Identifying and resolving organizational inefficiencies often requires hiring external consultants. The capabilities of collaborative crowdsourcing, however, provide an opportunity for organizations to leverage their own employees to achieve this task. We propose the development of GECKOS (Generating Employee Crowdsourced Knowledge for Organizational Solutions), a tool that integrates a wide range of algorithmic capabilities to identify and resolve organizational inefficiencies efficiently and effectively. GECKOS brings together expertise in crowdsourcing algorithm development, distributed team performance, collaborative team motivation, decision making, and human-automation design. It will provide organizations with a continuous improvement capability that incorporates contributions and insights across all organizational levels and units. Consideration of anonymity, motivation, team and task design, data aggregation, and other factors will be critical to the design of GECKOS, as will the experimental plan and associated metrics to validate its effectiveness. Cognitive analyses and human-centered principles will guide the design of collaborative workspaces and rulesets governing interactions to promote collaboration.
Benefit: GECKOS will provide several tangible and marketable benefits over traditional, external consulting approaches, including continuous analysis capability, lower cost, and a more informed picture of organizational inefficiencies and solutions across levels and units. These features have significant appeal to our candidate organizational partners, and likely many others, as well as to the military organizations for whom we currently conduct organizational analyses. These represent tangible and immediate customers.
Keywords: hierarchical organizations, hierarchical organizations, Algorithms, Human-Machine Teaming, organizational inefficiencies, Decision Making, collaborative crowdsourcing, Crowdsourcing, Distributed Teams
