by Arik Johnson
Ryan Jacobean has two missions in life as competitive intelligence (CI) director of a multinational financial services company. Monitor the competition for changes in direction. And fulfill the immediate needs of his superiors and customers when they ask for specific competitive data. The trouble he's having is controlling the flow of competitive information through the organization - my suggestion is that, he shouldn't try to "control" it, rather provide a guiding hand in how to use it more effectively. With many users demanding more immediate attention for simpler forms of CI, he's begun migrating many of the "news" elements of competitive research (newsfeed, broadcast of key events in the industry, etc.) off of the paper he's accustomed to and onto the intranet for delivery. "Moving to intranet delivery with our KM system gives users a customized, self-service CI feed buffet-style", he says. "But we still provide competitive analysis on project requests."
This dichotomy characterizes the complex nature of modern CI. On the one hand, the pace of constant change in markets and within firms makes it necessary for companies to continuously leverage new knowledge they learn about competitors, while they struggle to fulfill research requests coming from front-line policy-makers and field personnel that need mission-critical CI to execute more immediate business goals. This continuum of information-gathering creates a CI process that at once must capture intelligence as it happens and integrate this "fresh" intel with existing repositories of CI that might be months or even years old. These two very different processes form the core of how organizations act on the competitive intelligence that is made available to the firm and can be described in two discrete forms of CI workflow: Environmental Scanning and Ad Hoc Research.
Since many new CI units are chartered during times of strife, CI managers often begin by attacking a small number of event-driven research objectives with very short deadlines and great importance to the long-term health of the firm. Here's an example: a new competitor enters the market with a lower price point and marginal difference in quality -- presenting a competitive threat to the firm's established line of business. Management will often find its strategy lacking for competitor intelligence with which to react to this new entrant and "draft" a sales manager to head up the CI effort. Usually the project is accompanied by the absurdly vague mission of "finding out everything there is to know about...." the research target. The results of such a project tend to be highly speculative and often out-of-date by the time the project is complete. Furthermore, the concept of reacting to competitor initiatives becomes troublesome in terms of strategy and planning - the goal is to anticipate. If the CI unit is lucky enough to survive this first, scattershot project, this "Ad Hoc" quality of initial event-driven research eventually becomes much more seamlessly integrated with the CI objectives of the organization. Once customers learn how make requests that get results and processes are developed to manage CI activities more appropriately, the CI unit beings to learn the subtleties of its sister discipline, Environmental Scanning.
Environmental scanning is usually the next phase of development for the sophomore competitive intelligence unit. This process involves regular, ongoing monitoring of direct competitors and their initiatives, so as to avoid surprises, as well as latent competitors (those who might backwards- or forwards-integrate to enter the market directly) and parallel competitors (those with replacement or substitute products or services). Environmental scanning also involves monitoring other central issues important to the firm that might either present new opportunities or threaten the firm's position in the marketplace. This includes topics such as federal or state legislation and regulation, technological advances made outside the industry or investments made by the various industry organizations associated with the sector.
However, environmental scanning does not necessarily turn up immediately useful nuggets of competitive intelligence. For example, a pharmaceuticals firm might learn that its competitor has recently cited previous technologies in a patent application filed in Europe (patent applications are public documents in Europe, unlike the United States), while, at the same time, they've begun importing particular organic compounds from Brazil (available in public records as well) and have begun hiring scientists with specialties in a particular field of antibiotic drug approval. None of these pieces of competitor information means much on its own; it is the synthesis of the various bits of information that might lead the pharmaceuticals firm to begin drawing some conclusions about where their competitor is headed - perhaps foreshadowing the introduction of a new antibiotic compound some years hence.
This is very much the nature of scanning one's competitive environment -- bringing together the parts of an equation that represents meaningful "foreknowledge" of where a competitor might be headed in the future, rather than where they've already been. The firm that begins to integrate the workflow processes of ad hoc, event-driven research with those of environmental scanning begins to realize the true power of CI. This involves nothing less than the ability to predict the probably futures with which a competitor will behave and formulate countervailing strategies to beat them to new opportunities.
Once a company has regularized the scanning and ad hoc processes with internal customers, it can begin to automate collection of primary and secondary research sources and delivery mechanisms to end-users. Ad hoc research is rarely an automated or self-service kind of procedure. By definition, ad hoc research is event-driven in terms of specifically defining the objectives of the research request and communicating interim results of the research to the customer as the project unfolds. Ad hoc projects benefit a great deal from being as diligent as possible with customers, even to the point of knowing "why" the research is sought after by the customer in order to add context and give clues to the analyst about the best techniques for collection. So how can ad hoc CI research be applied to a self-service context?
Self-service research is best applied to locating ad hoc CI that has already been conducted or by connecting the CI consumer with a subject-matter expert that may have either made such a request or conducted research of their own in the past. This way, ad hoc requests can be fulfilled by existing documents on the network that have already been authored or by the authors of those documents themselves. Many modern KM systems - PC Docs/Fulcrum, Dataware, Lotus among others - help users identify subject matter experts based upon the documents that others have authored. For example, a company seeking out an expert on "mergers and acquisitions activity in the financial services sector in Southeast Asia" might simply find the author of any number of topically similar documents and ask them the questions they seek answered. In this context, CI has left the CI unit altogether and gone to the periphery, usually accelerating the pace of delivery and improving its "actionability". When CI users are able to connect with one another rather than using the CI unit as a broker, we begin to realize the true value of competitive knowledge. As they begin to materialize, these internal, de facto subject-matter experts can also become very important CI sources for the CI analyst as well.
Environmental scanning activities are much better suited to self-service or automated methods of delivery. Because a CI consumer is now able to search against a lexicon of similar keywords to isolate density of terms within a document or digital source, the consumer can automate the process of retrieving updates on their own. Or, the CI unit can customize a delivery profile for news items they discover during their scanning for delivery in a daily email message, on a personal homepage or using push technology.
One of the most exciting areas of change in the self-service and automation of CI comes in the form of intelligence agents. Intelligent agents search for new competitor information on a particular range of subject matter and deliver it to users as it appears, rather than hoping the user will perform a fresh search on their own. While simple agent-like effects can be built into search engines, like adding a date field to the search engine which will run new searches, the most exciting agent technology detects changes in documents and alerts users to those changes when they appear. For example, there are many free services which will track changes to Web sites and deliver an email message to users when a change of any kind is detected. While this service has applications in CI, the database-driven nature of modern, dynamic Web sites make such bookmarks far less appealing as a means of defining routine searches. Contemporary intelligent agents unify access to multiple data repositories - groupware apps, the Internet, RDBMS, legacy systems and files in departmental servers. Users are also presented with tightly controlled resource access - another big CI concern - not receiving search results for documents they don't already have access to.
As today's KM technology continues to evolve, we will see more proliferation of CI self-service applications, especially in environmental scanning activities, as CI units continue to strive towards giving meaning to competitor intelligence rather than just turning over information to customers. And, as they should, customers will likewise demand greater self-service capabilities from their CI units with higher quality output in their analysis.
Arik R. Johnson is Managing Director of the Competitive Intelligence (CI) outsourcing & support bureau Aurora WDC. Learn more about Arik at his firm's Web site www.AuroraWDC.com/arik.htm.