites with mixed fleets may multi-home. If Corvane stays closed, it invites the envelopment: its software remains tied to its 9% robot share. If Corvane opens, Competitor A may refuse certification for its robots, which limits Corvane's reach but also makes Competitor A's "open" programme less credible. Expectations matter: an early, credible commitment by Corvane (published interface, certification of the most popular third-party robots, a roadmap of applications) can shift what sites and robot makers expect.

Question 5: ecosystem. Following Adner (2017), map the activities the value proposition needs: robot makers must certify and maintain compatibility; warehouse-system vendors must integrate; application developers must build; integrators must install mixed fleets; customers must trust a single layer with safety-critical traffic. The bottlenecks are certification capacity (Mei-Ling's field engineers) and safety assurance for mixed fleets. An open platform that cannot certify quickly creates a queue of frustrated partners. Following Jacobides, Cennamo and Gawer (2018), the complementarity between Corvane's analytics and the number of robot types is what makes this an ecosystem rather than a supplier network.

Question 6: recommendation. A strong answer chooses the middle path, staged opening that grants access without devolving control (Boudreau 2010): publish the interface for the robot models customers ask for most, keep certification and the analytics in house, price access by value (at or above the break-even of about USD 1,900 per robot a year, or bundled into a site licence), cut the up-front investment by building certification capacity in step with demand, and commit publicly to support the industry interface specification if it becomes the standard. In Rumelt's terms: diagnosis (the control point is moving from the robot to the orchestration layer, where Corvane leads but cannot protect the interface), guiding policy (be the best independent layer and capture value through data, certification and applications), coherent actions (staged opening, value pricing, certification capacity, standards participation). Signposts for the next year: Competitor A's programme launch and its terms (if it is open to third-party robots, accelerate); third-party robots managed against the base path (at least 1,000 in 2027); share of new pilots that start with orchestration; fee realisation against USD 1,868; cannibalisation against plan. The analysis of staged commitment uses the logic of mba/mba-innovation-portfolio-card (Worked example B) and mba/mba-options-real-options-card.

Sources and further reading

Primary works.

• Utterback, J. M., and Abernathy, W. J. (1975). A dynamic model of process and product innovation. Omega, 3(6), 639-656.
• Tushman, M. L., and Anderson, P. (1986). Technological discontinuities and organizational environments. Administrative Science Quarterly, 31(3), 439-465.
• Anderson, P., and Tushman, M. L. (1990). Technological discontinuities and dominant designs: A cyclical model of technological change. Administrative Science Quarterly, 35(4), 604-633.
• Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, 15(6), 285-305.
• Teece, D. J. (2018). Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world. Research Policy, 47(8), 1367-1387.
• Henderson, R. M., and Clark, K. B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 35(1), 9-30.
• Christensen, C. M., and Bower, J. L. (1996). Customer power, strategic investment, and the failure of leading firms. Strategic Management Journal, 17(3), 197-218.
• Christensen, C. M. (1997). The Innovator's Dilemma. Boston: Harvard Business School Press.
• Katz, M. L., and Shapiro, C. (1985). Network externalities, competition, and compatibility. American Economic Review, 75(3), 424-440.
• Katz, M. L., and Shapiro, C. (1994). Systems competition and network effects. Journal of Economic Perspectives, 8(2), 93-115.
• Arthur, W. B. (1989). Competing technologies, increasing returns, and lock-in by historical events. The Economic Journal, 99(394), 116-131.
• Rochet, J.-C., and Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990-1029.
• Caillaud, B., and Jullien, B. (2003). Chicken and egg: Competition among intermediation service providers. The RAND Journal of Economics, 34(2), 309-328.
• Armstrong, M. (2006). Competition in two-sided markets. The RAND Journal of Economics, 37(3), 668-691.
• Boudreau, K. (2010). Open platform strategies and innovation: Granting access vs. devolving control. Management Science, 56(10), 1849-1872.
• Eisenmann, T., Parker, G., and Van Alstyne, M. (2011). Platform envelopment. Strategic Management Journal, 32(12), 1270-1285.
• Gawer, A., and Cusumano, M. A. (2014). Industry platforms and ecosystem innovation. Journal of Product Innovation Management, 31(3), 417-433.
• Adner, R. (2017). Ecosystem as structure: An actionable construct for strategy. Journal of Management, 43(1), 39-58.
• Jacobides, M. G., Cennamo, C., and Gawer, A. (2018). Towards a theory of ecosystems. Strategic Management Journal, 39(8), 2255-2276.
• Bass, F. M. (1969). A new product growth for model consumer durables. Management Science, 15(5), 215-227.
• March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71-87.
• Cohen, W. M., and Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128-152.
• Cooper, R. G. (1990). Stage-gate systems: A new tool for managing new products. Business Horizons, 33(3), 44-54.
• O'Reilly, C. A., and Tushman, M. L. (2004). The ambidextrous organization. Harvard Business Review, 82(4).
• Myers, S. C. (1977). Determinants of corporate borrowing. Journal of Financial Economics, 5(2), 147-175.
• Teece, D. J., Pisano, G., and Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533.

