The Digitalization of Management Accounting: Use Cases from Theory and Practice

Foreword
Preface
Contents
1: Digital Controlling: Basics for the Successful Digital Transformation in Controlling
1.1 Introduction
1.2 Controlling Digitalization
1.3 Digitalization in Controlling
1.3.1 Digital Controlling
1.3.1.1 Digital Controlling: Data
1.3.1.2 Digital Controlling: Technologies
1.3.1.3 Digital Controlling: Processes
1.3.1.4 Digital Controlling: Methods
1.3.1.5 Digital Controlling: Competencies
1.4 Conclusion
References
2: Current Trends in Digital Transformation in the Financial Sector
2.1 An Interview by Imke Keimer with Markus Zorn
3: Further Development of the Financial Forecast in the Context of the Digital Transformation Using the Example of SAP SE
3.1 Initial Situation
3.2 The New Forecast Process
3.2.1 Centralised and Decentralised Forecasting Processes Run in Parallel and Complement Each Other
3.2.2 SAP’s Transformation Process
3.3 Key Components in the Central Forecast Process
3.3.1 The Satellite Concept
3.3.2 Predictive Analytics Models
3.3.3 Collaboration Model in the Central Forecast
3.4 Success Factors and Challenges
3.4.1 Process and Organisation
3.4.1.1 Clear Commitment from Senior Management and Perseverance
3.4.1.2 Joint Project Between Experts, Citizen Data Scientists and IT
3.4.1.3 Rethinking Short-Term Management
3.4.2 Operational Work with Predictive Models
3.4.2.1 Clarity About the Objective of Modelling
3.4.2.2 Data Quality and Data History
3.5 Areas of Application Today and in the Future
3.5.1 Central Simulations of Outcome Scenarios
3.5.2 Integration of Predictive Components in Satellites
3.6 Conclusion
References
4: From Success Assurance to Product Development: Data Analysis at Gebrüder Weiss in the Corporate Logistics Department
4.1 Introduction to Controlling at Gebrüder Weiss
4.2 Logistics Controlling at Corporate Logistics
4.3 Current Development in Logistics Controlling at Gebrüder Weiss
4.3.1 Change in the Framework Conditions
4.3.1.1 New Tools
4.3.1.2 New Processes
4.3.1.3 New Methods
4.3.2 Change in the Methods Used
4.3.2.1 Forecasts
4.3.2.2 Machine Learning
4.3.2.3 Network Optimization
4.3.2.4 Simulation
4.4 The Path to Product Development
4.5 Conclusion
References
5: The Digital Transformation of Reporting at Swiss Radio and Television (SRF)
5.1 Introduction
5.2 Initial Situation
5.3 Objective
5.3.1 Standardisation: Notation, Content, Platform
5.3.2 Provision of Information: Self Service
5.3.3 Transparency: Need to Know
5.4 Solution Approach for the Introduction of the New Reporting Landscape
5.4.1 Clustering Modules
5.4.2 Reporting Guideline
5.4.3 Definition of Module Contents
5.4.4 Development of Module Contents
5.4.5 Training
5.5 Learnings
5.5.1 Cultural Change on the Part of Users and Controllers
5.5.2 Enabling
5.5.3 Gamification/Discovering Connections
5.5.4 Development Use and Influence of Further Developments
5.6 Online Reporting: Culture Change
References
6: Benefits and Stumbling Blocks in the Introduction of a Business Intelligence Solution for SMEs Using the Example of SIGA
