Putting knowledge to work: The intelligent learning organization

Since Senge\u27s (1990) seminal work The Fifth Discipline , various styles of learning organizations have evolved that employ cross-functional teams and double-loop processes (Argyris 1992) to manage knowledge assets and enhance learning. There is some empirical support that learning organizations are more adept at knowledge transfer, facilitating problem solving and augmenting strong financial performance over time (e.g. Goh & Ryan 2008). To be an essential strategic tool, KM needs to advance beyond software or process and find its place in an organization\u27s design. KM\u27s apex of value resides in its potential to provide decision makers with what they need to know when they need to know it to drive optimal actions. KM also needs to collect what has been learned from such actions and create knowledge lesson stocks. Ultimately, all forms of knowledge assets; intellectual capital, big data and competitive analytics, needs to fuel actionable intelligence to advantage decisions that can impact performance. And, they need to be able to feed back to the knowledge system what has been gleaned from different outcomes. Single loop use of knowledge needs to become a series of double loops. In this kinetic form, KM can become a unique organizational competency. People, teams, systems, cultures and process need a learning architecture to facilitate potentially complex engagements. This discussion presents such a design: the Intelligent Learning Organization. With roots in early Fifth Discipline, double-loop learning and competitive intelligence systems, it is an integrative form that unites knowledge sources and analytics, knowing, thinking and doing, to deliberately guide the firm as it impacts and is impacted by external forces