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