nextgen production: how to build a successful digital factory
TRANSCRIPT
NextGen production | How to build a successful digital factory
NextGen production / How to build a successful digital factory
The term Industry 4.0 describes a new industrial revolution driven by the digital automation of factories and by the industrial internet of things. It has become a byword for industrial digitalization. Digital factories present major challenges, both macroeconomic and internal, that have so far prevented a real breakthrough in their development.
We surveyed medium-sized companies across five industry segments: technical end-user products, mechanical engineering, basic materials, automotive suppliers and automation. Results showed:
• 64% of respondents said their main driver for digitalization was to improve processes; 44% cited cost reduction
• The majority (81%) of established use cases are in Big Data, AI analytics, advanced automation and robotics
• Increased efficiency (48%) in both manufacturing and internal processes and improved workflows (28%) are the most commonly reported use case benefits
• Overall, current use cases tend to be domain-specific solutions designed to address individual tasks; they rarely follow a holistic, strategic approach
• A well-thought-out blueprint, or target image, for digital production is still the exception at medium-sized companies
We make four recommendations for successful digital production:
Develop a clear, holistic target image: We outline a blueprint based on five dimensions: digital ecosystem, digital production system, digital shopfloor, digital workforce and digital enablers.
Create the right organizational capabilities, structure and culture: The most successful companies are those that integrate digitalization into existing value creation in the factory. The challenge is to achieve a smooth transition that takes along workers, managers and machines.
Actively seek partnerships and collaborations: Partnerships should aim to reduce costs, create standards, heighten knowledge transfer and improve innovation.
Convince the CFO: Learn by doing at first. But in the longer term, investment calculations (ROI etc.) need to be formalized in the standard investment framework.
We conclude that the path to commercially successful digitalization of factories begins with use cases, continues with the setting of a clear target image and ends with the rollout of changes to tools, skills, mindset and organizational structures. Follow our recommendations and kickstart the factory revolution.
MANAGEMENT SUMMARY
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5
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1 Introduction
Industry 4.0 – The evolution of a revolution
2 Challenges
Why medium-sized companies are yet to fully
benefit from Industry 4.0
3 Status quo
What our survey results reveal about
the current state of factory digitalization
4 Implementation
How to define a target image for digital production
5 Recommendations
How to achieve Industry 4.0 success
Conclusion
The next generation of production
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NextGen production | 3
CONTENTSPAGE
M anufacturing processes, such as the introduction of steam power and electrically powered mass production, changed everything, from the price
of basic goods to the way people worked and lived. The term Industry 4.0 was coined in 2011 to describe
a new industrial revolution, one driven by the digital automation of factories. Since then, the term has attracted much interest and hype. Industry 4.0 became a byword for industrial digitalization, manifesting itself in company strategic agendas and research projects, and driving the use of buzzwords such as digital factories, Big Data, artificial intelligence (AI), industrial internet of things (IIOT) and collaborative robots (cobots). For most manufacturers, its implementation also became one of their biggest challenges.
Yet, the great hype surrounding these terms and concepts seems to have died down. However, there is still little doubt that digitalization will reshape manufacturing, so what has changed? Have factories already fully digitalized, or has the topic somehow lost relevance? Has the big picture and awareness of the benefits been lost? Have priorities changed, or has the momentum faded? And what stage have companies reached in their journey towards digitalization?
This study aims to answer such questions. It incorporates results from a comprehensive survey of managers and experts in medium-sized companies to establish the status quo of digitalization across the production industry, from automotive suppliers to technical end-user products. We also look at the challenges facing the industry, the technologies available to overcome them and existing and potential use cases. Last but not least, we consider the question of return on digital investments.
Building on these, we propose a blueprint, or target image, for digital production that allows any medium-sized company to chart its own roadmap to Industry 4.0 success. We also offer several recommendations to
support their journey. Both aspects include practical industry examples. In conclusion, we find that Industry 4.0 will be more evolution than revolution, starting with developments on the shopfloor before greater domain knowledge and data use usher in true NextGen production.
1 / IntroductionINDUSTRY 4.0 – THE EVOLUTION OF A REVOLUTION
The great hype surrounding the term Industry 4.0 and its concepts seems to have died down. However, there is still little doubt that digitalization will reshape manufacturing, so what has changed?
