how intelligence practices reduce the fuzziness at the front end of innovation

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How Intelligence Practices Reduce the “Fuzziness” at

the Front End of Innovation

A Complimentary Webinar from Aurora WDC

12:00 Noon Eastern /// Wednesday 16 November 2016

~ featuring ~

Dr. David Blenkhorn Dr. Craig Fleisher


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Dr. David Blenkhorn

David Blenkhorn, CPA, CMA, is Professor of Marketing at Wilfrid Laurier University in Waterloo, Ontario, Canada, where he teaches courses in Competitive Intelligence, Business-to-Business Marketing, and Marketing Strategy. He is co-editor of the books (1) Competitive Intelligence and Global Business, (2) Controversies in Competitive Intelligence: the Enduring Issues, (3) Managing Frontiers in Competitive Intelligence, and co-author of the book Reverse Marketing: the New Buyer-Supplier Relationship. He has published articles on competitive intelligence, business relationship management, business-to-business marketing, and organizational effectiveness in journals such as Journal of Competitive Intelligence and Management, Journal of Advertising, Industrial Marketing Management, and Journal of Business and Industrial Marketing, among others. Email: [email protected]

The Intelligence Collaborative is the online learning and networking community powered by Aurora WDC, our clients, partners and other friends and dedicated to exploring how to apply intelligence methods to solve real-world business problems.

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mailto:[email protected]


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Questions, Commentary & Content


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The Genesis of This Research► Companies frequently fail at NPD.

Failures often come from the “fuzzy front end” (FEI).

► Some FEI failures are due to failures to develop intelligence about customers, needs, functionality, markets, and technology ecosystems.

► Though we have seen recent innovations in developing or employing FEI research methods, the range used is still too narrow and misses on capturing key insights.

► Many intelligence-based methods can be applied to improve the probability of FFE success.

FEI

The activities that take place before a product development

process (PDP) has been established.


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The “Fuzzy” Front End

Solutions

Ideas

Problems

R&DPrototyping/

Adjusting

Feasibility/Pre-

Marketing

The Business End

Plan

Build

The “Messy” Back EndThe Product Management End

SunsettingCustomer Support &

MaintenanceDelivery Sales +

Marketing

The Difficult Innovation Processin New Product Development (NPD)


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The “Fuzzy Front End” of Innovation (FEI)

1000s of Possible Business Ideas

100s of Ideas that Fit Your Capabilities

10s of Ideas that Fit Strategic Interests

Several Ideas that Users are Demanding

A Few Ideas that Users Will Pay For

A Couple Ideas that Will Scale

The 1 Idea that Became a Great Success

Ideation

Market & Tech Evaluations

Product Development

& Trials

Whole PD

Scale Up

Commercialization

FEI: The activities that take place before a product development process (PDP)

has been established.


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“In what ways can intelligence methods and processes contribute to reducing the “fuzziness” experienced by organizations during the front end of innovation (FEI) in the NPD process?”

Research Question

Intelligence-driven Innovation?


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Intelligence Propels the 10 Essentialsof Strategic Innovation1. Innovation has to be integrated and managed at the core of the strategy, as a pivotal, visible

corporate value – continuously focused2. Core competencies – explicity outline the linkages between your L/T strategic goals and

R&D/innovation investments and technology strategies3. It should move your organization from balancing/optimizing your business to/and creating

business and new spaces4. You’ll need to develop cross-functional innovation and/or insight teams (with R&D’s

participation, of course, but not only theirs)5. Stimulate participative management, a high degree of delegation & responsibility,

collaborative & team works, and employee engagement (an innovative HRM style)6. Continuous development of industry/market foresight – actively monitoring and exploring

emerging trends and developing alternative scenarios7. It’s an inside-out, open process of interacting w/customers, prospects, suppliers, partners,

competitors, staff8. Balance supply-pushed (new technologies) with demand-led (based on CX/UX, market

requirements) – directly involve suppliers and customers9. Design smart systems for idea assesment+prioritization of detected/selected opportunities10. Space – innovation teams need dedicated space (-s) to work and collaborate


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Classical Approach to NPD Intelligence-driven Innovation (IdI) Approach

1. Analysts:Their EducationalBackgrounds

- engineering- marketing - new product planning- single disciplines/majors - the traditional sciences

