How could innovative DSS have assisted in specific crisis situations?

This Ask Dan! builds upon prior discussions of DSS for crisis planning, response and management. Rather than examine this broad topic from a  general, abstract or theoretical perspective, there is an advantage to  speculating about what might have been possible in specific exemplar  situations.  My sense is that this type of exercise can improve contingency  planning and help us develop more sophisticated DSS.

According to the World Health Organization (WHO) website at URL,  more than 44 countries currently are experiencing a crisis. Not all crises  are of equal magnitude and different computerized decision support is needed  in different types of crisis situations. Grappling with the complexity of generalizing about DSS for crisis, emergency, disaster and hazard situations  has been and is challenging.

According to the WHO website, "People are exposed to a crisis when local and national systems are overwhelmed and are unable to meet their basic needs.  This may be because of a sudden increase in demand (when food and water are  in short supply), or because the institutions that underpin them are weak  (when government and local services collapse because of staff shortage or  lack of funds)."

"Crises can be triggered by:

1. Sudden catastrophic events - like earthquakes, hurricanes and sudden toxic spills.  

2. Complex and continuing emergencies - including over 100 violent conflicts, associated displacement and often dramatic political transformations.  

3. Slow onset processes - such as the gradual breakdown of a country's  social institutions due to economic downturn, populations affected by  chemical poisoning, or the impact of an inflating level of a fatal disease.  

People threatened by crises face heightened risks to their health primarily  as a result of common illness made more dangerous by crisis conditions.  Those who are most vulnerable experience excessive suffering and high death  rates."

The following paragraphs primarily discuss sudden catastropic events like  the Tri-State Tornado, Hurricane Georges, Exxon Valdez oil spill, the Bhopal  gas leak, and the Uberlingen Midair Collision, continuing and recurring  emergencies of various scales of magnitude, and private sector crises.  

In much of the world, recurring emergencies of a small scale like traffic  accidents are managed from centralized dispatch centers with computer-aided  dispatch (CAD) tools and the first responders bring some decision support to  the scene of an incident with them.  There is a significant opportunity for  expanding CAD to include more decision support while also enhancing its  transaction processing role. More mobile decision support for triage and  hazard management (like encountering dangerous chemicals) can also be  developed.  Improved data collection and sharing can also lead to more  timely traffic safety and traffic management decision making at the  management control level in local jurisdictions and enhanced monitoring and  problem identification at more macro level government organizations.

The Firestone Tire recall associated with Ford Explorer crashes demonstrates  a crisis that was mounting slowly for two large multinational companies.  Data collected from traffic accidents was eventually used to demonstrate a  cause and effect link that led the US National Highway Traffic Safety  Administration (NHTSA) to advise the companies involved to issue a recall of  6.5 million tires. Estimates of the impact of the faulty tires are  approximately 250 deaths and more than 3000 catastrophic injuries. Most of  the deaths occurred in accidents involving the Ford Explorer which tended to  rollover when one of its tires had a blow out. How could computerized  decision support have helped? A data-driven DSS at NHTSA might have helped  identify the problem sooner. In July 1998, a State Farm Insurance researcher  had "advised the National Highway Traffic Safety Administration (NHTSA) that  he had found twenty cases of tread failure associated with Firestone tires  dating back to 1992." Bureaucracy, data inadequacy and the disbelief/denial  by some decision makers delayed the identification of the problem and hence  exacerbated a crisis situation at Ford Motor Company and at Bridgestone/ Firestone. Could DSS have helped decision makers at Ford and Bridgestone/ Firestone? Possibly. Managers at both companies had sufficient warning of an  impending crisis to use computerized support to plan a crisis response. If  it been available, managers could have used data at a much earlier stage to  identify the problem and take action to avoid the problem. Business  Intelligence systems would need to become much more sophisticated to help in  this type of situation. Once the recall occurred, communications-driven DSS  including simple bulletin boards could have improved coordination, gathered  feedback and speeded decision-making.

