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Dashboard spy

Dashboard spy gallery of mangement dashboards and consoles full of KPI
(Key performance indicators).
Update 2006 Dec.: Moved to enterprise-dashboard.com.

Ed Tufte adds,

Edward Tufte

(1) See Peter Drucker's new book, The Essential Drucker,
for a thoughtful chapter on "the information executives
need today." That is, you should start by considering the
intellectual problems that the displays are supposed to
help with. The point of information displays is to assist
thinking; therefore, ask first of all: What are the thinking
tasks that the displays are supposed to help with?

(2) It is essential to build in systematic checks of data
quality into the display and analysis system. For example,
good checks of the data on revenue recognition must be
made, given the strong incentives for premature recognition.
Beware, in management data, of what statisticians call
"sampling to please"--selecting, sorting, fudging, choosing
data so as to please management. Sampling to please occurs,
for example, when the outflow from a polluting factory into
the Hudson River is measured by dipping the sampling
test-tube into the cleaner rather than the dirtier effluent.

(3) For information displays for management, avoid
heavy-breathing metaphors such as the mission control
center, the strategic air command, the cockpit, the dashboard,
or Star Trek. As Peter Drucker once said, good management
is boring. If you want excitement, don't go to a good
management information system.

Simple designs showing high-resolution data, well-labelled
information in tables and graphics will do just fine. One model
might be the medical interface in Visual Explanations (pages
110-111) and the articles by Seth Powsner and me cited there.

A model for tables might be the supertable, shown in The
Visual Display of Quantitative Information
, p. 179. More generally,
see chapter 9 of The Visul Display of Quantitative Information. The
displays should often be accompanied by annotation, details from
the field, and othersupplements.

"Sparklines" show high-resolution data and also work to reduce
the recency bias prevalent in data analysis and decision-making.
More on that in the next book, Beautiful Evidence, probably out by
2003, I do hope.


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