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11 — References

References​

  • Amabile, T. M. (1997). Motivating creativity in organizations: On doing what you love and loving what you do. California Management Review.
  • Amabile, T. M., & Kramer, S. J. (2011). The Progress Principle: Using Small Wins to Ignite Joy, Engagement, and Creativity at Work. Boston: Harvard Business Review Press.
  • Bessant, J., & Tidd, J. (2015). Innovation and Entrepreneurship. Wiley.
  • Bettencourt, L. (2010). Service Innovation: How to Go from Customer Needs to Breakthrough Services. McGraw-Hill Education.
  • Brown, T. (2009). Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation. HarperBusiness.
  • Chesbrough, H. (2006). Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business School Press.
  • Chesbrough, H. (2011). Open Services Innovation: Rethinking Your Business to Grow and Compete in a New Era. San Francisco, CA: Jossey-Bass.
  • Christensen, C. M. (1997). The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business School Press.
  • Christensen, C. M., Anthony, S. D., & Roth, E. A. (2004). Seeing What's Next: Using Theories of Innovation to Predict Industry Change. Harvard Business School Press.
  • Cooper, R. G. (2001). Winning at New Products: Creating Value Through Innovation. Perseus Publishing.
  • Davila, T., Epstein, M. J., & Shelton, R. (2006). Making innovation work: How to manage it, measure it, and profit from it. Upper Saddle River, NJ: Wharton School Publishing.
  • DARPA. (n.d.). The Heilmeier Catechism. From DARPA: link
  • Doulab. (n.d.). AFP Siembra case study. From Doulab: link
  • Doulab. (n.d.). Innovation Maturity Model program. From Doulab: link
  • Doulab. (n.d.). OGTIC RedLab Innovation Network case study. From Doulab: link
  • Donovan, M., & Grace, A. (n.d.). Innovation Frameworks: What They Are and How to Build One. From GP Strategies: link
  • Edmondson, A. C. (2018). The Fearless Organization: Creating Psychological Safety in the Workplace for Learning, Innovation, and Growth. Wiley.
  • El Caribe. (2023). OGTIC lanza la Red de Laboratorios de Innovación (RedLab). From El Caribe: link
  • Elkington, J. (1997). Cannibals with Forks: The Triple Bottom Line of 21st Century Business. Capstone.
  • Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: from National Systems and "Mode 2" to a Triple Helix of university-industry-government relations. Research Policy.
  • Freeman, C. (1987). Technology policy and economic performance: Lessons from Japan. Pinter Publishers.
  • Friedman, T. L. (2007). The World Is Flat 3.0: A Brief History of the Twenty-first Century. Picador.
  • Hagel, J., Brown, J. S., & Davison, L. (2010). The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion. Basic Books.
  • Hammer, M. (2001). The Agenda: What Every Business Must Do to Dominate the Decade. New York: Crown Business.
  • Harvard Business Review. (2009). Innovator's Toolkit: 10 Practical Strategies to Help You Develop and Implement Innovation. Harvard Business Review Press.
  • Joubert, S. (2017, December 21). The Innovation Process: A Step-by-Step Guide. From Digital Leadership: link
  • Kaplan, R. S., & Norton, D. P. (1996). The Balanced Scorecard: Translating Strategy into Action. Harvard Business School Press.
  • Kaplan, R. S., & Norton, D. P. (2008). The Execution Premium: Linking Strategy to Operations for Competitive Advantage. Boston, MA: Harvard Business Press.
  • Kaplan, S. (2012). The Business Model Innovation Factory: How to Stay Relevant When The World is Changing. Wiley.
  • Keeley, L., Pikkel, R., Quinn, B., & Walters, H. (2013). The Ten Types of Innovation. Wiley.
  • Kelley, T., & Kelley, D. (2013). Creative Confidence: Unleashing the Creative Potential Within Us All. Crown Business.
  • Kim, W. C., & Mauborgne, R. (2005). Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant. Harvard Business Review Press.
  • Kline, S. J., & Rosenberg, N. (1986). An overview of innovation.
  • Kotter, J. P. (1996). Leading Change. Harvard Business Review Press.
  • Kurzweil, R., & Meyer, C. (2003, May 3). Understanding the Accelerating Rate of Change. From the Kurzweil Library + collections: link
  • Lane, N. (1999). Why do we need an innovation policy? In Science and Technology Policy Yearbook. American Association for the Advancement of Science.
  • LeFave, D. (2023, September 7). Entrepreneurs in Survival Mode: How Stress Hormones Control Their Future. From linkedin: link
  • McKinsey & Company. (2018). Disruptive forces in the industrial sectors: Global executive survey. From mckinsey.com: link
  • McQuivey, J. (2013). Digital Disruption: Unleashing the Next Wave of Innovation. Amazon Publishing.
  • Mitzkus, S. (2024). Innovation Lifecycle: Understanding the Curve & the Cycle of Innovation. From Digital Leadership: link
  • Moore, G. A. (1991). Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers. HarperBusiness.
  • Moore, G. A. (1999). Inside the Tornado: Marketing Strategies from Silicon Valley's Cutting Edge. New York: HarperBusiness.
  • Moore, M.-L., & Westley, F. (2011). Surmountable Chasms: Networks and Social Innovation for Resilient Systems. Ecology and Society.
  • Mulgan, G. (2014). Design in Public and Social Innovation: What Works and What Could Work Better. Nesta.
  • Nidumolu, R., Prahalad, C. K., & Rangaswami, M. R. (2009). Why sustainability is now the key driver of innovation. Harvard Business Review.
  • Nonaka, I., & Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York: Oxford University Press.
  • O'Reilly, C. A., & Tushman, M. L. (2016). Lead and Disrupt: How to Solve the Innovator's Dilemma. Stanford University Press.
  • OECD OPSI. (2023, December 18). Innovation labs through the looking glass: Experiences across the globe. From OECD OPSI: link
  • Oslo Manual 2018: Guidelines for Collecting, Reporting and Using Data on Innovation, 4th Edition, The Measurement of Scientific, Technological and Innovation Activities. (2018). Paris/Eurostat, Luxembourg: OECD Publishing.
  • Osterwalder, A., & Pigneur, Y. (2010). Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers. Wiley.
  • Porter, M. E. (1998). On Competition. Harvard Business Review Press.
  • Prahalad, C. K., & Ramaswamy, V. (2004). Co-creation experiences: The next practice in value creation. Journal of Interactive Marketing.
  • Ries, E. (2011). The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. Crown Publishing Group.
  • Roland Berger. (2025, May). What innovators can still learn from Xerox PARC. From Roland Berger: link
  • Russell, S., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach. Pearson Education.
  • Schneier, B. (2004). Secrets and Lies: Digital Security in a Networked World. Wiley.
  • Schumpeter, J. A. (1934). The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle. Harvard University Press.
  • Startup Genome. (2011, September 02). A Deep Dive Into The Anatomy Of Premature Scaling. From Startup Genome: link
  • Sutherland, J. (2014). Scrum: The Art of Doing Twice the Work in Half the Time. Crown Business.
  • Sutherland, J., & Schwaber, K. (2013). The Scrum Guide: The Definitive Guide to Scrum: The Rules of the Game. Scrum.org.
  • Tidd, J., & Bessant, J. (2018). Managing Innovation: Integrating Technological, Market and Organizational Change. Wiley.
  • Wagner, T. (2012). Creating Innovators: The Making of Young People Who Will Change the World. Scribner.
  • West, M. A. (2002). Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups. Applied Psychology: An International Review.
  • Westley, F., & Antadze, N. (2010). Making a difference: Strategies for scaling social innovation for more significant impact. The Innovation Journal.
  • Wired Insider. (n.d.). Innovation is accelerating. Here's how to keep up with the pace. From Wired.

