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Models of Innovation

DRAFT FOR DISCUSSION. Models of Innovation. Edward G. Happ, Global CIO September 2013. Three Types of Innovation*.

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Models of Innovation

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  1. DRAFT FOR DISCUSSION Models of Innovation Edward G. Happ, Global CIO September 2013

  2. Three Types of Innovation* • Empowering (or disruptive) innovation – “transmutes complicated and costly products available to a few into simpler, cheaper products accessible to many” “creating new markets and wreaking havoc within industries” (e.g., Ford Model T car) • Sustaining innovation – “replaces old models with new products that often incorporate new technology and novel design features.” “making things incrementally bigger, more powerful, and more efficient” (ex. Toyota Prius) • Efficiency innovation – “makes existing products more proficiently” (ex. Lean production) Only disruptive innovations create new jobs *Clay Christensen, Davos interview, January 2013

  3. What are we trying to optimize? • Thinking outside the box; engage the creativity of our people • Investing small amounts for big returns • Delivering new program/services that demonstrate impact and scale In short, engaging our creativity to maximize supply and minimize constraints

  4. Models of Innovation • Traditional, top-down innovation • Discovery innovation, an inverted model • Disruptive Innovation, Clay Christensen model • The R&D lab, corporate model • Controlled experiments, the Dartmouth model • Crowdsource ideagoria, the Tapscott model

  5. 1. Traditional, top-down innovation An Internal Model Shadow IT Demand Supply Capacity ITSG Filter Internal apps (5 years, 60 apps) User needs A “do” model 12-20 projects/year Incremental, Sustainable, BPR • Problems • Getting to new apps • ISD cost bottleneck Strategy: grow the apps by widening the capacity filter

  6. 2. Discovery innovation, an inverted model An External/Internal Model Shadow IT Supply Scaled Sharing Capacity Quality Filter Shared apps (3 years, 900 apps) User, local apps A “harvest” and polish model Contests, consultations, criteria • Problems • Freeing up resources to run • Reallocation 20% of project budget • Does not work for enterprise apps and systems Strategy: widen the supply scan and filter

  7. 3. Disruptive Innovation, Christensen model An External Model User self-selection (variation on shadow IT) Demand New Supply BYOD, BYOA A Filter Bypass • Problems • Rarely embraced in HQ • Radical change is hard • Challenges letting go of core • Risky bets Strategy: scan horizons and partner

  8. 4. The R&D lab, corporate model An Internal Model Demand Supply Winners: Scaled apps Lab Funding Filter Research, Tech. context Losers: Learning Opp’s A traditional model • Problems • Expensive investment • Long development cycles • Costly failures • Elitist Strategy: invest in experiments; tolerate failures

  9. 5. Controlled experiments, Dartmouth model An Internal Model Learning Loop Supply Results Lab Scaled apps Ideas A try-learn-do model • Problems • Lab size limit • Lab speed • Idea self-dependence, myopia Strategy: limited experiments, clear learning

  10. 6. Crowd-sourced ideagoria, Tapscottmodel An External Model Shadow IT Demand Supply Crowd Capacity Wide Filter Surviving apps User needs A volume model • Problems • Takes significant humility Strategy: harvest the best of the solutions

  11. Conclusions • The traditional approach is not working • As must-do, compliant and continuing projects dominate, we have a declining number of new projects approved for funding • Funding to “widen” the filter is an issue, as is human capacity • The R&D lab approach is too expensive and time consuming • The crowdsource-ideagoria may be too radical for a humanitarian organization • Disruptive innovation may first be an awareness, over coming denial issue • Discover and harvest plus controlled experiments may be best suited for the next step

  12. Recommendation • Combining the Discover and Harvest model (option 2) with Controlled Experiments (option 5) may be best suited for a nonprofit organization budget and culture • Use a project review panel, pilots and contests to create an ecosystem for innovation to take root, flourish and scale • Disciplined experimenting to take projects from Pilot to Scale to Mainstream, with try-learn-do investment levels • Create an innovation fund to get started • Reallocate existing budget to create an initial budget of 1.5M CHF and evaluate after one year (See the IT Think paper for details)

  13. Appendix

  14. Model factors • Supply side – the aggregation of solutions (apps, ideas) • Demand side – the aggregation of needs • Capacity side – the ability to deliver on needs and solutions

  15. Innovation at the margins Historical IT – all components provided Local innovation is more likely and sustainable at the outer layers of IT delivery Current Era – Users bring their own devices and apps Future Era – Users bring their own networks Standard core – it is unlikely users will have or should have their own Finance, HR, Supply Chain, and Legal applications and data

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