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== [[Strategic management schools|Strategic management schools: prediction]]==
== [[Strategic management schools|Strategic management schools: prediction]]==
== Assembly ==
== [[Assembly]] ==
A crisis is described by a number of key aspects.  See also: [[From Crisis Prone to Crisis Prepared: A Framework for Crisis Management]]
* High magnitude
* Require immediate attention
* Element of surprise
* Need to take action
* Out of a company's direct control
The element of surprise is important in relation to prediction. If something is predictable it means that there is no element of surprise. The question leading from this: can you predict a crisis? It sounds contrary since a crisis is a situation that is unexpected. Black swans are even more unpredictable since they are sudden and unexpected. Greater element of surprise. What we possibly can predict is certain future changes in an environment that might if no action are taken might evolve into a crisis. The degree to which we can predict future events in an environment depends on the properties of an environment. The environment a company operates in dictates which management school principles might work. The more uncertain an environment the more the adaptive school will prevail, since the future is uncertain, the environment to complex and uncertain to understand. Adaptive school lends to a mode of monitoring and reacting effectively on important changes in the environment.  An environment that is more stable, more linear with less unexpected events over time  lends itself to prediction based on the understanding of variables in the environment. In these environments planning school could be useful to plan strategically decisions. Transformative and Control are relatively the same as Adaptive and Transformative although their theory underlines the importance a company has on the environment variables. Globalization, trends towards more efficiency and increased integration however lead to a more complex world, increasing variable dependency.
The level of prediction and the management mode are dependent on the environment a company operates in. Understanding and collecting important environment variables is important for any management mode whether used for prediction or for decisions. Adaptive approches are more likely to gain popularity because of the increase of complexity and non linearity in environments.
Extra information on prediction efforts from big datasets:
= Examples, Lessons and Curiosities =
= Examples, Lessons and Curiosities =

Revision as of 07:47, 8 June 2012

Introduction to the subject

How can enterprises use information to be prepared when a crisis comes?
Now-a-days enterprises are gifted with powerful technology, however, they are also damned with a fast-pace constant changing market. The whole market evolution and product cycle are faster, new technologies overcome old technologies almost in a monthly basis. It is very hard for a company to keep on the top of the edge, without falling into disaster.

Companies need then, to be able to understand the market, learn it and - most importantly - react to it. The extra mile on the path to organizational success might reside in the information we get from the market every moment of the day, the enterprise internal and external information, and in the analysis put on both of the information together.

If enterprises are able to capture the small changes that take place every day, record minimal evolutions in the market, and notice the competition moves, they could be always one step ahead of any crisis.

Our group is interested in analyzing how can enterprises be better prepared when a crisis comes, through the use information?


The Institute for Crisis Management defines crisis as:

A significant business disruption that stimulates extensive news media coverage. The resulting public scrutiny will affect the organization’s normal operations and also could have a political, legal, financial and governmental impact on its business.[1]

There are two types of Crisis. Sudden Crisis and Smoldering Crisis.

Sudden Crisis

Sudden Crisis are circumstances that occur without warning and beyond an institution’s control, usually the company is not to blame for this. This type of crisis is impossible to predict, the variables affecting it are out of scope, and modeling it is simply too complex.

Smoldering Crisis

Smoldering Crisis are “events that start out as small, internal problems within a firm, become public to stakeholders, and, over time, escalate to crisis status as a result of inattention by management." [James and Wooten, “ [2] This type of crisis is possible to predict/anticipate, the variables affecting it are manageable although it is still very complicated.

As shown in the graphs with data from The Institute for Crisis Management [3], smoldering crisis are a huge threat for organizations. Normally, organizations have contingency plans, crisis management plans and/or other mechanisms to prevent organizational collapse during and after a crisis. Before a crisis starts to happen is almost impossible to predict it. However, it is possible to identify the crisis in a very early stage, being easy to mitigate the threat. This is the goal of our presentation.

