A Toolkit for Deployable Best Practices

Award Information
Agency:
Department of Defense
Branch
Office of the Secretary of Defense
Amount:
$99,991.00
Award Year:
2009
Program:
STTR
Phase:
Phase I
Contract:
W9132T-09-C-0018
Award Id:
90369
Agency Tracking Number:
O08A-002-2029
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
454 Pine Street, Suite 1A, Williamsport, PA, 17701
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
128516114
Principal Investigator:
ToddGriffith
President & CTO
(570) 329-0251
tgriffith@discoverymachine.com
Business Contact:
ToddGriffith
President & CTO
(570) 329-0251
tgriffith@discoverymachine.com
Research Institute:
Pennsylvania State University
Robert Walter
P.O. Box 30
North Atherton Street
State College, PA, 16804
(814) 863-8876
Nonprofit college or university
Abstract
Discovery Machine, Inc. is partnered with Pennsylvania State University to produce a best practices capture system that goes beyond the storage and dissemination of lessons learned. The proposed system will leverage warfighters' specific knowledge as deployable knowledge assets. These knowledge assets will be executable best practices that can be embedded in job aids and training systems. The lack of true best practices capture prevents the military from both identifying many useful standard processes but also from improving upon them over time. The problem is that bringing best practices to the warfighter requires the capture of real expertise. The tacit knowledge or key person know-how found in the heads of experienced individuals. To capture this expertise requires a methodology and technology based in cognition. It requires the military to reexamine what knowledge is and how to make it an asset. This proposal describes how to capture best practices and turn them into knowledge assets through a series of stages. Each stage leverages knowledge to provide value and each stage requires that real knowledge be captured with the intent to deploy that knowledge. The stages are described in the following sections: capture, collaborate, automate, optimize, embed and network.

* information listed above is at the time of submission.

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