By G.Scott Erickson; Helen Rothberg
ISBN-10: 1137035323
ISBN-13: 9781137035325
ISBN-10: 1349345458
ISBN-13: 9781349345458
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Extra info for Intelligence in Action: Strategically Managing Knowledge Assets
Sample text
Zynga Complaint, pp. 2–3) What is particularly interesting about this episode is what it tells us about the kinds of knowledge valued in this industry. Based on our data, these firms and competitors like Electronic Arts and Activision Blizzard fall squarely into the high KM, high CI SPF 45 category. They are included in SIC 7372 as the guts of the product offering are software-based. As this case and our discussion will make clear, however, there is a lot going on here in terms of knowledge development and protection.
To do so, of course, one must measure both KM and CI and try to determine if a correlation exists with financial performance. We discussed our development of metrics in an earlier section of this chapter, and that has some insights on the connection of KM to financial performance. But the field has been basically wide open in terms of the variety or measures. Many, many exist (Tan, Plowman, and Hancock 2007) including wide-view techniques such as Tobin’s q (previously discussed) and firm-specific techniques such as the Balanced Scorecard (Kaplan and Norton 1992) and Skandia Navigator (Edvinsson and Malone 1997), Preparing for Launch 39 both also mentioned earlier.
The distinction is important in that organizations looking to better leverage their knowledge assets will try to identify and employ them. In some ways, this is easier with explicit knowledge (the digitization helps) though conversion from tacit is not always easy or even possible. Further, there are specific knowledge management techniques for all kinds of knowledge, so understanding the nature of the assets to be managed is critical to using the right tools (Boisot 1995, Choi and Lee 2003, Schulz and Jobe 2001).
Intelligence in Action: Strategically Managing Knowledge Assets by G.Scott Erickson; Helen Rothberg
by Jason
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