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When participants at the April 2004 E-Gov Knowledge Management Conference reflect on the event, they must think we were truly prescient. It was late 2003 when we were planning the conference. I had committed to teaching a tutorial on building knowledge management environments. While looking for a case study for discussion, I read some of the headlines coming out of Asia regarding the avian flu. After noticing these stories, I decided to pick a potential avian flu crisis as the case study for our tutorial. In February the Washington Post carried many similar stories like “Bird Flu Strain Is Discovered in Chicken Flock in Delaware” and “Maryland Bans Live Poultry Sales as a Precaution.”
This was long before the first cases of transmission to humans appeared in Thailand and Vietnam. Once this happened, the specter of human-to-human transmission started to emerge. When the threat of a pandemic began capturing national attention and the problems of a vaccine—or lack thereof—arose, it seemed to be old news to our group. Clearly, we had been examining this problem at least a year earlier.
The process of the case study is interesting because it mimicked what might happen in real life situations. For the tutorial’s purposes we created a fictitious government organization called the National Emergency Center for Knowledge Sharing (NECKS), which was responsible for “disseminating accurate and timely knowledge to all agencies involved in addressing emergency situations.” NECKS’ logo—pun intended—was a chicken with its neck outstretched in apparent expectation of the axe; and its motto was “Saving our necks together by sharing our common knowledge.”
The fictitious scenario we presented was straightforward. Three cases of avian flu in humans appeared in Delaware. This generated significant concern at both the state and local levels. The Centers for Disease Control (CDC) was informed and the Secretary of Health and Human Services briefed the President. Key questions were asked and answers were needed to address the problem and take an appropriate course of action. Consequently, NECKS was ordered to assist in generating relevant knowledge for the agencies involved in dealing with the actual emergency.
The exercise began with a mock phone call from the White House to NECKS where the director answers, “Yes, Mr. President. We’ll get right on it.” The “President” has just asked a series of critical questions that demand answers, in the form of business intelligence, in order to determine a course of action:
- What do we know about avian flu?
- Who are the experts?
- What populations are at-risk?
- Where are they?
- What measures need to be taken?
- What might be the economic impact?
- How do we identify and contact the necessary authorities in the at-risk locations?
- What do we tell them?
The first module basically set the stage. Many questions had to be asked. What is avian flu? What do we know about it? Is there a vaccine? Who is affected? There are underlying themes of tacit knowledge, knowledge spaces, content management, concept searches, taxonomies and others. We introduced an “Avian Flu Knowledge Space” that had been developed by using the web, as well as large agricultural and health care research sources. This also allowed us to demonstrate the use of search engines, federated searches and concept search tools to start navigating the knowledge space.
The second module focused on finding the sources of expertise on “avian flu.” Who are the experts? Where are they? What are the criteria that qualify them as experts? Their identification, vetting, contacting and collaboration included themes of communities of practice, best practices and collaboration. These allowed us to show the results of queries to the avian-flu knowledge space; identify people involved with the issue; establish qualifying criteria for being deemed as “expert” (i.e., authors, speakers at relevant conferences, faculty teaching related topics, researchers in relevant firms); develop a list of expert resources; set up a collaboration vehicle; and even show a video clip of one expert addressing the topic.
Next, we moved on to address the question: what populations are at risk? After asking this, there were the logical follow-up questions to consider: Where are they? What are their characteristics? This again allowed us to use query tools, document navigators, summarizers and begin introducing geospatial processing to address the question of location, the where dimension. We were able to introduce the concept of the data mart, OLAP tools and queries and visualization techniques as we built a small data mart with data from both Census 2000 and the National Agricultural Census. We did this to show statistics on poultry production by county and the location of chicken farms. We were also able to compute ratios of chicken per person in high-density counties.
This allowed us to project these queries on maps to identify the location of populations at risk by capturing business intelligence about poultry industry labor statistics, its density and where there was a high concentration in these locations of very young and very old people, since these were the populations most vulnerable to the virus.
What is the economic impact? This was the next question to tackle. Identifying the economic impact followed from analyzing the same sources and available information. We looked at demographics, labor statistics, poultry industry figures and inventory of farms. After completing this, we extrapolated the potential economic impact as reflected in the gross domestic product of a county or state if there was a need to undertake a massive destruction of poultry. Again, visualization on maps was very helpful. This showed queries, such as income from sales of chicken or the median income in affected counties.
Then, we addressed the question: How do we identify and contact the necessary authorities in the at-risk locations? This raised a number of additional related questions: Who are they? Where are they? What do we tell them? How do we tell it to them? How do we get ready to assist? These questions, in turn, introduced themes like leadership, storytelling, learning, collaboration and security. Here we relied on the excellent resource provided by the federal, state and local editions of the Yellow Book (Leadership Directories) to quickly prepare contact lists with names, titles, telephones, and electronic as well as postal addresses.
Lastly, we were ready to take action. The crux of the matter was determining what measures needed to be taken. And these, of course, come in several categories, such as medical, economic, security, transportation, security, communications and press relations, among others. As the need to work with local authorities and the themes of leadership and lessons learned emerge, we again needed to demonstrate knowledge management tools. This had to be done to investigate what was done in other countries/incidents, obtain recommendations from experts and identify resource sites on the Internet.
Essentially, the avian flu provided us with an excellent case study for a business intelligence tutorial. Hopefully, we have learned enough to help when we are actually confronted with a real pandemic.
Dr. Barquin is the President of Barquin International, a consulting firm, since 1994. He specializes in developing information systems strategies, particularly data warehousing, customer relationship management, business intelligence and knowledge management, for public and private sector enterprises. He has consulted for the U.S. Military, many government agencies and international governments and corporations.
Dr. Barquin is a member of the E-Gov (Electronic Government) Advisory Board, and chair of its knowledge management conference series; member of the Digital Government Institute Advisory Board; and has been the Program Chair for E-Government and Knowledge Management programs at the Brookings Institution. He was also the co-founder and first president of The Data Warehousing Institute, and president of the Computer Ethics Institute. His PhD is from MIT. Dr. Barquin can be reached at firstname.lastname@example.org.
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