Staying in the transportation sector, the Uberlingen Midair Collision on  July 1, 2002 was a major tragedy. A Boeing 757-200 operating as DHL flight  611 and a Bashkirian Airlines Tupolev TU154 collided in midair over  Uberlingen, Germany. Seventy one people died in the crash. Peter Ladkin  (2004) analyzed the crash in a recent paper and a television documentary was  made about the crash. Failures in the aircraft collision avoidance systems  (decision support systems) and in the overall sociotechnical system led to  the crash. Conceivably better computerized decision support and better  procedures could have avoided this crash. Once the crash occurred, the  crisis was poorly managed and eventually a second tragedy occurred when one  of the Air Traffic Controllers was murdered by a bereaved parent of one of  the Russian children killed on the Bashkirian Airlines flight. In  disasters/crises like this, a document-driven DSS can help track the  needs/responses for victims' families.   

On an even larger scale, a 1984 gas leak in Bhopal, India, was a tragedy  that continues to stimulate strong emotions. In the early hours of December  3, 1984, methyl isocyanate (MIC) gas leaked from the Union Carbide India  Limited (UCIL) plant in Bhopal, India. According to the state government,  approximately 3,800 people died, approximately 40 people experienced  permanent disability, and approximately 2,800 other individuals experienced  partial disabilities. Union Carbide provided immediate and continuing aid to  the victims and set up a process to resolve their claims. All the claims  arising out of the release were settled with the approval of the Supreme  Court of India. Could computerized decision support have helped responders  during the immediate crisis? Probably not.  Computerized decision support  could have assisted in managing, resolving and settling the claims. The goal  must be to avoid this type of catastrophic accident.

When possible, it is also important to avoid environmental accidents and  crises. For example, small oil spills are perhaps unavoidable and DSS can  help first responders in clean up efforts by predicting the consequences of  a spill and in managing the incident. The Exxon Valdez incident demonstrates  the difficulties in responding to large scale spills. "On March 24, 1989,  the Exxon Valdez grounded on Bligh Reef, and spilled nearly 11 million  gallons of oil into the biologically rich waters of Prince William  Sound. ... In the aftermath of the Exxon Valdez incident, the U.S. Congress  passed the Oil Pollution Act of 1990, which required the Coast Guard to  strengthen its regulations on oil tank vessels and oil tank owners and  operators. Today, tank hulls provide better protection against spills  resulting from a similar accident, and communications between vessel  captains and vessel traffic centers have improved to make for safer sailing."  

The Piper Alpha incident presents a different situation for computerized  decision support. "On the evening of July 6, 1988, a fire broke out on the  off-shore oil and gas platform Piper Alpha located in the North Sea. The  fire was uncontrollable and evacuation plans inadequate. 167 men died and 62  men were pulled from the sea." The overwhelming magnitude and suddenness of  incidents like this tragedy creates a sense of helplessness, but perhaps  better monitoring and automated decision systems could have triggered  equipment to avert the tragedy or provide some time for evacuation.   Computerized planning support might help test scenarios for this and similar  situations and develop evacuation plans.

Some hazards can not be avoided like earthquakes, tsunamis, hurricanes,  flooding, wildfires, mudslides, avalanches, and tornados. Longer lasting  natural events like heat waves and droughts require different decision  support. The impact of natural disasters can be very large and civil  emergency and not-for-profit agencies need to invest in many DSS for a wide  range of disasters. For example, the Tri-State Tornado of March 18, 1925 was  the worst tornado disaster in U.S. history. The tornado killed 695 people  and injured 2027. From September 21-30, 1998, Hurricane Georges killed more  than 600 people and the damage estimates for the U.S. including Puerto Rico  were $5.9 billion. Although weather forecasting involves extensive  computerized decision support, more can probably be done to provide  computerized decision support for these situations.  Better early warning  and notification systems can be built and monitored. DSS can support  Incident Management and First Responders and assist in the followup of such  disasters.  Web portals can help gather relief items and notify the public  about facts following a natural disaster. Communications-driven DSS can be  created to inform, notify and consult with individuals, including potential  victims.

