 |
 |
 |
|
|
Bookmark this page to stay current with all of Doug Hubbard's upcoming engagements. |
|
 |
 |
 |
|
 |
 |
 |
 |
How
To Measure Anything: Finding the Value of
Intangibles in Business
Expert Doug Hubbard will give us a sneak
preview of key ideas in his upcoming book
about how to measure things usually
considered “immeasurable.” In the last ten
years, Hubbard has quantified such things as
the value of the public health benefits from
better information management at the U.S.
Environmental Protection Agency and the
method the U.S. Marine Corps uses to
forecast fuel for battlefield operations.
He asserts that the idea that some things
are immeasurable is based on a set of
misconceptions about statistics and
measurement in general or, in many cases, a
lack of a clear definition of what the
proposed “intangible” really is. Whatever
is relevant to business must have observable
consequences. The presentation will
include:
-
The three reasons why anything is ever (incorrectly) thought to be
immeasurable
-
Quick and simple methods for measuring any uncertain quantity
-
Interesting examples of where “impossible” measurements had clever solutions
Four Revelations: Findings from 10 Years of
Measuring
IT Risk and Value with Mathematical Methods
Most IT organizations don't measure risk in the same way an
actuary or statistician would and most don't
attempt to build economic models to estimate
even the most "intangible" benefits. This
results in missing some of the most
important trends, risks and metrics in IT
today. Using data from 45 statistical case
studies with a total of over 3,000 variables
and hundreds of tracked forecasts, Hubbard
has found four key revelations that may
profoundly affect what you measure, where
you invest and how you control risks. When
IT investment portfolios are analyzed
quantitatively, four surprising findings
emerge:
-
How much actuarially-sound risk analysis changes IT priorities
-
What the highest-value measurements really are in IT
-
The true cost of scope creep
-
Four factors that best predict success of IT projects
|
 |
 |
 |
 |
 |
|