- communication- cross-disciplinary/dual majors- data sciences- intelligence studies- liberal arts

2. Analysts: Their Functional Backgrounds

- functional silos- marketing- product engineers- single discipline data teams

- cross-disciplinary data teams- crowd-sourced- insight teams- subject matter expert networks

3. Nature of Data Utilized

- existing products./services logs- heavily quantitative- legacy records- off-line testing- past customer behavior structured - traditional/classic experiments

- creative design- heavily qualitative- mobile/recorded- real-time experiments/field testing- semi- and unstructured data - socially generated

4. Degree of Change Achieved

- additive- functional improvements- one-offs- refinements of existing products

- disruptions- exponential- field or market changers- revolutionary

5. IT and Systems Support

- assigned per project- closed/proprietary platforms- data mining techniques- enterprise data warehouses- fixed cost investments

- collaborative- customized insight portals- fusion centers- platforms- variable/marginal cost investments

Intelligence-driven Innovation or IdI *

* (Source: Fleisher & Blenkhorn, 2016, PDMA Proceedings, Atlanta)


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Classical Approach to NPD Intelligence-driven Innovation (IdI) Approach

6. Methods Used to Collect Data

- automated mobile collection- focus groups- internal sales records- purchase behavior data records- sensors/smart devices- targeted web-based techniques

- computer-assisted phone interviews - ethnographic interviews/observation - face-to-face interviews (developing areas.) - focus groups- social communication platforms

7. Nature of Analysis Methods Used

- those taught in business and engineering schools, e.g., SWOT, voice of the customer (VOC), user experience (UX), traditional statistical methods, data mining, web analytics, etc.

- socialized, cross-functional, collaborative, synchronous, and/or interactive methods; e.g., competitive simulations, customer journey mapping,red/blue teaming, mind mappingwar-gaming, etc.

8. Nature of Planning - grand visions- longer cycle- set cycles- strategic

- agile experimentation- iterative cycles- opportunistic- shorter cycle

9. Organizational Structure

- business unit-based- NPD unit- permanent- silos

- agile/rotating- cross-functional- fluid structures- insight teams

10. Timing Considerations & Project Time Frame

- deliberate - must pass stage gates- planned - show results next quarter/year

- agile- longer-term, 2 cycles or more in future- opportunistic- rapid production of preliminary results

Intelligence-driven Innovation or IdI *



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Intelligence-based Analysis Methods

Key Intelligence-based Analysis Methods Underlying

1) Idea-driven FEI

Key Intelligence-based Analysis Methods Underlying

2) Opportunity-driven FEIAlternative Futures Design ThinkingBlue Sky Thinking EthnographyBrainstorming | Brainwriting Market Opportunity & SizingConvergent Thinking Product Life CycleCustomer Journey Mapping Product Lines and MarketsDivergent Thinking Road MappingIdea Management Systems Scenario ThinkingMind Mapping S-curve mapping | Tech Life CycleRed/Blue Teaming Strategic RelationshipsShadowing Technology ScoutingSimulations/Games Trend Analyses



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Preliminary Results

1. When companies apply IdI, they generate a higher volume of actionable insights.

2. The use of IdI increases the likelihood that ideas will receive higher levels of executive investment.

3. IdI results in a higher percentage of ideas that make it to subsequent parts of the innovation process.

4. IdI introduces new techniques in data collection and analysis which are not currently utilized in traditional NPD .

5. IdI is complementary to traditional NPD, not a substitute for it.

Front End of InnovationBEFORE

Front End of InnovationAFTER


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What’s Next?

► Expand the number of companies adopting IdI.

► Attempt to employ a wider and deeper range of IdI conepts/analytics in the traditional NPD process.

► Apply IdI across more industry/vertical contexts.

► Educators/programs must ramp up with the new digitally-based social data inputs and techniques.

► Traditional NPD analysts must morph to include IdI analytics.


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Thank you!

Now how about a little Q&A?

The Intelligence Collaborative is the online learning and networking community powered by Aurora WDC, our clients, partners and other friends and dedicated to exploring how to apply intelligence methods to solve real-world business problems.

Apply for a free 30-day trial membership at http://IntelCollab.com or learn more about Aurora at http://AuroraWDC.com – see you next time!

Email: [email protected]. David Blenkhorn