4 | Focus
M edium-sized manufacturing firms face tough times at the moment. They are juggling numerous challenges that threaten their
business models and bottom lines. Squeezed by the economic downturn and handicapped by the slow pace of internal modernization, many have been in crisis mode for months, trying to balance priorities and react to new trends. Most also lack the financial and capacity resources of larger corporations.
To better understand the current situation, below we look at the key macroeconomic and internal challenges facing medium-sized companies.
MACROECONOMIC CHALLENGES
Difficult trade climate: Trade policy is shifting away from multilateralism, as evidenced by the proliferation of tariffs, embargoes, trade wars, withdrawals from trade agreements, and differences in economic and monetary policies. Countries such as China are also growing in strength, forcing the redistribution of economic power. The result is growing uncertainty, especially for export-oriented medium-sized companies. It is forcing many companies to rethink and reorganize their production footprint and supply chains. Digitalization could play a major role in helping to better manage both.
Sustainability: Companies are facing increasingly stringent sustainability requirements, driven by numerous environmental, social and governance pressures such as climate campaigns and greener investment models. Stricter CO2 emissions targets, for example, have had a major impact on the business model, earnings and operations of many medium-sized firms. Inconsistent global regulations and large investments in climate-neutral technologies also cause disruption. Digitalization provides better control
of such volatility, as well as CO2 emissions. It also offers better transparency.
Digital factories and sustainability
Roland Berger has developed a framework based on the three key aspects of sustainability – environmental, social and governance. The sustainability effects of the digital factory can be measured against this framework.
Digital production has a particular impact on environmental sustainability. As well as helping to improve a company’s CO2 footprint, it also offers: more efficient energy and water usage, for example through the reuse of exhaust heat; enhanced waste management due to optimized machine handling; and recycling of a large share of production materials. When it comes to social sustainability, digital factories also provide more comfortable workplaces, for example by using ergonomic workstations.
Coronavirus pandemic: The majority of medium-sized companies are suffering badly from the pandemic’s effects. With continued uncertainties around new strains and slow vaccination campaigns, this is likely to remain the case for some time. Entire sales markets are collapsing and production and supplier systems need to be urgently rethought. Yet it is almost impossible for companies to predict what will happen next. The final economic damage and consequences are difficult to estimate. As a result, profits have been hit and cash is short for investments in the digitalization of factories.
2 / ChallengesWHY MEDIUM-SIZED COMPANIES ARE YET TO FULLY BENEFIT FROM INDUSTRY 4.0
NextGen production | 5
INTERNAL CHALLENGES
Complexity: Deciding how to digitalize a factory is no easy task. Choosing and evaluating which steps in the value chain and production processes are the best targets is hard enough. But then firms must select the best fitting technology and/or application from the multitude available, or even start to develop their own solutions. At the moment, many firms are still experimenting with new technologies so their decisions lack a wider strategy on which to base them, something that would reduce complexity.
Monetization: It is becoming increasingly clear that the topic of monetizing digitalization is being overlooked. Return on investment calculations, savings and additional revenue potential are rarely monetized. If investments in digital factories continue to exclude potential monetization of digital processes, it will be difficult for firms to adhere to an overarching digital goal that can really drive them forward. To address this, the factors behind scalable production cost savings or revenue gains need to be better understood, and should be brought from project mode into the regular budgeting process.
Adapting structures, processes and skills: The topic of digitalization is often viewed separately from existing production. As a result, central processes and organizational structures are not designed around digitalization and are not truly cemented within companies. Digital skills are also often lacking, and the shift in competencies from traditional to digital has an enormous impact on recruitment and personnel development. This is a big challenge for mid-sized companies in particular, but also an opportunity as new career paths can be fostered.
All mid-sized firms must overcome these challenges if they want to build a truly digital manufacturing organization.
If investments in digital factories continue to exclude potential monetization of digital processes, it will be difficult for firms to adhere to an overarching digital goal that can really drive them forward.
6 | Focus
more than two fifths cited cost reduction and almost a quarter quality enhancement. The drivers were largely the same across all five industry segments. A
DIGITALIZATION TECHNOLOGIES The technologies already being used in digital factories cover everything from Big Data analytics to predictive maintenance and smart energy solutions. Our survey found that technologies to collect, store and analyze data are currently the most important. For example, 44% of respondents said they use cloud data technology, the highest-scoring response. B
T he process of digitalization has been underway in factories for a long time now. Our survey results found that various digital technologies
and associated use cases are already established in all five of the industry segments covered. In this chapter we examine the drivers behind their use and assess their limitations.