6.1 Introduction
6.2 Definition of Controlling and Business Intelligence
6.2.1 Controlling
6.2.2 Business Intelligence
6.3 IT Systems and Data Management of the BI Solution
6.4 Business Intelligence and Analytics in Controlling: Practical Examples
6.4.1 Standard Report Using the Example of a Sales Report
6.4.2 Drill-Down Report Using the Example of Sales Prices
6.4.3 Alerts Using the Example of a Real-Time Report in Production
6.4.4 Shopping Basket Analysis
6.4.5 Forecasting with Prophet
6.5 Stumbling Blocks and Lessons Learned
References
7: Digitalize Corporate Management with Business Intelligence
7.1 Introduction
7.1.1 Business Intelligence
7.1.2 Business Analytics
7.1.3 From Strategy to Management Cockpit (Descriptive and Diagnostic Analysis)
7.1.4 From Control to Planning
7.1.5 Using Business Analytics to Recommend Action
7.1.6 From Selection to Implementation
7.2 Initial Situation
7.3 Objectives of the New BI Solution
7.4 Solution: Project Preparation as a Basis for the Successful Implementation of the BI Solution
7.4.1 From Big Data to Services
7.4.2 The Requirements Definition
7.5 Result: From the Requirements Specification to the BI Solution
7.5.1 Specifications
7.5.2 Why Is the Comment Function so Important?
7.6 Design: There Is No Second Chance for the First Impression
7.6.1 Design
7.6.1.1 The Home Page Is the Reference
7.6.1.2 Selection and Choice Fields
7.6.1.3 Information and Selection Fields (Left)
7.6.1.4 Time and Basic Data Selection
7.6.1.5 Keeping Graphics Clear, Consistent and Simple
7.6.1.6 Colour Is Information
7.7 Success Factors for Successful Implementation
7.7.1 Acceptance
7.7.2 Quality/Trust
7.7.3 Care
7.8 Learnings
7.8.1 What Have Been the Benefits of Implementing the Business Intelligence Solution?
7.8.2 Getting Out of the Comfort Zone
7.8.3 Requirements Determine the Technology
7.9 Conclusion
Literature
8: From Digital Tools to Digital Methodology
8.1 Initial Situation
8.1.1 Previous Planning
8.1.2 Status of Digitisation and Technical Stack
8.1.3 Definition of BI system
8.2 Design Phase
8.3 Agile Prototyping for the Development of the Agile Planning Method
8.4 Iterative Development Process
8.5 Result Actual Status
8.6 Outlook
8.7 Lessons Learned
8.8 Conclusion
References
9: Business Analytics in Marketing Controlling: A Case Study for the Automotive Market
9.1 Digitalization in Marketing Controlling
9.1.1 Analytics: Challenge and Opportunity of Digitalization
9.1.2 Characteristics of Marketing Controlling
9.1.3 Controlling Tasks in the Analytics Process Using the Example of CRISP-DM
9.2 Time Series Analysis as an Application Example in Marketing Controlling
9.2.1 Characteristics of Time Series Analysis
9.2.2 Data Preparation
9.2.3 Modeling and Evaluation
9.2.4 Further Development of the Model: Distinguishing the Type of Drive
9.3 Competence Requirements in Digital Controlling
References
10: Interactive Big Data Visualizations: Potential for Management Reporting
10.1 Introduction
10.2 Overview and Use of Big Data Visualizations
10.2.1 Types of Visualization: Application and Level of Familiarity
10.2.2 Interaction: Taxonomy and Application
10.3 Design and Usability of Specific Interactive Big Data Visualizations
10.3.1 Overview of the Research Methods Used
10.3.1.1 Online Surveys
10.3.1.2 Eye Tracking
10.3.2 Multidimensional Visualizations – Multiple Dimensions
10.3.2.1 Sankey Chart
10.3.2.2 Sunburst Chart
10.3.2.3 Treemap
10.3.3 Multidimensional Visualizations – Multiple Attributes
10.3.3.1 Parallel Coordinates Plot
10.3.3.2 Heatmap
10.4 Conclusion
References
11: Digital Transformation in Controlling at the Alpiq Group
12: Controller Profiles in Switzerland: Importance of Digitalization
12.1 Introduction
12.2 Development of the Controlling Role Models
12.2.1 Traditional Controlling Role Models
12.2.2 Controller as Business Partner
12.2.3 Digital Controller
12.3 Analysis of Controller Job Advertisements in Switzerland
12.3.1 Research Design and Methodological Approach
12.3.2 Areas of Responsibility Mentioned
12.3.3 Required Competences
12.4 The Controllers of the Present and Future
References
13: Standardization and Automation as the Basis for Digitalization in Controlling at Siemens Building Technologies
13.1 Introduction
13.2 Standardisation and Automation at Management Level
13.2.1 Initial Situation
13.2.1.1 ESPRIT Database
13.2.1.2 BT Business Warehouse
13.2.2 Smart Reporting
13.2.2.1 Challenge
13.2.2.2 Structure of Smart Reporting
13.2.2.3 Requirements for Smart Reporting
13.2.2.4 Implementation by the IT Team
13.2.2.5 Rollout and Acceptance
13.2.2.6 Further Development of Smart Reporting
13.2.2.7 Success Factors
13.2.3 Smart Analytics
13.2.3.1 Challenge and Structure of Smart Analytics
13.2.3.2 Objective of Smart Analytics
13.2.3.3 Implementation by the IT Team
13.2.3.4 Rollout and Acceptance
13.2.3.5 Additional Visualization and Analysis Options
13.2.3.6 Success Factors
13.3 Standardization and Automation in Operational Controlling
13.3.1 Business Activity (BA) DAsh
13.3.1.1 Objective
13.3.1.2 Requirements for BA DAsh
13.3.1.3 Implementation by the IT Team
13.3.1.4 Result
13.3.1.5 Success Factors
13.3.1.6 BA DAsh Outlook
13.3.2 Further DAsh Applications
13.4 Digitalization Through Predictive Analytics
13.4.1 Sales Forecast with Predictive Analytics
13.4.1.1 Initial Situation
13.4.1.2 Requirements
13.4.1.3 Objectives
13.4.1.4 Pilot Project Procedure
13.4.1.5 Result
13.4.1.6 Success Factors
13.4.1.7 Next Steps
13.4.2 Possibilities and Limits of Predictive Analytics
13.5 Learnings
13.6 Conclusion
14: Digitalization of the Controlling System in Theory and Practice Using the Example of the ARTS Group
