Loading...

Reporting and Big Data. Big Data as one megatrend of industry 4.0 and the impacts on controlling

Term Paper 2015 19 Pages

Business economics - Controlling

Excerpt

Table of Contents

List of Abbreviations

List of Figures

List of Tables

1 Introduction
1.1 Problem and Objectives
1.2 Procedure of Seminar Paper

2 Defining the Terms
2.1 Controlling
2.2 Reporting
2.3 Big Data

3 Reporting & Big Data
3.1 Big Data as one Megatrend in the Era of Industry 4.0
3.2 Strategic Potential of Big Data
3.3 Beneficial Categories of Big Data
3.4 Characteristics of Big Data
3.5 Application of Big Data in Industries

4 Big Data in Controlling
4.1 Potential of Big Data in Controlling
4.2 Implementation to the Controller´s Tasks
4.3 Preparing the Controller

5 Threats, Risks, and Barriers of Big Data

6 Conclusion and Outlook

Appendix

Bibliography

List of Abbreviations

illustration not visible in this excerpt

List of Figures

Figure 1: Development of the global Volume of Data (CM 2014, p. 36)

Figure 2: Big Data application-oriented (Härting 2014, p. 17)

Figure 3: The Characteristics of Big Data (ICA 2014, p. 4)

Figure 4: Evaluation of Big Data Potentials per Sector (ICA 2014, p. 8)

Figure 5: Big Data across the entire Supply Chain (ICA 2014, p. 11)

List of Tables

Table 1: Big Data and traditional Analytics (Davenport 2014, p. 4)

Table 2: Big Data Support in Controlling Processes (ICA 2014, p. 25-28)

1 Introduction

1.1 Problem and Objectives

The global data volume is expected to increase fifty-fold over the next ten years (2012-2022). Reasons for extensive growth of data volume within the era of industry 4.0 are the increased use of sensor technology in production and logistics as well as the extensive distribution and the use of mobile Internet. (ICA 2014, p. 3) But the explosion of data is not new. It continues a trend that started in the 1970s. Changes are the velocity of growth, the diversity of data, and the imperative to make better use of information in business. To harvest and harness every byte of relevant data and use it to make the best decisions is the hopeful vision of organizations in terms of big data. (McKinsey 2013, p. 15) On the one hand, opportunities of big data can be identified in all industries over the entire value chain. On the other hand, many companies are sceptical of big data because of high investment costs, the lack of skilled staff and know-how, and privacy risks. That causes delays in big data´s implementation in companies. The careful analysis of the application, and the identification of realizable excess values of big data is one of the controller’s tasks. Completely new opportunities and challenges for the controller arise due to the massive growth of data. Though in future the positions of business analysts and data scientists overlap with the controllers’ skills and fields of activity. (ICA 2014, p. 3) This assignment gives an overview of big data itself and illustrates the potential in controlling and for the controller. Additionally challenges, threats and risks are determined.

1.2 Procedure of Seminar Paper

The second chapter of this assignment defines the most relevant terms. Chapter three has a focus on big data as one megatrend in the era of industry 4.0, where the strategic potential, beneficial categories, characteristics, and the application in industries are described. The following chapter deals with the topic big data and controlling before chapter five concentrates on threats, risks, and barriers of big data. A short conclusion and outlook top the assignment off.

2 Defining the Terms

2.1 Controlling

Controlling is a part of the entrepreneurial management system that main task is to plan, steer, and control all areas of the company. (Springer Gabler Verlag 2014a) Controlling supports the management process in a kind that the motivation of each employee increases because of appropriate key indicators and better steering possibilities. (Horváth 2011, p. 21)

2.2 Reporting

In companies, commonly, reporting is seen as a task of controlling. It includes methods of systematic collection and analysis of data of all quantifiable entrepreneurial connections and processes for planning, steering, and controlling the business happenings. Within the company there are the following objectives:

Illustration and Monitoring of operational processes

Planning and Steering in form of investment appraisals and calculation of return of investment that is a basis of planning of the management. (Springer Gabler Verlag 2014b)

2.3 Big Data

The term big data relates to the development of terminologies for evaluation and analysis of data in support of corporate management. (ICA 2014, p. 3) Big data is a relative term that describes a situation where the volume, velocity, and variety of data exceed an organization´s storage or compute capacity for accurate and timely decision making. It is a combination of old and new technologies helping companies to be actionable. Therefor the capability to manage a gigantic volume of different data, at the right speed, within the right time to allow real-time analysis and reaction is called big data. (McKinsey 2013, p. 16) It refers to data that is too big to fit on a single server, too unstructured to fit into a row-and column-based database, or too continuously flowing to fit into a static data warehouse. The most difficult thing of big data, regarding to Davenport, is its lack of structure. (Davenport 2014, p. 1)

3 Reporting & Big Data

Big data might yield a transformational impact on a company or an industry as well as it changes the nature of work for many individual job roles, regarding to Davenport. He points out a few industry categories that might be transformed in a substantial fashion: Every industry that moves things, sells to customers, employs machinery, sells or uses content, provides service, has physical facilities, and involves money. It is not a systematically classification but demonstrates the huge impact of this topic. (Davenport 2014, p. 31-32)

3.1 Big Data as one Megatrend in the Era of Industry 4.0

The era of industry 4.0 with its trends – mobility, big data, and cloud computing – describes the next industrial revolution. Information Technology (IT) connects the individual elements of manufacturing, from the machinery to the product provided with own intelligence. Not only the horizontal supply chain but also the vertical business-IT, the manufacturing execution (MES) and production systems, up to single machinery sensors are connected in industry 4.0. It is not a concrete technology but describes a vision that has to be implemented by existing technology in combination with technology to develop. Industry 4.0 benefits from the introduced trends, as big data, because it builds up a basis for the implementation of the vision of industry 4.0. (Neubauer 2014) Figure 1 concentrates on the growing global data volume until 2022 within these megatrends of IT-connection. Actually it is not a technically nor an economically problem to store such data but it has to be indicated that only a small percentage (5%) of this amount of data is specifically analysed and used concretely. (CM 2014, p. 35-36)

illustration not visible in this excerpt

Figure 1: Development of the global Volume of Data (CM 2014, p. 36)

As only a small amount of data is specifically analysed and used Table 1 illustrates the main differences of traditional analytics and big data. New requirements in dealing with the huge amount of structured and unstructured data appear with the topic of big data and industry 4.0. (Davenport 2014, p. 4)

illustration not visible in this excerpt

Table 1: Big Data and traditional Analytics (Davenport 2014, p. 4)

3.2 Strategic Potential of Big Data

Entrepreneurial objectives of big data are to get new knowledge through suitable analyses that are relevant for reaching primary goals of the long-term company strategy. Therefor the generation of knowledge in form of defined models of analysis, interpretable results and guidance are most important. The target of companies in the field of big data should be the development to an analytical competitor. That includes to generate competitor´s advantage through data analysis. Especially for companies who´s business models almost only base on data processing the efficient way of using data to support the strategy will be essential for survival. (Bachmann et. al 2014, p. 45 – 48)

[...]

Details

Pages
19
Year
2015
ISBN (eBook)
9783656925118
ISBN (Book)
9783656925125
File size
1013 KB
Language
English
Catalog Number
v294636
Institution / College
FOM Hochschule für Oekonomie und Management gemeinnützige GmbH, Hochschulstudienzentrum Freiburg – business administration
Grade
Tags
big data controlling reporting cfo management strategie variety velocity structure data potential swot volume applicatoin megatrend industry 4.0 industrie 4.0 controller daten unstructured struktur

Author

Share

Previous

Title: Reporting and Big Data. Big Data as one megatrend of industry 4.0 and the impacts on controlling