Appendices​

Introduction to the MicroCanvas Framework (MCF 2.2) and the structure of innovation projects using Micro Sprints​

MCF 2.2-Tools-Core v2.0 - EN Luis Santiago (luis@lsantiago.net) April 10, 2024

The motivation behind an innovation framework​

The MicroCanvas Framework (MCF 2.2) is the result of a six-year research effort beginning in 2018 at NASA Ames Campus in Mountain View, California. During this time, as an Entrepreneur in Residence for Singularity University's (https://su.org) Graduate Studies Program, I focused on how to improve innovation practice in organizations based outside Silicon Valley.

As a software developer from the Dominican Republic myself, I'm familiar with survival entrepreneurship and how the "stress response" can lead to constrained decisions during entrepreneurship. (LeFave, 2023). At the time, the question was, "How can I guide my customers to faster innovation cycles with an approach that works across cultural contexts and economic realities, globally?"

It became clear that many innovation frameworks only cover part of the innovation lifecycle and that, for many teams, the knowledge required to manage innovation at a sustained pace was still out of reach. Thus, a new "meta framework", one that would logically connect aspects or "micro-processes" of the full innovation lifecycle was needed. This was the point when the "MicroCanvas" Framework was defined.

External disruptions are affecting all industries and all types of organizations.​

According to a 2018 McKinsey report, "The industrial sectors will see more disruption within the next five years than in the past 20 years combined." (McKinsey & Company, 2018). These disruptions will only accelerate as the "the 21st century will be equivalent to 20,000 years of progress at today's rate of progress." (Kurzweil & Meyer, 2003).

This means that significant stress is already straining many organizations' ability to understand and apply meaningful measures to tackle challenges produced by rapidly changing market conditions.