We have created a complex public/private infrastructure that can fail and lead to "man-made" disasters. New York City experienced electrical blackouts  in 1965, 1977 and 2003. An earlier Ask Dan! (August 31, 2003) commented on  the 2003 crisis. The Aug. 14, 2003 blackout demonstrated that a failure in  control and decision support systems can have wide-ranging consequences.   U.S. President Bush said the power outages across the Northeast and Midwest  were a "wake-up call" to the antiquated state of the nation's electrical  grid. David Talbot, a senior editor at Technology Review wrote recently that  there are "computer models under development that could help avoid the kind  of cascading blackout that occurred on Aug. 14, 2003 in North America. The  key to this solution is rapidly throwing switches and rerouting power so  that, when necessary, large parts of the grid that are ordinarily  interconnected are quickly broken into isolated 'islands'." Decision  automation and DSS will be built to help limit the consequences of  infrastructure failures.  The First Responders to such crises will continue  to use computerized command centers and better incident management decision  support to reduce the loss of life and property that might result. Chemical  storage facilities create similar problems on a different scale. For an  example, check the DSS case on Geographic Information Systems (GIS) and  plume modeling by Tomaszewski at

Dam collapses have had an important place in the realm of crisis management and dam safety is an ongoing issue. The St. Francis Dam Flood in California  on March 12, 1928 killed 306 people. The failure of the Teton Dam in  southeastern Idaho resulted in the loss of 11 lives and millions of dollars  in property damage. In February 2005, a newly built dam collapsed under  heavy rain waters in southwestern Pakistan killing at least 135 people. In  China in August 1975, the worst dam disaster occurred. The Chinese called  it "Chu Jiaozi" (The river dragon has come!). Altogether 62 dams broke in  this incident. Downstream the dikes and flood diversion projects could not  resist the flood of water from the initial dam collapse. The flood spread  over more than a million hectares of farm land throughout 29 counties and  municipalities. Eleven million people throughout the region were severely  affected and more than 85 thousand died as a result of the dam failures.  According to Thayer Watkins (San Jose State economist) "there was little or no time for warnings".

What about terrorism and the resulting crises? Implementing structural  solutions to reduce risks when possible are better than hoping that improved computerized decision support will identify and avoid terrorist threats. My  Ask Dan! column of September 23, 2001 briefly discussed whether DSS and  decision support technologies can help reduce the threat of terrorism. The  United States has changed as a result of the 9/11 attacks (see www.9- More than 2,600 people died at the World Trade Center;  125 died at the Pentagon; 256 died on the four planes. The death toll  surpassed that at Pearl Harbor in December 1941. The case study at  DSSResources.COM by Matt Walton (2003) documents DSS used in response to the  9/11 crisis. During the 1970s, many terrorist attacks occurred in Western  Europe. The Baader-Meinhof and the Red Army Faction (West Germany), the Red  Brigade (Italy) and the Action Directe (France) created an ongoing terrorist  threat. Improved Law Enforcement databases and improved communications  helped reduce that threat and ended an ongoing crisis.

The number of crisis exemplars is large and diverse, but I'll end with only  three more: public health crises, organizational crises of leadership and  succession and large scale financial crises.

Public health crises have been a problem for humankind for thousands of  years. Plagues and epidemics have ravaged nations and communities.  Collecting data has helped monitor the spread of disease and identify the  causes of such events. Computerized decision support has taken on an  increasing role in this crisis management and response domain. Severe Acute  Respiratory Syndrome (SARS), Mad Cow Disease, and Bird Flu are modern  pandemics. These crises have killed people, hurt trade and led to the  destruction of millions of animals. Could DSS have avoided these crises? No,  but the goal of new DSS must be to help decision-makers identify outbreaks  sooner and respond faster and more appropriately.

Leaders die suddenly.  Often such events create organizational or national crises.  For example, in 2004 there were two sudden succession crises at  McDonald's ( On April 20, 2004 McDonald's Chairman and  CEO Jim Cantalupo, 60, died of an apparent heart attack. His successor  Charlie Bell was quickly appointed. On November 23, 2004, a second abrupt  succession crisis occurred at McDonald's. President and Chief Executive  Charlie Bell resigned to battle colorectal cancer (Wall Street Journal). On  January 16, 2005, Charlie Bell died of cancer. He was 44. Jim Skinner is the  current CEO of McDonald's. Succession plans, computerized staffing support  and crisis response teams can help in this type of situation, but is there a  need for new type of DSS? Probably not.  But a good Web site can help a  crisis response team provide information to shareholders and other  stakeholders.

