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Organizational Learning and Organizational Memory 367

Box 11.1
An example: NASA organizational memory

NASA faces a challenge in collecting and maintaining valuable knowledge in its organiza-
tional memory. There has been much publicity over the loss of knowledge with respect
to manned space fl ights. To make matters worse, there was also a recent admission by
NASA that it was no longer able to locate the original recordings of the landing on the
moon; they exist, but the people who know where they are located are long gone from
NASA.
Petch (1998) notes that NASA has forgotten how to put a man on the moon. The Apollo
mission documents — millions of pages of plans — have been reduced to microfi che. But
missing is the critical set of plans. Twenty-fi ve years ago someone threw away the blue-
prints for the Saturn booster, the only rocket with enough thrust to send a manned lunar
payload on its way. The Apollo missions were completed and project directors were
moving offi ces. No other set of Saturn blueprints have been found to date.
The Columbia disaster showed that the lessons learned from the Challenger accident
either went unlearned or were forgotten once learned. NASA has a culture that is resistant
to criticism and to change — no one else could possibly understand what the agency does
. . . only NASA possesses the unique knowledge about how to safely launch people into
space. These attitudes are coupled with ineffective communication, and a tendency to only
accept opinions that agree with their own. The bureaucratic structure kept important
information from reaching engineers and managers alike, stifl ing the spread of critical
information.
Even when documents endure, they can be devoid of meaning, and human context is
often needed. A computerized knowledge base was designed by Dr. Richard Ballard (see
the NASA web site http://km.nasa.gov/) which imposes a rational structure on existing
sources of knowledge, then automates the capture and communication of future text-based
knowledge. This knowledge base was unique in that it used semantic nets and represen-
tational modeling. This knowledge base combines data retention with contextual relation-
ships that provide meaning to information, and may stop the liquidation of knowledge
assets, prevent future knowledge loss, and provide above-the-line profi t opportunities, to
be thought of as group memory or organizational intelligence.