Smoldering crisis classification [4]

Level 1 Level 2 Level 3 Level 4
Description An internal business problem or disruption that can be dealt with and resolved by management responsible for responding to this kind of situation. An internal problem that can be managed by those who are responsible for this area of business, with support from other management or employees who may have to be brought in to assess the situation and help resolve it. An internal problem that has the potential of going “public” via the news media and generating negative reactions from government officials, plaintiff’s attorneys, competitors, investors consumer activists, labor unions, etc. The crisis can still be contained but will require specialized assistance beyond the management capabilities in place to deal with normal business problems. This assistance may be from corporate headquarters, outside legal counsel, and/or consultants who specialize in resolving this kind of problem. The situation is very serious and is likely to be disclosed publicly in the very near future. The public reaction will have a significant adverse impact on the business for a period of weeks or months and top management along with numerous employees and outside consultants will have be diverted from their normal activities to resolve this situation. The financial impact will be substantial and will have a direct and indirect effect on operating results.
Example Employees of an organization are upset with bad work conditions. They talk with their boss to find a solution for this problem. Employees decided to boycott their work temporarily until their problem is solved. Their boss and other higher management discuss the problem with them. Employees decide to stand in demonstration to achieve what they asked for. They also decide to send a letter to their syndicate to find a resolution for their problems. Employees are resisted and don’t have the chance to manifest dissatisfaction. However, they decided manifest. There’s high friction between them and the management, it draws the attention of media which makes the whole story public. Sales go down.

Prediction and monitoring

Organizational environment

Data Mining

Business Intelligence

Data Mining and Socio-Economic Crisis

Sorts of data and its sources

From Data to Knowledge & Action

Can these data help us take more intelligent decisions? The answer is no. To take better decisions one needs to discover and understand the underlying patterns from these data. Data mining can provide the answers to all kid of organization-related question. Data mining can help organizations to have useful insights into its business from the data it has collected over the years and take better decisions to achieve new heights.

When using organizational as well as external data in order to anticipate on/or manage crisis, one thus has to derive kowledge from information in the collected data and make strategic organizational decisons based on that knowledge. The the overview below for this general process.


  • Internal (operational & transactional data, customer data) vs
  • external (web, news media, social media, metadata, web archive, science databases, etc.)


  • Pattern, associations, relationships among data can provide information


  • Information can be converted into knowledge about historical patterns and future trends


  • Strategig decisions need to be made based on gained knowledge

Steps to be Taken

There are various steps that are involved in the process that leads from raw data to profoun dorganizational decisions. These steps are depicted in the model below:


  1. Data Integration: First of all the data are collected and integrated from all the different sources.
  1. Data Selection: We may not all the data we have collected in the first step. So in this step we select only those data which we think useful for data mining.
  1. Data Cleaning: The data we have collected are not clean and may contain errors, missing values, noisy or inconsistent data. So we need to apply different techniques :to get rid of such anomalies.
  1. Data Transformation: The data even after cleaning are not ready for mining as we need to transform them into forms appropriate for mining. The techniques used to :accomplish this are smoothing, aggregation, normalization etc.
  1. Data Mining: Now we are ready to apply data mining techniques on the data to discover the interesting patterns. Techniques like clustering and association analysis :are among the many different techniques used for data mining.
  1. Pattern Evaluation and Knowledge Presentation: This step involves visualization, transformation, removing redundant patterns etc from the patterns we generated.
  1. Decisions / Use of Discovered Knowledge: This step helps user to make use of the knowledge acquired to take better decisions.

Data Analysis

  • Descriptive Analysis
finding distinctive features in existing data
  • Predictive Analysis
deriving trends from data
interest in temporal patterns, rules, dependencies, regularities
  • Statistical Methods
Neural Networks
Machine Learning

Strategic management schools: prediction


Examples, Lessons and Curiosities

Crisis related examples can be found in the page Crisis: Examples, Lessons and Curiosities.

Case Study

The overview of our case study, the questionnaire and other info can be found at Case study Group 6.

Group and Work Plan overview

Our group is formed by the following students:

Details about our work plan evolution can be found in Group 6 Work Plan page.

Discussion: Are Crises Predictable?

Article about the predictability of the European Financial Crisis


The handouts for the IMOC Group 6 presentation on "Predicting a Crisis" are available here:


  1. Institute for Crisis Management - Crisis Definition, http://www.crisisexperts.com/crisisdef_main.htm
  2. Leadership as (Un)usual (2007) [142–143]. Leadership Review, Kravis Leadership Institute, Claremont McKenna College, Vol. 7
  3. http://www.crisisexperts.com/04report.htm
  4. Institute for Crisis Management - Crisis Definition, http://www.crisisexperts.com/crisisdef_main.htm


Environmental uncertainty, foresight and strategic decision making Sales, Marketing, and Research-and-Development Cooperation Across New Product Development Stages: Implications for Success