IT Systems & E-Learning #1: Decision support systems for business processes
IT Systems & E-Learning #2: Obtain Information
IT Systems & E-Learning #3: Analyse Information
IT Systems & E-Learning #4: Make Decisions
IT Systems & E-Learning #5: Enterprise Information Systems

Statistical Analysis

Usually, we want to evaluate large datasets to obtain information for decision-making, so that our decisions are well-founded. However, large datasets cannot be evaluated by simply reading through the data. Therefore, we want to utilise statistical methods to analyse data and find patterns. Some statistical methods that can be used are listed below.

  • Time-Series Analysis: Compare data at different points in time to identify a trend.
  • Correlation Analysis: Compare data points for two variables to find a relation between the variables.
  • Dynamic Programming: Solve a decision problem by splitting it into smaller sub-problems and solving these first to obtain a solution for the entire decision.
  • Frequency Distribution: Calculate how often a certain value or value range is represented in the dataset.
  • Sensitivity Analysis: Analyse to what extent uncertainty in the source data affects the analysis outcome.
  • Descriptive Statistical Analysis: Includes computation of the average, mode, median, minimum, maximum, sum, count, range, standard deviation.

In addition to statistical analysis, we can use queries to the database to filter information to our needs if the data is managed by a DBMS. We have to think of a database as a “black box”, because we usually do not know how the data in a database looks like. Therefore, it is important that any query is specified in detail and relevant to the information required for decision-making. For example, a query can be “Return a count of all unique products with a price higher than $220 of which at least 1 unit was sold in the month of November 2015 from Store Southport2”.

SWOT Analysis

Besides using data and statistical analysis tools or database queries to support a decision, we can perform a high-level analysis of the factors that influence the decision. A prominent tool to carry out such an analysis is the strengths, weaknesses, opportunities, and threats (SWOT) analysis. In the analysis, internal (strengths and weaknesses) and external factors (opportunities and threats) relevant to a decision are evaluated. Strengths are properties of a company that are beneficial to achieve the goal of the decision. Weaknesses are properties of a company that hinder achievement of the goal of the decision. Opportunities are properties of a company’s environment that are beneficial to achieve the goal of the decision. Threats are properties of a company’s environment that hinder achievement of the goal of the decision.

SWOT Table

Decision Models

A model is an abstract representation of a system or an object that exists in the real world or is conceptualised. For example, mathematical models can describe relationships between input and output variables, and a miniature model can describe a real life architectural building. Here, we are interested in decision models, which are models that rely on input data to describe relationships between the data and ultimately provide a basis to make decisions. Most decision models rely on three types of input data:

  1. Constants, such as fixed costs, maximum production capacities, legal working hours, building space.
  2. Uncontrolled variables, which are variables that cannot be influenced by the decision maker, such as customer numbers, legislation, interest rates, harvest outcomes.
  3. Controllable variables, which are variables that can be influenced by the decision maker, such as product prices, production levels, stock levels.
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