Peter Rausch

Business Intelligence and Performance Management

During the 21st century business environments have become more complex and dynamic than ever before. Companies operate in a world of change influenced by globalisation, volatile markets, legal changes and technical progress. As a result, they have to handle growing volumes of data and therefore require fast storage, reliable data access, intelligent retrieval of information and automated decision-making mechanisms, all provided at the highest level of service quality. Successful enterprises are aware of these challenges and efficiently respond to the dynamic environment in which their business operates.Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges and provide techniques to enable effective business change. The important aspects of both topics are discussed within this state-of-the-art volume. It covers the strategic support, business applications, methodologies and technologies from the field, and explores the benefits, issues and challenges of each. Issues are analysed from many different perspectives, ranging from strategic management to data technologies, and the different subjects are complimented and illustrated by numerous examples of industrial applications. Contributions are authored by leading academics and practitioners representing various universities, research centres and companies worldwide. Their experience covers multiple disciplines and industries, including finance, construction, logistics, and public services, amongst others.Business Intelligence and Performance Management is a valuable source of reference for graduates approaching MSc or PhD programs and for professionals in industry researching in the fields of BI and PM for industrial application.

Business Intelligence and Performance Management: Introduction

Globalisation, volatile markets, legal changes and technical progress have an immense impact on business environments in most industries. More and more IT is deployed to manage the complexity. As a result, companies and organisations have to handle growing volumes of data which have become a valuable asset. The ability to benefit from this asset is increasingly essential for business success. Therefore, fast storage, reliable data access, intelligent information retrieval, and new decision-making mechanisms are required. Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges. Before important aspects of both topics are analysed from different points of view, this chapter gives an introduction to concepts and terms of BI and PM.

Managing Uncertainties in the Field of Planning and Budgeting – An Interactive Fuzzy Approach

Despite all effort in last decades, Planning and Budgeting (P&B) is still a challenging task. The corresponding processes for large organizations are usually very resource-intensive, time consuming and costive. One of the major issues is to manage uncertainty. Apart from that, P&B methods have to fulfill other requirements. They have to be consistent with human thinking and should allow realistic modeling. In this paper we analyze whether interactive fuzzy approaches solve these issues and if they could be a new way to fulfill the above mentioned requirements efficiently. For that purpose, prior research related to P&B problems as well as practical issues and challenges will be outlined. Based on a case study, fuzzy interactive solutions will be analyzed. Possible benefits and issues of the applied approach are discussed and ideas about ongoing and further research are given.

Data Supply for Planning and Budgeting Processes under Uncertainty by Means of Regression Analyses

Planning and Budgeting (P&B) is an important part of Performance Management (PM). The corresponding processes for medium-sized and large organisations are usually very resource-intensive, time consuming and costly. These issues are mainly caused by uncertainty, which is a big challenge for companies. It is shown that available software and tools do not address this challenge in an appropriate way. Before possible issues and solutions are analysed in detail, an overview of different types of uncertainty is given. Afterwards important steps of the P&B process which suffer from uncertainties are outlined. Quite often it is not really clear which parameters have an impact on the planning object and how strong the planning object is influenced by certain parameters. Additionally, forecasts of the most important parameters which anticipate uncertainties are needed at an early stage of the P&B process. To resolve these issues, the application of different types of regression analyses will be explored. Also, ideas for further processing of fuzzy data in the following P&B steps are given. Furthermore, organisational and cultural prerequisites for the successful application of the outlined approaches will be indicated.

Linking the Operational, Tactical and Strategic Levels by Means of CPM: An Example in the Construction Industry

During the last decade, much progress has been made in the field of CPM. However, there are still some issues to master. Many companies have implemented only isolated CPM bricks, and controlling systems which supply real-time information are still missing. To exploit the whole potential of CPM, it is necessary to integrate the CPM components and to link the operational, tactical and strategic levels. In this chapter, an integration grid is used to address all interconnections between the different components systematically and to fill the gaps between the operational, tactical and strategic levels. The grid is applied to a new generation of CPM systems for the construction industry. The CPM approach presented is based on data of a satellite-supported, machine control & guidance system. This data is combined with data from other sources to enable intelligent analyses. Benefits and open issues are discussed. Finally, possibilities for further developments of the presented approach are mentioned.

Efficient Interactive Budget Planning and Adjusting Under Financial Stress

One of the most challenging tasks in financial management for large governmental and industrial organizations is Planning and Budgeting (P&B). The processes involved with P&B are cost and time intensive, especially when dealing with uncertainties and budget adjustments during the planning horizon. This work builds on our previous research in which we proposed and evaluated a fuzzy approach that allows optimizing the budget interactively beyond the initial planning stage. In this research we propose an extension that handles financial stress (i.e. drastic budget cuts) occurred during the budget period. This is done by introducing fuzzy stress parameters which are used to re-distribute the budget in order to minimize the negative impact of the financial stress. The benefits and possible issues of this approach are analyzed critically using a real world case study from the Nuremberg Institute of Technology (NIT). Additionally, ongoing and future research directions are presented.

Interactive Fuzzy Decision Support to Adjust Human Resource Structures.

Human resource planning plays a key role for enterprises’ and organizations’ sustainable success. This paper focuses on issues and challenges in the field of human resource planning in hierarchical organizations. Due to current challenges, like digital transformation, progress in artificial intelligence, etc., a fundamental structural transformation of workforce is initiated in many companies and organizations. Especially, huge enterprises in many industries and the service sector as well as organizations in the public sector have to review their mid-term and long-term desired human resource (HR) target structures. Based on an organization’s target structure, a strategy to transfer the actual HR structure to a desired new target structure is needed. This step is a big challenge because of many uncertainties of system parameters and complex structures of the planning approaches with many constraints and conflicting goals. To bridge gaps in this field, an interactive fuzzy approach which supports the development of strategies for actual-target structural adjustments (ATSA) in big organizations will be presented. This approach manages conflicting goals and is based on experience gained in an organization of the public sector, but it can also be transferred to non-governmental industry and service

On the Way Towards Automated Planning and Budgeting: Combining Fuzzy Planning with CBR Learning Systems

In this paper we present a novel hybrid approach to improve the complex process of planning and budgeting (P&B). Especially in the field of fuzzy P&B a lot of expert knowledge is needed to find an appropriate solution for planning problems. To support decision makers we consider a combination of a fuzzy P&B tool with a case-based reasoning (CBR) system. The novel hybrid approach will be presented, and it will be analysed in which way decision making and learning processes can be improved. Due to the promising results, we also discuss possible extensions to automate P&B processes completely.

Quality Management Using Electrical Capacitance Tomography and Genetic Programming: A new Framework

Currently, many automotive companies struggle with expensive product recalls. To overcome these issues the need for quality management increases. Hence, we propose a monitoring and control framework for Lost Foam Casting (LFC) manufacturing processes using Electrical Capacitance Tomography (ECT) and an evolutionary Genetic Programming (GP) based system. The multi-tier framework simulates the process output, helps simulating a metal filling modeling part of the process and supports product quality control. The results are very promising.