In practice, this means leadership teams need measurable signals for when to adjust portfolio decisions.

Developing innovation at a sustained and consistent pace is not easy.​

Many organizations struggle to maintain a consistent pace of innovation development. Sometimes it feels like innovation is an art more than a science. During the first stages of our exploration of innovation frameworks, we realized that innovation can be measured and learned as a process that organizations can implement.

Operationally, this shows up as inconsistent cadence and unclear decision gates.

Although creating new products and services may never be "easy", failure rates can decrease when "uncertainty" is reduced by having a structured innovation process. This raises the question of how organizations adapt to faster change, often through an organizational change process focused on a transformative purpose.

According to a team at PA Consulting, the statement that "Developing life-changing technology at pace is an artform" emphasizes defining purpose early. (Wired Insider, n.d.).

At Doulab, we found that developing a transformative purpose required a deeper understanding of customers, their pains, needs, and goals, and a clearer view of the root causes behind the problems being addressed.

For that reason, the MicroCanvas Framework (MCF 2.2) focused on dividing the innovation lifecycle into short "Micro Sprints", small experiments designed to help the organization reduce risk and volatility by implementing continuous agile innovation.

These micro sprints were intended to shorten innovation cycles and support problem/solution fit during the "Discovery" phase of innovation projects, as well as product/market fit during the "Validation" phase. This can reduce cost and volatility associated with faster innovation cycles. By building each micro sprint in a modular fashion, a linear path was not needed.

As long as the previous steps of the innovation process had well-defined outputs (for example, a well-defined understanding of the problem), there may be no requirement for an organization to follow the innovation process from the start, but rather start with a module in a later process.

Additionally, the MicroCanvas Framework (MCF 2.2) was designed to accommodate each phase of the innovation lifecycle and each of the "Contexts", a logical sub-division of the framework, designed to organize each of the micro-processes depending on what part aspect of the organization was designed to work for, was also logically connected through the whole innovation process.

The Life cycle of innovation and entrepreneurship development.​

We decided to adopt the "standard model" of innovation and entrepreneurship development that divides the innovation process in the following stages:

  • Discovery: It involves identifying unmet market needs, generating innovative ideas and exploring potential solutions. It is a relevant phase in which entrepreneurs and organizations evaluate the viability of their concepts through research and analysis before moving to more concrete stages such as validation, efficiency optimization and scalability.

  • MCF 2.2 processes associated with this stage: Customer Analysis, Problem Analysis, Objectives and Key Results, Solution Alternative Analysis, Unique Advantages and Product Features, Transformative Purpose, Team Structure and Business Model Validation.

  • Validation: It involves approving and confirming that a product, service or business model meets the identified needs of the market and has the potential for success. This often includes conducting experiments, collecting feedback from potential customers, and refining the offering based on that feedback to support it aligns with customer demands and preferences.

  • MCF 2.2 processes associated with this stage: Key Growth Metrics, Key Impact Metrics, Sales, Marketing and Engagement, User Stories, Customer Experience and Loyalty and Business Model Validation.

  • Efficiency: It involves evaluating and improving operations, workflows, and product features to support they are delivered with minimal resources while maintaining or improving customer value. It is about making the delivery of the product or service as efficient and simple as possible while supporting sustainable growth and scaling.

  • MCF 2.2 processes associated with this stage: Cost and Revenue Structure, Risks, Operations, Financial Analysis, Legal Compliance and Strategy, External Stakeholders, Regulatory Constraints, External System Integrations, Product Architecture and Business Model Validation.

  • Scalability: It involves optimizing and improving processes, infrastructure and systems to support growth, increase the ability to deliver products or services to a larger market segment and support that the business model can sustain increased sales and operations efficiently.

  • MCF 2.2 processes associated with this stage: Future Disruptions, Accelerated Growth Attributes, Key Partners, Delivery Channels, Socio-cultural Context and Business Model Validation.

  • Continuous: it involves continuously analyzing each aspect of the business model to continuously adapt by experimenting, monitoring, learning and improving.

  • MCF 2.2 processes associated with this stage: Customer Analysis, Key Impact Metrics, Key Growth Metrics, Cost and Revenue Structure, Risks, Future Disruptions and Business Model Validation.

Conclusion​

The development of MCF 2.2 v2.0 reflects iterative work across multiple cycles.

After more than 250 micro sprints with customers ranging from the financial and educational sectors, health, technology and others, coming from countries in the US, Europe and Latin America, with some notable failed experiments but many more successes, we have been able to distill and refine an innovation process that can help not only with innovation projects but also with organizational transformation.

As work continues, MCF 2.2 may evolve and incorporate new tools as technologies mature, including artificial intelligence. This section is a forward-looking observation rather than a prediction of outcomes.