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.

Risk Management

In the previous post, we have outlined methods to extract information from data that can be used to help with making decisions about business processes. While these methods provide a good foundation to make well-founded decisions, some degree of uncertainty will always remain about the outcomes of decisions. Risk management is part of any good project management plan and we can use its concepts in decision-making to address and reduce risks associated with a decision.


Project Risk Factors

The chart above shows that three factors influence project risk: the project scope, the project structure, and the project team’s previous experience.

Project Scope: Project scope refers to the size of the project, this includes the length of the project, the resources required, and the stakeholders and business areas involved in the project. The bigger the project scope is, the greater is the risk associated with the project.

Project Structure: Project structure refers to how well the requirements of a project are defined. Projects that are well-structured have a lower risk than projects that not structured well.

Experience: Whenever the project management or implementation team has experience with similar projects, project risk is lower than for projects the team is unfamiliar with.


Develop a Project Risk Management Plan

In order to address risks, the project management team should use information as shown in the chart above to prepare a risk management plan: a project scope statement, a schedule management plan, a cost management plan, a communications management plan, an evaluation of enterprise environmental factors, and an overview of organizational process assets. The risk management plan is then consulted during a decision-making process to reduce the risks associated with the decision.

Making Decisions


Levels of Decision-Making

The chart above shows what type of decisions are made on each level of management in a business. Operational management is responsible for making structured decisions. Structured decisions are decisions that have to be made on a regular basis with little or no variance, have low impact on the overall business, and a well-defined procedure to deal with them. Unstructured decisions, on the other hand, are decisions with high impact on the business and differ greatly in the way they are treated and the type of information required to address them. Senior management is responsible for such kind of decisions. Decisions that share characteristics of both structured and unstructured decisions are typically found in middle management.

We can summarise the steps involved in making decisions as intelligence, design, and choice. Intelligence is the process of determining and understanding the exact business problem. Design refers to finding the possible solutions to the business problem and choice means selecting one or more of these solutions.


Three Steps of Decision-Making

Looking at the three-step process, we can see that information is the underlying foundation of all steps. Therefore, information systems are crucial to making decisions in modern businesses.

Information Flow

After any decision has been made to address a business problem, the decision needs to be implemented. The implementation will bring about change to the business and it is important that all stakeholders are informed about the decision that has been made as well as its implications. In addition, the structure of information generated and required during business processes needs to be considered. Any change to a business operation also affects the information generated and required during the process. As such, to implement a decision the following actions are required with respect to the information flow in the business:

  • Document the decision and inform stakeholders timely
  • Update internal and external communication plans
  • Update data collection methods, databases, and information systems
  • Test and curate new systems
  • Update and ensure company information policy and security

After the new systems and/or processes are implemented, they provide the business with new information about its operation and effectiveness. This information can then be used as input to successive decisions to be made. Thus, we have a cycle of information flow and can extend next figure as follows.

Closing the Information Cycle
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