This document summarizes a webinar about how intelligence practices can reduce uncertainty during the front end of innovation (FEI) process. It discusses how classical new product development differs from an intelligence-driven innovation approach. An intelligence-driven approach utilizes more qualitative data, cross-functional teams, and agile experimentation. Preliminary results suggest intelligence methods generate more insights and ideas that progress further in the innovation process. The webinar concludes by discussing expanding the use of intelligence-driven innovation across more companies and industry contexts.

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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: dblenkho@wlu.ca
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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&D
Prototyping/
Adjusting
Feasibility/
Pre-
Marketing
The Business End
Plan
Build
Evaluate
The “Messy” Back EndThe Product Management End
Sunsetting
Customer
Support &
Maintenance
Delivery
Sales +
Marketing
The Difficult Innovation Process
in 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

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Intelligence Propels the 10 Essentials
of Strategic Innovation
1. Innovation has to be integrated and managed at the core of the strategy, as a pivotal, visible
corporate value – continuously focused
2. Core competencies – explicity outline the linkages between your L/T strategic goals and
R&D/innovation investments and technology strategies
3. It should move your organization from balancing/optimizing your business to/and creating
business and new spaces
4. 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 scenarios
7. It’s an inside-out, open process of interacting w/customers, prospects, suppliers, partners,
competitors, staff
8. Balance supply-pushed (new technologies) with demand-led (based on CX/UX, market
requirements) – directly involve suppliers and customers
9. Design smart systems for idea assesment+prioritization of detected/selected opportunities
10. 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 Educational
Backgrounds
- 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 mapping
war-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 *
* (Source: Fleisher & Blenkhorn, 2016, PDMA Proceedings, Atlanta)

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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 FEI
Alternative Futures Design Thinking
Blue Sky Thinking Ethnography
Brainstorming | Brainwriting Market Opportunity & Sizing
Convergent Thinking Product Life Cycle
Customer Journey Mapping Product Lines and Markets
Divergent Thinking Road Mapping
Idea Management Systems Scenario Thinking
Mind Mapping S-curve mapping | Tech Life Cycle
Red/Blue Teaming Strategic Relationships
Shadowing Technology Scouting
Simulations/Games Trend Analyses
* (Source: Fleisher & Blenkhorn, 2016, PDMA Proceedings, Atlanta)

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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 Innovation
BEFORE
Front End of Innovation
AFTER

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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: dblenkho@wlu.caDr. David Blenkhorn