recognized an opportunity to improve development cycle time,
product value, and business results by augmenting the current
process with additional practices. As a result, we initiated a
cross-industry best practice study with a goal to collect innova-tion transfer best practices from other companies, synthesize our
findings to determine the most feasible practices to implement at
Intel, and then set upon a journey of implementation.
Innovation-transfer best practice study learnings
As we began our best practice study, we did not anticipate the dif-
ficulty we would encounter in finding companies that felt they had
best practices to share. Most responded that they were experiencing
the same transfer problems. Additionally, we found little literature
available concerning internal technology-transfer practices. One
technologist shared his belief that the lack of literature on this issue
was due to most people accepting that innovation transfer is difficult,
and they are therefore content to “admire the problem.”
Eventually, we were able to identify a set of practice leaders
and complete our research by identifying a number of best prac-
tices that could be implemented at Intel. At a high level, the best
practices were identified as the following:
Portfolio management techniques are used to select and 1.
prioritize innovation options.
There must be an appropriate balance between technology 2.
push and usage pull for technology solutions.
Technology maturity is best managed via rigorous risk man- 3.
agement and life cycle processes.
Strategic roadmapping techniques are effective in linking 4.
market, usage, product, and technology strategy.
The presence of a corporate-level technology strategy orga- 5.
nization can drive practices one through four.
As stated, one of the best practices identified in the study was
the use of portfolio management techniques to identify the inno-vations that will deliver the greatest value and have the highest
probability of implementation success. However, we learned that
the use of portfolio management in the innovation transfer process
is quite different than its use in the later stages of project and
product selection. The two greatest differences are: 1) a qualitative
assessment of innovation ideas should be used, and a quantita-tive assessment should be avoided; and 2) multiple perspectives
must be involved to avoid personal and organizational bias in the
assessment process.
All best practice companies in our study used portfolio manage-
ment techniques to select and prioritize their own set of potential
innovations, and all used qualitative criteria and scoring methods
to assess value. Quantitative measures such as financial return on
investment or net present value were avoided. The base justification
behind this qualitative approach is that there is too much uncertainty
in the “fuzzy front end” of the innovation process to try to quantify
value. Greater value is gained from a discussion of value based
upon more qualitative measures such as strategic value, competitive
positioning, and customer pull. This finding is consistent with our
own practical experience, where our greatest difficulties in imple-
menting portfolio management practices within Intel have come in
trying to define and use quantitative scoring models.
Best practice companies also expressed the need to bring
innovation selection and prioritization out of the “smoke-filled
back room,” where a small number of über experts make the
selection and prioritization decisions. Best results are gained
when a collective and collaborative approach was used where
multiple disciplines, functions, and roles were represented and
have an equal voice in the selection and prioritization process.
This brings stickiness and broader buy-in of the selection and
prioritization outcomes.
Wisdom of Crowds emerges
Once we completed the innovation-transfer best practice report,
focus then turned to looking for opportunities to implement the
best practices within Intel. We began by presenting the findings
to the various stakeholders who were involved in the early fact-finding stage of the study. As anticipated, these discussions led
to implementation opportunities.
One individual, who is responsible for the technology readi-ness process at Intel, identified the need to improve the portfolio
management process for portfolios of like-technologies developed
in the exploration phase of the life cycle (see Exhibit 2).
He explained that the priorities for these portfolios were chang-ing on a monthly basis in some cases. Analysis of the problem
showed that there were three primary causes for the prioritization
problem:
Exhibit 1: How Intel uses the Wisdom of Crowds technique to cross the Valley of Death in technology selection
Technology portfolio
prioritization
product Technology &
Feature prioritization
Exploration
The Valley
of Death
Planning
Development
Production
Traditionally, the Valley of Death (VoD) sits between the Exploration and Planning stages of the new
product development process. Many ideas do not make it across this divide. In this example, the
VoD is the point at which Intel weeds through innovation technologies. On the left is Exploration,
where Intel used the “Wisdom of Crowds” technique described in this article to prioritize selection
of different technologies it was considering. On the right is the Planning phase, where those
technologies with the most promise are evaluated against other product innovations.