About the survey
The survey was conducted through a qualitative questionnaire and interviews. Five industry segments were covered: technical end-user products, mechanical engineering, basic materials, automotive suppliers and automation.
Participants were mainly drawn from medium-sized companies with revenues up to EUR 5 billion a year.
All relevant functions and leadership levels were covered, including top management, middle management, (project) management and technical experts.
The questionnaire consisted of approximately 20 questions and around 40 interviews were conducted.
DIGITALIZATION DRIVERSIn the past, factory digitalization has largely been driven by efficiency improvement, cost reduction and quality enhancement. According to our survey, this is still the case today. Almost two thirds of our survey respondents said their main driver was to improve processes, while
3 / Status quoWHAT OUR SURVEY RESULTS REVEAL ABOUT THE CURRENT STATE OF FACTORY DIGITALIZATION
A: Efficiency drive Process improvement and cost reduction were the top drivers of digital factories in the past (according to survey participants)
Process improvement 64%
Cost reduction 44%
Quality 24%
Flexibility/agility/scalability 16%
Supply chain improvement 12%
Innovation push 12%
Source: Roland Berger
NextGen production | 7
EXISTING DIGITALIZATION USE CASES – AND THEIR LIMITS Numerous use cases can be derived from the technologies already in use and applied in practice. Examples of current use cases are plentiful.
One might be a mechanical engineering company using augmented reality applications (which enhance real-world objects with computer-generated information) to communicate with its customers, both to demonstrate machines and service them.
Another is the widespread use of Automated Guided Vehicles (AGVs), as well as automated packing and shipping, in the warehouse of an automation technology supplier.
Further use cases already applied by medium-sized companies include the use of digital twins (running a digital version of an existing or planned physical system side by side) in production and maintenance, even fully
B: Top tech Software and hardware that exploit data are the most commonly used technologies (according to survey participants)
Source: Roland Berger
Cloud data
44%
Integrated MES
32%
Connection with
customers
20%
Big Data analytics
40%
Digital twinning
24%
AI
16%
Advanced/ smart
analytics
40%
Predictive maintenance
20%
Autonomous systems
16%
integrated manufacturing execution systems (MES), intelligent reporting systems that can directly intervene in operational processes, and the digitalization of quality management.
Our survey found that the majority of established use cases are found in the four areas of Big Data, AI analytics, advanced automation and robotics. Primarily, they are aimed at improved data management, automation of processes, efficient reporting processes and quality improvement. Use cases tend to deviate across industry segments as many are specific to particular industries or even companies. C
These technologies and use cases have already proved successful in medium-sized companies, across various different roles. In particular, respondents repeatedly cited increased efficiency (48%) in both manufacturing and internal processes, improved workflows (28%) and better analysis (12%) as the biggest success stories.
8 | Focus
C: Cases in point Most current digital factory use cases fall into four major categories
Respondents' feedback
Success stories
"Through different digital use cases, we increased the efficiency of our client's production process by 39%"
"Many processes are much easier than they used to be – in particular, claims management and documentation have been hugely simplified"
"We were surprised at how easily new workflows and methods of working were established and accepted by our workforce"
"The speed and accuracy of our failure analysis and error resolution increased significantly"
Challenges
"To really make the digitalization process work, management buy-in is crucial. However, sometimes we do not even know ourselves what to do next. You could say we are lacking a clear digitalization strategy"
"We are a mid-sized company – we cannot and we do not want to develop all the digital solutions ourselves. However, it is hard to find the right partner to develop the solutions that we really need"
"For many digitalization projects it is hard to come up with a valid ROI calculation – sometimes projects are only conducted because we are convinced that they will help us"
Source: Roland Berger
15%
23%
8%Logistics and material handling
Other
Operations reporting• Digital use cases to improve OEE by collecting
and analyzing data throughout the entire production process
• Intelligent reporting that actively suggests operative interventions and procedures
Big Data and AI analytics• Digital use cases enforce predictability and
mobility of maintenance• Strong focus on collecting and analyzing data
to better understand the production process and to steer it more efficiently
• Development of digital twins
8%
3%
18%
25%
Augmented Operator
Quality improvement• Digital use cases to reduce defects and scrap• Digitalization of the quality management process• Communication between ERP and quality system
to steer complaint management (e.g. monitoring of measuring instruments and malfunctions)
Advanced automation and robotics• Automated control of supplies and
equipment usage• Increased focus on introduction of an
integrated MES
NextGen production | 9
In most cases, however, the use cases tend to be domain-specific solutions designed to address individual tasks. They rarely follow a holistic, strategic approach. This is the result of companies approaching processes and technologies individually and pursuing implementation with mixed priorities.
