Knowledge management has never been so clearly a superior investment as it is now in this permafrost economy.
Five years ago, a raft of vendors despoiled the term KM by flying its flag above everything from search utilities to document management apps to "push" clients. Before KM had even established itself in the enterprise, marketing gibberish had rendered it meaningless.
But now things are different, and it's time to re-examine preconceived notions about KM and its role in the enterprise. Vendors are using technological advancements in strategic tools such as XML and Web services to bolster KM, and through re-imaginations such as these, KM -- the real thing, not the label -- has matured. With budgets tight, this maturity may pay large dividends for KM vendors and implementers alike.
"The value of knowledge management and all it encompasses is far more valuable in these economic conditions than when project investment dollars were dropping off trees," says Albert Ray Edwards, director of the capital markets group at Cap Gemini Ernst & Young. "The value of effective reuse of what we know, especially in the financial services market, is just so much greater now."
Here's the catch: Whereas technology has made incremental advances, deployment strategies and organisational behaviour have not. KM must be approached as a way of doing business, one enabled by properly-used technology. In fact, organisations participating in the employee slash-and-burn wave -- some out of necessity, some just for blood sport -- find it more difficult to execute KM strategies and to reap the benefits right at the point where it would have yielded stratospheric returns. For organisations with the courage to take different approaches to difficult times, however, the payback can be significant.
According to Edwards, new approaches to KM are making sense for CGEY's financial clients, such as American Express, CitiBank, Merrill Lynch and JP Morgan Chase. KM brings together two disparate categories: all the data about potential investment choices, what Edwards calls "content"; and all the practical knowledge about how and when to use that content, that is, what resides in experts' heads. According to Edwards, the real value comes when you blend technology with people.
The inability to mesh stored knowledge with human expertise is why so many attempted KM projects have failed, souring IT on the idea of KM, according to Bob Bauer, CTO of Xerox Global Services.
"The singular focus that powered IT growth was [that] IT spent money by arguing there was all this data out there: 'Let's get it patterned and manage it better, and that will give us the ability to make better decisions,' " Bauer explains. "But they got lost because they got focused on trying to create transactions of data with data when the fact is that any decision process or action based on valuable transactions involves people. Someone has to make a decision, whether it's a tactical choice or a strategic decision."
"Data in these systems can only be made actionable by people. That's the genesis of a successful IT view," Bauer adds.
One of CGE&Y's high-payback KM projects is simple in concept but upends an IT behaviour norm that is based on a tacit assumption: Low-cost work is the easiest to commodify so that's what you target for automation. But that approach ends up replacing the smallest amount of your total costs. Instead, CGE&Y is targeting high-cost work bought by the largest capital-markets firm on Wall Street by developing resources to reuse expertise gained from outside counsel.
In this case, CGE&Y's client's legal department frequently uses outside counsel for a myriad of projects. The outside counsel delivers the work, but often, a few months later a similar situation comes up in which already-purchased work would have great value if workers knew it was at their disposal. The system CGE&Y is putting together will let the client find similar cases and find sources both within the company and among outside counsel who have expertise in the specific topic at hand.
"[The system] lets them pull together the expertise, the recipe, the content and the people they need very quickly," Edwards explains. By reducing the need for outside-counsel hours, the KM-based system cuts costs for the client.
The technologies used for that project could have been cobbled together five years ago, but with the maturity of KM wares and an increased familiarity with the tenets of sound KM practice, CGE&Y's present-day implementation better realises the potential of these technologies.
Meeting KM demands
Other recent KM initiatives are powered by technologies that have recently become more solid and widely-used. The rise of XML, for example, may help ease the two most challenging aspects of initiating a KM implementation: how best to collect knowledge and how best to search what has been collected.
XML, which aids tremendously in sorting collected data, is a key component of products built by ClearForest, a developer of what it calls unstructured data management software for BI (business intelligence) applications. One of its products, ClearTag, scans unstructured documents using a pattern recognition engine and applies XML tags that plumb the context of the document, recognising, for example, the who, what, when, and where described in the unstructured text, as well as how those facts are connected.
"A scheme without XML could achieve auto-tagging, but you wouldn't have the integration with external documents that have XML tags," explains ClearForest CEO BarakPridor. To integrate without XML would require so much human intervention that it would likely be seen as a deal-breaker, leaving what Xerox's Bauer calls the "digital landfill" unmined.
Pridor notes that recognition technology has also improved during the past five years, making entire categories of knowledge-enabling products more useful and certain kinds of applications incrementally more logical for deploying KM initiatives. Improved pattern recognition has boosted the value of desktop research consoles, enterprise analysis products such as ClearForest and Lotus' Discovery Server, and search capabilities of offerings such as those from Autonomy, according to Dan Rasmus, vice president of Giga Information Group. It has also advanced expertise location systems from companies such as AskMe, Tacit and Kamoon.
AskMe highlighted the value of this technology by improving the searching of stored knowledge by implementing a tipping factor in its Enterprise 6.7 software, released last month. The program is now integrated with Microsoft Office applications, allowing an end-user to highlight a term on a Web page or in a spreadsheet that he or she doesn't understand, bring up a definition and expertise community window, and find both quick information and avenues for gaining a richer understanding of the subject matter, according to Stephen Pao, vice president of AskMe.
Stronger integration is also a key factor in the changes made to Open Text's newest knowledge environments, including LiveLink Team Collaboration Suite. According to Anik Ganguly, executive VP of Open Text, the aim of the integration is to break down what he believes has been the single toughest barrier to successful KM deployments: the input barrier.
"People love the idea of going to a system and getting everything they want easily, but if you ask them to do a shred of input work, they recoil in horror," Ganguly says. Although LiveLink has always had collaborative spaces, its newly integrated electronic whiteboard application not only encourages side-channel conversations but also documents questions and answers during a session and enables LiveLink to capture that data for later access. "It's all in context," Ganguly adds. "No one has to do any work to get the knowledge stored."
Knowledge for the future
Some technologies not yet in the limelight promise to further shake up enterprise notions of KM by making it easier to collect information and to get users to use KM systems. Advances in all four functions that make up a KM system -- gathering, organising, refining and distributing knowledge -- are on the horizon.
For gathering knowledge, the proliferation of voice-mining applications is crucial to the future of KM. Industry experts estimate that three-quarters of all knowledge crucial to a company's efforts is transmitted verbally; virtually none of this knowledge has been captured for use in KM implementations.
On the organisation front, pattern-recognition efforts are expected to improve. Veterans such as ClearVision and Autonomy continue to grind away at the limits of binary code, and newcomers such as Inxight Software are likely to tackle data-organisation problems at a slightly different angle.
Refining advances are being set up by a combination of better pattern recognition and continued XML adoption, according to Xerox's Bauer. XML can be applied across an enterprise to create a vast network of data and relationships to be mined for purposes such as fine-tuning workflows in response to custom demands.
Now that KM-enabling technologies are being worked into a variety of applications, companies have the tools available to successfully build a KM strategy and thereby squeeze more value out of the expertise they have already in place. The challenge, however, is to inspire enterprises to make the workflow and process changes critical to KM success and to invest in the benefits of KM at a time when budgets remain tight.
"Too many executives are in survival mode, not investing anything in adding value," Xerox's Bauer says.
The irony is that, by not investing, executives may hinder their company's chances of escaping the permafrost.
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