Books and textbooks (further reading only). Rogers, Diffusion of Innovations (Free Press, first edition 1962); Foster, Innovation: The Attacker's Advantage (Summit Books, 1986); Moore, Crossing the Chasm (HarperBusiness, 1991); Shapiro and Varian, Information Rules (Harvard Business School Press, 1999); Dixit and Pindyck, Investment under Uncertainty (Princeton University Press, 1994); Parker, Van Alstyne and Choudary, Platform Revolution (W. W. Norton, 2016); Adner, The Wide Lens (Portfolio, 2012); Schilling, Strategic Management of Technological Innovation (McGraw-Hill); Burgelman, Christensen and Wheelwright, Strategic Management of Technology and Innovation (McGraw-Hill).

Open resource. OpenStax, Principles of Management (CC BY-NC-SA 4.0), chapters on strategy, for background.

Answer key

1. A design that wins the market's allegiance and becomes the reference that competitors must follow. Afterwards, product innovation slows and competition moves to process innovation, cost, scale and incremental improvement (Utterback and Abernathy 1975).
2. Competence-enhancing discontinuities build on existing know-how (a much faster version of an existing chip process); competence-destroying ones make it obsolete (a new technology that needs entirely different skills) (Tushman and Anderson 1986).
3. An innovation that reconfigures how existing components are linked. Incumbents' communication channels, information filters and problem-solving routines are built around the old architecture, so they may not recognise the change or be able to execute it.
4. The appropriability regime, the phase of the industry (before or after a dominant design) and complementary assets (generic, specialised, co-specialised).
5. Owners of the specialised complementary assets needed to commercialise it, or fast imitators. The innovator should secure access to those assets (own them, integrate, or contract on favourable terms) or license if it cannot.
6. With increasing returns, early adopters raise the value of a technology for later adopters, so small early leads (chance events) can grow until the market is locked in, whether or not the technology is the best.
7. The alignment structure of the partners that must interact for a value proposition to materialise. A bottleneck is an activity or partner whose failure to move blocks the whole value proposition.
8. USD -15.075m: =0.6*-5.869+0.4*-17.815+0.15*-29.518 (expected open NPV -10.647 plus the 15% tipping risk on a USD 29.518m loss).
9. About 0.511: =(-10.647+0.15*-29.518)/-29.518.
10. About USD 1,868 per robot per year (Goal Seek: set the base-case NPV to zero by changing the fee).
11. Their resource-allocation processes favour projects demanded by their best customers, with large, near and measurable returns; disruptive technologies first serve small or low-end segments that those customers do not want, so funding them looks irrational until the technology improves enough to take the mainstream.
12. Any two of: an ambidextrous structure with separate exploratory units integrated at the senior team; separate budgets or strategic buckets with different criteria; corporate venture investments or partnerships; staged funding with learning milestones; building absorptive capacity through internal R&D.

Revision history

Standard and licence note

Structure aligned with the technology and innovation strategy literature named above (Utterback and Abernathy, Tushman and Anderson, Teece, Henderson and Clark, Christensen, Katz and Shapiro, Arthur, Rochet and Tirole, Adner, Jacobides, Cennamo and Gawer and others) and with the broad competency areas used in graduate business education. The roadmap, explanations, mini-case, exhibits, teaching note, rubric and answers are original; no published case, teaching note or textbook text is copied or paraphrased, and Corvane Robotics and every person and competitor in the case are fictional. This template is independent and not affiliated with or endorsed by any school, author or publisher. Check your own syllabus for session topics, grading and the rules on collaboration and AI tools. Template licence: MIT.