THE FUTURE FACTORYIt’s clear that the gradual implementation of these solutions and use cases is driving the evolutionary
development of Industry 4.0. But it is equally clear that Industry 4.0 has not yet been revolutionary, as many companies hoped in 2011. The developments and results are not yet profound enough. This is reflected in our survey results, where respondents say that almost two thirds of their digitalization goals are still in the idea or planning phase. D
Respondents are also unable to envisage a future that is very different to the current situation. For example, when asked about future drivers and use
D: Slow-going digital journeyMost of our respondents' Industry 4.0 projects are still in the early stages of progress towards a target image
Source: Roland Berger
Large discrepancy
between target and status quo
Skepticism regarding
profitability prevents concrete actions
IDEA
Slicing the elephant:
Projects are planned and executed in small pieces
Currently laying the foundations
(e.g. MES) to execute plan
PLAN
Individual projects
are in the budget
phase
BUDGET
Implementation of first modules
of larger projects started
Overarching framework being
defined for currently ongoing individual projects
PROJECT HARDWARE
Digitalization part of the
factory floor for many years
Parts of the blueprint fully implemented and running
SOFTWARE HR
40%
25%
5%
20%
0%
10%
0%
10 | Focus
cases, respondents gave replies similar to those they gave for current drivers and use cases. In short, they have not formed a clear vision of how digital use cases may disrupt the future production ecosystem. This helps to explain why a well-thought-out blueprint for digital production, outlining its target image, is still the exception at medium-sized companies. E F
Domain-specific use cases will continue to be the major driver for the digitalization of machinery and factories. But it is notable that the most successful
companies to date are those that integrate digitalization into their existing value creation, and not those that impose it as a separate process. Such evolutionary tendencies might lead to a disruptive, revolutionary development. Their implementation requires radical change but can produce radical results.
Mixed-reality applications, for example, are used to train and support technicians more efficiently and enable hands-free working. Besides improved ergonomics, process quality and consistency through
E: Stuck in the past Predictions of future digitalization use cases differ little from today's
Source: Roland Berger
8%Augmented Operator
10%Augmented
Operator
8%Logistics and material handling
19%Logistics and material handling
25%Big Data and AI analytics
29%Big Data and AI analytics
23%Advanced automation
and robotics
18%Operations reporting 3%
Operations reporting15%
Quality improvement
6%Quality
improvement
3% Other 3% Connectivity and communication
PRESENT USE CASE
CATEGORIES
Percentage change
NEAR FUTURE USE CASE
CATEGORIES
+4%
+11%
+2%
+3%
29%Advanced
automation and robotics
+6%
-15%
-9%
NextGen production | 11
Despite the complexity involved and insecurity about the development of digital factories, willingness to invest in digital factories remains high among many companies. G
The question is, where should these investments be made, and how should medium-sized companies approach digitalization?
standardized repair procedures lead to a significant decrease in maintenance operations costs without a change in proven procedures and processes.
Such processes will not replace existing production systems and value creation approaches overnight. Rather the challenge is to achieve a smooth transition that takes into account workers, management and machines.
Source: Roland Berger
F: Time to changePredictions of future digitalization drivers also differ little from current views, with companies lacking a clear vision
MOST IMPORTANT FUTURE DRIVERS (BY SHARE OF SURVEY PARTICIPANTS CITING DRIVER AS ONE OF THE TOP 3)
Process improvement 48%
Cost reduction 40%
Flexibility/agility/scalability 32%
Supply chain improvement 24%
Workplace improvement 16%
Quality 8%
Innovation push 8%
Failure resistance/management 4%
Customer demand 4%PastFuture
12 | Focus
G: Money matters: Most companies plan to invest heavily in digital factories in the short term
Source: Roland Berger
20-30% 70% 2 years 60%
• More investment capital required than for traditional programs
• In some cases, investments in software are a major element
• As well as financial investment, internal resources are deployed for further development of factory digitalization
… the average share of total
investments used for the evolution of the digital factory
… of respondents expect to increase
their share of investment in
the future
… the timeframe in which the majority of respondents will
carry out a large part of their planned
investments
… of respondents apply a standard
ROI calculation for their investment
• New technologies will be more expensive
• No reduction of investments due to COVID-19 expected
• Lighthouse project still missing – but investment planned in the near future
• Only alternative to keep competitive position
• Some companies plan continuous investments in digitalization and no big individual projects
• Standard ROI calculation is the preferred evaluation method – However, in many cases estimate of potential difficult
• Alternatively, project-based calculations are applied. In some instances, no return calculations conducted at all
NextGen production | 13
A clear target image for digital production is a key tool to allow medium-sized companies to focus on the right competencies, standards and
projects – and ultimately make the right investments. But as noted above, this is often missing. In this chapter, we outline a blueprint that companies can align themselves with.
