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A Model for Assessing the Maturity of
Technical Ladders
Need for a tech-ladder maturity
assessment model
Most of the technology organizations
define dual-ladders: a managerial ladder and a technical
ladder. They also have an associated competency
framework that helps the organizations define entry
criteria for each level of the ladder and is used in
hiring, promotions reviews and in career pathing of
employees.
Between the two ladders, assessment of
the managerial ladder is relatively better understood.
After all, the metric associated with managerial ladder
is indeed tracked by investors and customers. How much
revenue did you lose due to delivery slippage? How come
there is so much difference between the profitability of
BU1 and BU2? How much revenue did you close against the
plan last quarter? How much is your attrition vis-à-vis
competition? We hear these questions in internal
management meetings as well as in analyst calls. We
don’t need to look anywhere else for judging how our
management is performing. However, nobody asks what kind
of patents did you file last quarter?
Or how many new ideas did you implement last year? And
you can’t blame analysts for that. Unless your revenue
from patents is 50% of your total revenue (like that of
Qualcomm which had a revenue of $683 million a quarter
from QTL division Q-Jun-2006 which is 57% of Qualcomm’s
total revenue), you don’t have an easy way to measure
how well your technical ladder is working.
However, technical ladder exists for a
reason (if it exists). It is expected to make
significant contribution in building a technology brand,
it is expected to give competitive advantage to the
organization, and it is expected to nurture the
aspirations of the young and bright talent the company
is attracting. Hence, it is imperative that
organizations start thinking about a model to assess the
maturity of the technical ladder and it should have a
feedback loop like in CMM so that system can improve
itself.
Key
parameters of the assessment model
How do we assess the maturity of a
tech-ladder? Well, that depends upon what it is expected
to achieve. Not every technology organization with a
tech-ladder is focusing on its patent portfolio. Or for
that matter, expecting quality patents from an
organization where good white papers don’t come out, is
like expecting “Defect Prevention” activity to mature
before “Risk Management” is matured in the CMM
framework.
I believe that following parameters
should be considered while assessing the maturity of
tech-ladders:
-
Strategy alignment:
How much of the tech-ladder output is in line with
today’s and tomorrow’s business?
-
Productivity:
How many papers
are we publishing in conferences? How many patents
are we filing? Are we helping the business
acquisition folks enough to explain or demonstrate
our technology / offering?
-
Career pathing:
Do employees believe in tech-ladder? Is tech-ladder
motivating young and bright engineers plan their
careers? Is it creating role models? Are some of
the senior folks in the tech-ladder creating a brand
outside the organization (like do we have an
embedded-guru or a database-guru or Linux-guru etc.)
A
sample model
Following
table shows how we can use the parameters mentioned
above to build a model. I am sure this can be refined
further. However, this shows an approach how we can
build one.
|
Stage |
Characteristic |
Strategic alignment |
Productivity |
Career pathing |
|
Initial |
Nobody knows if/how it is working
|
Low |
Low |
Low |
|
Repeatable |
-
Some output
coming out in a predictable manner.
-
Not aligned to
strategy yet.
-
People are not
sure of tech ladder yet.
|
Low |
Medium |
Low |
|
Defined |
-
Strategic
alignment (measurable)
-
Measurements
in place for productivity and career pathing
-
At least a few
people start saying, “I want to be like
her/him”
|
Medium |
Medium |
Medium |
|
Managed |
-
External brand
building happens (papers, patents, standards
contribution)
-
Critical mass
of role models
|
Medium |
High |
Medium |
|
Optimizing |
|
High |
High |
High |
This is not entirely true. In the analyst call
for quarter ending June 2006, Qualcomm’s CEO
Paul Jacobs mentioned “While we do not believe
that counting schemes of any kind are a reliable
measure of the value and quality of patents, the
frequency with which one’s patents are cited by
others is obviously more of an indicator of the
importance of a patent portfolio than simply
counting essential patents in a standard.
Looking at citations is a measure of
significance somewhat analogous to the way
Google ranks Web pages by examining the number
of links to that page. When you factor out
citations by a company of its own patents,
QUALCOMM has 47% of the citation-weighted
portfolio of essential patents for WCDMA,
followed by Ericsson at 21%. Significantly,
Nokia has only 3%, NEC 2%, Panasonic 1%, and TI
and Broadcom have less than 1%.”
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