1. COURSE DESCRIPTION

The increasing complexity of industry and commerce and global trends such as big data, the analytics revolution, or digitization mean that companies must take a more sophisticated approach towards their decision-making. The quality of decisions is often based on “hard data” to select the best course of action. Also management consultants are often required to focus strongly on quantifying their recommendations wherever they can.

However, managers often fail to understand some of the underlying (statistical) principles and they rely too often on their guts. In consulting, especially junior consultants – the level which is usually charged with extensive analytical tasks at top management consultancies – frequently face a number of challenges when being assigned analytical jobs.

The course addresses some quantitative skills and merges data management techniques in Microsoft Excel with statistical analysis skills. The course considers various types of research and analysis methods. Throughout the course, key ideas, concepts, and techniques will also be discussed extensively in class. The lectures provide both basic concepts and informative material along with some critique of the main idea. We will use many examples that relate to international management or international business.

Please note: Students should be aware that the course is not suited to students who already have a strong background in Excel and in statistical analysis.

2. AIMS

Main aim of the course is to deliver a set of key quantitative skills that the students can use in the future. This not only covers how to conduct a specific quantitative analysis but also to understand its value and importance in today’s business life, as well as its associated problems when it comes to preparing, managing, analyzing, and communicating data and results of analyses.

Knowledge and Understanding:

After completing the course the student will be able to:

•    examine how data assists management in decision-making

•    understand the different types of data available to businesses, the ways data is collected, and what makes data usable to create knowledge.

•    understand and apply specific techniques for data analysis, including techniques using Excel.

Cognitive and Subject Specific Skills:

After completing the course the student will have acquired skills as follows:

•    know where to obtain information which will aid decision making within a company

•    demonstrate that they can move beyond a simple description of data to the analysis and evaluation of data and to the transformation into information

•    know how to conduct effective secondary research with a focus on firm-internal issues

•    know how to combine data files, to set up and manage data bases, and to conduct basic analyses in Excel

•    know how to analyze and interpret data derived from Internet usage, i.e. customer behavior on web pages and in online stores

•    be able to code and analyze primary data by using appropriate (statistical) software packages

•    be able to present and interpret data analysis results in a professional manner

Key Skills:

Students upon completion of the course will have the following skills:

•    Analytical skills – beyond simple description

•    Discussion skills of data analysis and interpretation issues through class discussion

•    Argumentation skills – to debate and defend considered arguments in class during discussions

The course is taught using a combination of lectures, case analyses, class discussion (and outside guest speakers). The readings will give you a broad picture of the importance of data management and analytics.

1)    Take-home exam (15% - group)

2)    Peer review (10% - Individual)

3)    In-class participation (20% - Individual)

4)    Final exam (55% - Individual)

Attention: if a student misses more than 20% of all contact hours in this course the lecturer reservers the right to fail the student.

! ATTENTION ! There are two important issues that you should consider before registering for this course:

The course is not suited to students who already have a very good level in Excel and in statistical analysis.

The following points concern preparatory work for the block course:

1) Familiarize with the eLearning tool (http://bigdata4cems.businesscatalyst.com/st-introduction.html (login: pmba2017))

2) Read all required readings, especially the articles “Keeping up with the quants” and “Analytics 3.0” by Davenport.

3) Read the lecture notes (slides!).

4) Buy and read the case study: Campbell, D.; Martinez-Jerez, F.; Epstein, M. (2006): "Slots, tables, and al that jazz: Managing customer profitabiltiy at the MGMGrand Hotel", Harvard Business School Case: 9-106-029 (http://cb.hbsp.harvard.edu/cbmp/access/63970078)

6) Inform yourself about at the names of functions and other functionalities in MSExcel in the English version. Also have a look at the Data Analysis ToolPak. The ToolPak will be used throughout the course and it is necessary to be fully operationable from the start.

nach Vereinbarung

!! Attention! This course will be based on and optimized for MS Windows system users !!

Mac users will face substantial difficulties as most tools differ between Mac and Windows, sometimes quite substantially!

Those of you who still prefer to use mac please find some information about the analysis toolpak solution here: http://support.microsoft.com/kb/2431349.