The Roland Berger target image for digital production is based along five dimensions, each of which is a prerequisite of a successful digital factory. Within the dimensions, we have assigned the relevant technological and organizational elements. With the target image providing the parameters, companies can then build a tailored digital roadmap around them. H
DIMENSION 1: DIGITAL ECOSYSTEMThe digital ecosystem defines and sets the direction of networks inside and outside a company. Internally, these consist primarily of the networking of production into the supply chain, as well as links to sales and service. Externally, the ecosystem covers networking, standards and even joint investments with other firms or partners.
For example…Customers awaiting delivery of a new car are not simply given an estimated delivery date but instead can follow the processing status of their vehicle in real time through better networking of production and customer information. They can even make changes to selected equipment up to a certain time point.
DIMENSION 2: DIGITAL PRODUCTION SYSTEMThe digital production system defines value creation and technical standards for all plants. Particular attention must be paid to integration with the existing analog production system.
For example…Adaptive demand planning and control of material flow and transport are key requirements in a plant and its production network. By using battery-powered sensors to monitor the fill level of containers, tanks, silos etc., status reports on fill level, temperatures and location can be transferred to control systems. This allows material requirements planning to be automatically and continuously adapted.
DIMENSION 3: DIGITAL SHOPFLOORA large number of use cases are currently located on the digital shopfloor, as this is where the technological possibilities of digitalization are operationally implemented. These include planning, operational value creation and logistics functions, as well as the implementation of high-performance connectivity.
For example…With the help of a digital twin, an entire digital shopfloor can be planned down to the smallest detail before it is built. Special consideration should be given to flexibility so that the layout can be adapted to different situations in the future. AGVs, cobots, "smart" products and high-performance data transmission via a private 5G network are key tools.
DIMENSION 4: DIGITAL WORKFORCEOur survey showed that the involvement of management and employees plays a special role. This applies both to attitudes toward digitalization and to the integration of digitalization into management methods and work processes. Particular complexities include bottlenecks in recruiting suitable candidates, and flexible, continuously monitored skills development at all levels.
4 / ImplementationHOW TO DEFINE A TARGET IMAGE FOR DIGITAL PRODUCTION
14 | Focus
Digital Enablers
Cloud & edge computing, Big Data, data analytics, AI, ERP & MES systems
H: A new digital blueprint The five dimensions of the target image and their technological and organizational elements
Source: Roland Berger
Digital Ecosystem
Digital supply chain, business model & production, network partners, IP protection, manufacturing footprint
Digital Production System
Value creation, production control model, Reporting, quality management, standards
Digital Workforce
Recruitment & training, shopfloor management, agile methods, digital mindset
Digital Shopfloor
Automation & robotics, logistics, additive manufacturing, sensors, connectivity, AR & VR, cobots, digital twins
E
I
M
A
G
TARGET
NextGen production | 15
For example…The creation of digital workforces is now widespread. Automotive manufacturers, for example, need to completely change their recruitment and development model from one focusing on blue-collar workers to one focusing on white-collar and IT experts.
DIMENSION 5: DIGITAL ENABLERSComputing power, storage space and corresponding algorithms are the core elements of a company’s digital enablers landscape. However, many companies still have big digital gaps in their ERP or MES systems. As such, addressing problems with legacy systems and ensuring new systems are compatible is particularly important in this dimension. There is a high level of expectation in the market with regard to which data-driven tool, application or combination of the two will ultimately prevail. Betting on the wrong horse may result in lost time and money.
For example…New technologies offer new possibilities for automation at the plant and machine control level. Past and current production data can be used to dynamically optimize production schedules in real time, while machine learning can also optimize the control parameters of machines and production lines.