14.1 Introduction
14.2 Digitalization and Controlling Systems
14.3 Digitization of Controlling Subsystems
14.3.1 Digitalization of Controlling Tasks
14.3.2 Digitalization of the Controlling Organisation
14.3.3 Digitalization of Controlling Instruments
14.4 Case Study: Digitization of the Controlling System at ARTS
14.4.1 Digitalization of Controlling Tasks
14.4.2 Digitalization of the Controlling Organisation
14.4.3 Digitalization of Controlling Instruments
14.5 Further Development Trends of Digitalization in Controlling
14.6 Conclusion
References
15: From Financial Report to Controlling Cockpit in the Age of Digitalization
15.1 Introduction
15.2 Initial Situation
15.2.1 Presentation of the Current Situation by Means of the Maturity Model
15.2.2 Reporting
15.2.3 Analysis
15.2.4 Planning
15.3 Objective
15.3.1 Target Image
15.4 Solution Approach
15.4.1 Prerequisites
15.4.1.1 Value Driver Tree
15.4.1.2 Control of the Organisation
15.4.1.3 Standardisation Versus Individual Needs
15.4.2 Reporting
15.4.2.1 Level- and Addressee-Oriented
15.4.2.2 Real-Time Key Figures
15.4.2.3 Self Service Portal
15.4.2.4 Visualizations
15.4.3 Analysis
15.4.3.1 Structure and Integration of Order Cockpit in ERP
15.4.3.2 Structure of Data Sources, Data Cube, Business Warehouse
15.4.4 Planning
15.4.4.1 Consistent Key Figs
15.4.4.2 Significant Reduction of Complexity
15.5 Learnings
15.5.1 Establish Principles at the Outset
15.5.2 Putting Yourself in the Role of the Receiver
15.5.3 Change Takes Time and Resources
15.6 Conclusion
References
16: Possibilities and Limitations of Mobile Applications for Controlling
16.1 Introduction
16.1.1 Current Tasks and Challenges of Controlling
16.1.2 Brief History of Mobile Devices
16.1.3 Current Characteristics of Mobile Devices
16.2 Relevant Mobile Devices and their Usage Habits
16.2.1 Tablets
16.2.2 Smartphones
16.2.3 Wearables
16.2.4 Usage Habits
16.3 Reporting on Mobile Devices from a Controlling Perspective
16.4 Challenges in Controlling
16.5 Possibilities of Mobile Devices
16.5.1 Development Possibilities
16.5.1.1 Development with Cross-Platform Language
16.5.1.2 Development with Platform-Specific Language
16.5.1.3 Development with Non-platform Language
16.5.1.4 Specific Solutions
16.5.2 Security
16.5.3 Information Presentation
16.5.4 Mobile Backends and Cloud Computing
16.5.5 Synchronisation and Continuity Between Mobile and Fixed Devices
16.6 Case Studies
16.6.1 Use of Microsoft Power BI
16.6.2 Use of the Microsoft SQL Server BI Platform
16.6.3 Using SAP HANA with MicroStrategy
16.7 Conclusion
References
17: How Zalando Uses Digital Solutions to Transform Investment Controlling
17.1 Introduction: Zalando and Digitalization
17.2 Initial Situation: Reasons for Introducing Two New Digital Solutions
17.3 Target Image: Product Vision and Use Cases
17.4 Procedure: Project Structure and Implementation
17.4.1 Investment Boardroom
17.4.1.1 Discovery
17.4.1.2 Definition
17.4.1.3 Design
17.4.1.4 Delivery
17.4.1.5 Rollout
17.4.2 Investment App
17.4.2.1 Discovery
17.4.2.2 Definition
17.4.2.3 Design
17.4.2.4 Delivery
17.4.2.5 Rollout
17.5 Lessons Learned: Challenges, Do’s and Don’ts
17.5.1 Investment Boardroom
17.5.2 Investment App
17.6 Conclusion: Digitization as an Opportunity for Controlling
References
18: Digitalization of Controlling in Insurance Companies
18.1 Basic Understanding of Insurance and Controlling
18.1.1 Basic Understanding of Insurance
18.1.2 Basic Understanding of Controlling
18.1.3 Need for a Sector-Specific Concept of Controlling?
18.2 Application Orientation and Interdisciplinarity in Controlling in Insurance Companies
18.2.1 Application Orientation
18.2.2 Interdisciplinarity
18.3 Selected Applications of Controlling in Insurance Companies and their Digitalization
18.3.1 Contribution Margin Calculations
18.3.2 Internal Models