Finally, financial crises occur. Depressions, financial collapses,  bankruptcies and loan defaults occur.  Risk management is an ongoing issue  in banks and in financial regulatory organizations. Could DSS have helped  avoid the 1929 Stock Market crash in the U.S.? One can only speculate based  upon the 1989 crash and other recent financial debacles that DSS can both  compound financial meltdowns and help reverse them. Let's begin with the  Long-Term Capital Management (LTCM) crisis of 1998.  The LTCM hedge fund was  highly leveraged and regulators had to bail out the banks that had lent  money to the fund managers. The Financial Times reported LTCM had built a  total market exposure (in credit) of US$200 billion. "LTCM's notional gross  market position, adding together the value of all outstanding derivative and  other financial contracts, could be several times that" (28 September 1998).  According to some estimates, the gross value of LTCM's contracts exceeded $1  trillion. "The proximate cause for LTCM's debacle was Russia's default on  its government obligations." A case study about LTCM is on the Web at Computers and information technologies have created decision  support capabilities for implementing hedging using derivatives. DSS and  information technology are actually creating some crises. According to the  case study, some lessons learned include: 1) "sophisticated financial models  are subject to model risk and parameter risk, and should therefore be stress- tested and tempered with judgement" and 2) financial institutions must  aggregate exposures to common risk factors. Both lessons learned suggest  better computerized decision support is needed by various participants in  the making and regulating of financial markets.  The complexity of modern  financial transactions means that more DSS are needed to manage the risks  associated with lending operations and credit decision making. Check the Ask  Dan! of July 18, 2004 titled "How can DSS help implement Basel II?"

Other crisis exemplars such as computer failures, computer virus attacks, hazardous material spills, product tampering and political crises like the overthrow of a government or the Cuban Missile Crisis may be discussed in  a future Ask Dan! column.

What can we conclude? Only some emergencies and crises require or will benefit from elaborate computerized decision support. DSS are not especially  relevant, helpful or useful in some crisis situations. We need a typology of  crisis situations to analyze DSS needs and gaps for crisis planning,  response and management. We need to critically examine who "owns" the crisis  related DSS capabilities and how such capabilities should be funded and  maintained.  Also we need to critically assess what DSS are needed by  public sector first responders, by both private and not-for-profit sector organizations, and by national and international government agencies.  


Bhopal Website maintained by Union Carbide Corporation Bhopal Information Center at .

Firestone Tire Recall Legal Information Center, .

Ladkin, P. B., "Causal Analysis of the ACAS/TCAS  Sociotechnical System," 9th Australian Workshop on Safety  Related Programmable Systems (SCS'04), Brisbane, 2004, URL .

LTCM-Long-Term Capital Management case,  .

Power, D., "Can DSS and Decision Support technologies help reduce the  threat of terrorism?", DSS News, Vol. 2, No. 20, September 23, 2001.

Power, D., "Can DSS/IS/IT improve the Incident Command System? What needs  can DSS meet?", DSS News, Vol. 6, No. 8, March 27, 2005.

Power, D., "How can computerized decision support help in crisis situations?", DSS News, Vol. 4, No. 18, August 31, 2003 

Power, D., "How can DSS help implement Basel II?", DSS News, Vol. 5,  No. 15, July 18, 2004 

Power, D., "How can DSS help in crisis planning, response and management?",  DSS News, Vol. 6, No. 6, February 27, 2005 

Tomaszewski, B., "Erie County Emergency Response and Planning Application  Performs Plume Modeling", posted at DSSResources.COM March 6, 2005.

US Environmental Protection Agency, Exxon Valdez case, .

Walton, Matt S., III, "Rebuilding an Emergency Operations Center for NYC  following 9/11", 2003, posted at DSSResources.COM September 11, 2003.

Watkins, T., "The Catastrophic Dam Failures in China in August 1975," at .

Yi Si, "The World's Most Catastrophic Dam Failures: The August 1975 Collapse  of the Banqiao and Shimantan Dams," in Dai Qing, The River Dragon Has Come!,  M.E. Sharpe, New York, 1998 (cited by Watkins).

The above response is from Power, D., How could innovative DSS have assisted in specific crisis situations? DSS News, Vol. 6, No. 9, April 10, 2005.

Last update: 2005-08-16 22:03
Author: Daniel Power

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