Addressing problems with legacy systems and ensuring new systems are compatible is particularly important.
16 | Focus
and goals are openly and transparently communicated.
ACTIVELY SEEK PARTNERSHIPS AND COLLABORATIONSPartnerships in the development of a digital factory, whether with startups suppliers and customers, software/hardware producers, players from other industries or even competitors, can bring significant advantages for medium-sized businesses. Startup scouting, whereby companies monitor the performance of startups in their sector, often with a view to partnerships or investing, is also a useful collaboration tool.
Whoever the partner, cooperation should be flexible and strongly related to the business, with clear objectives. These should include: reducing costs; creation of standards; joint learning and knowledge transfer (for example of IT know-how, future strategies etc.); faster, more agile action in implementation; and deeper penetration of innovations. Potential partners can sit vertically along the value chain but also horizontally at the same level, such as partnerships with research institutions and universities. Ultimately, a collaborative approach ensures a holistic approach to digital factories.
CONVINCE THE CFOOur survey results show that companies would like to maintain their existing approach to budget approval, that is, conventional budgetary control overseen by a CFO. But this is often not possible in digitalization projects as their effects cannot be specifically gauged. Therefore, courageous entrepreneurial decisions are often necessary at first. But in the longer term, investment calculations (ROI etc.) need to be formalized in the standard investment framework. Companies must also deftly combine digital investments with conventional investments. Those that follow this approach and make decisions based on investment need tend to be further ahead with the digitalization of the factory.
B uilding on our survey results and target image framework, we developed four recommendations to help companies plan, implement and execute
digital production.
DEVELOP A CLEAR, HOLISTIC TARGET IMAGENext generation production means moving beyond domain-driven, task-specific use cases. Companies must think holistically and take all dimensions of the digital factory into account. This means they must develop a clear, overarching target image based on the five dimensions outlined above. This model can look very different depending on the company and must be tailored and adapted to fit its individual and specific characteristics. Ultimately, the target image serves as a common orientation point for employees and the management team. This facilitates digital roadmap development, the making of investment choices and the joint implementation of decisions.
CREATE THE RIGHT ORGANIZATIONAL CAPABILITIES, STRUCTURE AND CULTURE This is one of the most important prerequisites for successful implementation of the target image. Having the right people (73%), a management team that understands and promotes digitalization (32%) and the right organizational culture (32%) were three of the most frequently cited prerequisites for successful implementation of a digital factory in our survey.
In the ideal organization, independently motivated employees with the right competencies and skills should be trained and recruited for the long term. Management must also play its role as a sponsor of digitalization and be able to credibly communicate this sense of transformation to its employees. In addition, systems should be put in place to develop knowledge and keep it in the organization. Finally, companies must adopt a mindset in which digital change is openly embraced
5 / RecommendationsHOW TO ACHIEVE INDUSTRY 4.0 SUCCESS
NextGen production | 17
The next generation of production
It’s clear that advances in digital production have come
a long way since the coining of the term Industry 4.0
in 2011. While the past decade has not yielded the
hoped-for revolution, the implementation of new
technologies and value-creating use cases prove that the
process has begun. We believe it will gain pace and
strength. Initial developments will probably continue
to be driven by use cases, starting on the shopfloor or
at the machine level. The key to commercially
successful digitalization of factories will be to build on
these by defining a clear target image that harnesses
greater domain knowledge and better diagnostic and
evaluation data. This will lead to changes in tools,
skills, mindset and organizational structures. The
result will be time and cost reductions and improved
quality in digital production processes. So follow
our recommendations, and let the revolution begin.
Conclusion
18 | Focus
We welcome your questions, comments and suggestions
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This publication has been prepared for general guidance only. The reader should not act according to any information provided in this publication without receiving specific professional advice. Roland Berger GmbH shall not be liable for any damages resulting from any use of the information contained in the publication.
© 2021 ROLAND BERGER GMBH. ALL RIGHTS RESERVED.
AUTHORS
OLIVER KNAPPSenior Partner+49 711 3275 [email protected]
MARC BAYERPrincipal+49 711 3275 [email protected]
FABIAN BAUERConsultant+49 89 9230 [email protected]
Special thanks to our alumnus Dr. Ralf Klöpfer (Nederman GmbH) for his fruitful ideas and support of this study.
04.2021
Find out more about the future of operations: rb.digital/opera_2030_en
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