18.3.3 Telematics Tariffs
18.4 Effects of Digitalization on the Competencies of Controllers in Insurance Companies
18.5 Conclusion and Outlook
References
19: Use of Smart Technologies in Large Infrastructure and Energy Projects
19.1 Introduction
19.2 Challenges of Large Infrastructure and Energy Projects
19.2.1 Technical and Functional Level
19.2.2 Economic Level
19.2.3 Political Level
19.2.4 Project Management Level
19.2.5 Data Management Level
19.3 Data Management and Digital Technologies for Project Controlling
19.3.1 Basic Technologies
19.3.2 Obtaining Data
19.3.3 Checking the Plausibility of Data and Structuring it
19.3.4 Analysing and Using Data
19.4 Practical Approaches to the Digitalization of Project Controlling
19.4.1 Overview of Controlling Tasks and Digital Tools
19.4.2 Project Objectives and Feasibility
19.4.2.1 Project Databases and Benchmarking
19.4.2.2 Cognitive Agents in the Collection of Information
19.4.2.3 Scenario Technique for Validation of Project Assumptions
19.4.3 Project Planning
19.4.4 Risk Controlling
19.4.5 Reporting and Analysis
19.4.6 Closure and Consolidation
19.5 Conclusion and Outlook
References
20: Current Trends and Future Potentials of Digitalization in Procurement Controlling
20.1 Objective
20.2 Relevance of Procurement
20.3 Digital Transformation of Procurement
20.4 Effects of Digitalization on Controlling
20.5 Special Effects of Digitalization on Procurement Controlling
20.6 Empirical Review: Job Advertisement Analysis
20.6.1 Justification of the Method of Investigation
20.6.2 Objectives and Presumptions of Effectiveness
20.6.3 Overview of Existing Studies
20.6.4 Procedure
20.6.5 Description of the Sample
20.6.5.1 Framework Data
20.6.5.2 Representativeness: Sector and Size Distribution
20.6.6 Results of Job Advertisement Analysis
20.6.6.1 Impact Assumption 1: Increase in Strategic Tasks
20.6.6.2 Impact Assumption 2: Increase in the Need for IT Skills
20.6.6.3 Impact Assumption 3: Increase in Analytical Activities
20.6.6.4 Impact Assumption 4: Intensified Cooperation with IT Department
20.7 Conclusion
References
21: The Role of the Chief Financial Officer in the Digital Transformation of Business Models
21.1 Introduction
21.2 Value-Oriented Controlling and the Digital Transformation of Business Models
21.2.1 Value-Added Oriented Controlling: Purpose, Functions, Objects, Tasks and Duty Bearers
21.2.2 The Digital Transformation of the Business Model as an Object Field of Value-Added Oriented Controlling
21.3 Tasks, Duty Bearers and Instruments in the Context of the Digital Transformation of Business Models
21.3.1 Initialize
21.3.1.1 Locomotion Function
21.3.1.2 Information Function
21.3.1.3 Reconciliation Function
21.3.2 Realize
21.3.2.1 Locomotion Function
21.3.2.2 Information Function
21.3.2.3 Reconciliation Function
21.3.3 Evaluate
21.3.3.1 Locomotion Function
21.3.3.2 Information Function
21.3.3.3 Reconciliation Function
21.4 The CFO in the Digital Transformation of Business Models
21.4.1 Scientific Approach
21.4.2 Empirical Validation
21.5 Target Profile of the CFO
21.6 Conclusion and Outlook
References
22: Hack Yourself: A Call for an Artistic Metamorphosis of the Controller in the Digital Transformation
22.1 Controlling and Controllers in the Digital Transformation
22.2 The Controller at the Crossroads
22.2.1 The Changing Art of Controlling
22.2.2 Modern Art as Agent & Inspirational Surface of Transformation
22.3 L’Invitation au Voyage: Excursions into Artistic Thinking
22.3.1 Against the Norm
22.3.2 Without Purpose and Open-Endedness
22.3.3 From Aesthetic Competence to Transfer
22.4 Drawing Inspiration: Looking Inwards and Outwards
22.4.1 Looking Inwards: Studio Time
22.4.2 The View Outwards: Figure and Ground
22.4.3 Disrupt Yourself – Creative Destruction
22.5 Digitalization as a Creative Opportunity for Controllers
References