1  Introduction

1.1 What is the value that I can add in this course?

As a professor, my goal is to educate business graduates so that they can add value to their future organizations. Unfortunately, neither you nor I know what situations you will end up in in business where you can take advantage of using data to make good decisions. There are countless ways to contribute by understanding “data analysis for decision-making”. Therefore, I will try to provide knowledge that is as general as possible. This way, I increase the likelihood that at least some parts of the lecture will be important for your future.

Since access to the internet is virtually constant and instantaneous these days, it’s hard to add value by memorizing something. In seconds, we get answers to almost any sort of question using tools like Google and ChatGPT. Therefore, I don’t see much added value to your education by teaching you facts and schemes to solve problems. Instead, I try to build up your skills and your data literacy that will help you ask the right questions, search for the right information, and use and analyze data in a meaningful way.

Perhaps you know the saying

“A man is well educated when he knows where to find what he doesn’t know.”1

1 Loosely translated and based on the well-known saying “Gebildet ist, wer weiß, wo er findet, was er nicht weiß.“ which is often attributed to George Simmel (1858 - 1918).

I would like to add something here. A man is well educated when he knows…

  • … what he needs to know.
  • … where to find what he doesn’t know.
  • … how to search efficiently.
  • … how to verify the information being found.
  • … how to transform information into insights.
  • … how communicate the insight.

In the spirit of this lecture, my goal is to help you become an educated person who understands how data can support good decision-making.

1.2 What is data analysis for decision-making

For successful communication, intersubjectivity is essential. Once we agree on a clear definition of the words used in the title of this lecture, we can identify the things that we need to know, where to find them efficiently, how to evaluate and use the knowledge.

Data refers to all types of recordable information – facts about something or someone. Data analysis involves the thorough examination of this information with a specific goal in mind. Decision-making is defined as the process of reaching a decision. The word decision comes from the Latin verb decidere, which has various meanings, including

  • make explicit,
  • put an end to,
  • bring to conclusion,
  • settle/decide/agree (on),
  • die,
  • end up,
  • fail,
  • fall in ruin,
  • fall/drop/hang/flow down/off/over,
  • sink/drop,
  • cut/notch/carve to delineate,
  • detach,
  • cut off/out/down,
  • fell.

Let’s agree on the following definition:

Fitzgerald (2002, p. 8): “A decision is the point at which a choice is made between alternative—and usually competing—options. As such, it may be seen as a stepping-off point—the moment at which a commitment is made to one course of action to the exclusion of others.”

Fitzgerald, S. P. (2002). Decision making. Capstone Publishing.

Exercise 1.1 Pass the course

To pass this course, you will be required to give a 10-minute presentation and produce a 3-5 page handout. Your performance will be measured by the quality of your work in relation to the time available. The value of the presentation lies not only in the content, but also in the impact it has on your audience – your classmates and your professor. Your goal is to add some value with your work.

Discuss:

  • What do you need to know to do well in this course?
  • Where can you find the information you need to be successful?
  • What tools will help you find, store and use information efficiently?
  • How can you verify the accuracy of the information you find?
  • How can you analyze information to gain valuable insights?
  • How can you communicate these insights effectively?

Exercise 1.2 Information is omnipresent

Facts are abundant and easily accessible, so education should not just focus on providing information. Instead, skills should be developed to deal effectively with the wealth of facts available. This includes mastering statistical methods and avoiding common pitfalls when working with data.

To find the appropriate statistical method and interpret the data correctly, you should have some knowledge about the type of data and variables that you look at. Use ChatGPT to inform yourself about the following points that are defined in the module description:

Data literacy competencies

  • Types of data: Cross-section, panel, time-series, georeferenced, …
  • Types of variables: Continuous, count, ordinal, categorial, …

Make a short presentation about it. At best, include definitions and examples to the different types of information.

Moreover, what tools would you pick to make the presentation? Discuss the pros and cons of the options available.