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© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Software Business
Leader Forum
Industry 4.0 after the initial hype – Where manufacturers are finding value and how
ISVs can help them to best capture it
Ondrej Burkacky, McKinsey & Company
CONFIDENTIAL AND PROPRIETARYAny use of this material without specific permission of McKinsey & Company is strictly prohibited
McKinsey & Company 1
Most companies expect Industry 4.0 to increase their competitiveness …
What are your expectations concerning how your company’s competitiveness will
develop due to Industry 4.0?
Percent
57
50
54
33
37
40
10
13
6
Increase
Germany
DecreaseRemain unchanged
Japan
USA
SOURCE: McKinsey Industry 4.0 Global Expert Survey 2016
52
55
33
39
15
6Manufacturers
Suppliers
McKinsey & Company 2
… and have also remained these high expectations over the last year …
To what extent has your view concerning the potential of Industry 4.0 changed
compared to 1 year ago?
Percent
44
19
8
10
14
18
46
67
74
Germany
Less optimisticMore optimistic Unchanged
USA
Japan
SOURCE: McKinsey Industry 4.0 Global Expert Survey 2016
23
24
22
9
55
67Manufacturers
Suppliers
McKinsey & Company 3
… but only every second player made real progress in the last year, even less among manufacturers
SOURCE: McKinsey Industry 4.0 Global Expert Survey 2016
50
56
16 84
44
50
Japan
US
Germany
Good/substantial progress or implementation almost complete No or only limited progress
47
36 64
53Technology suppliers
Manufacturers
Progress companies made in the last year in implementing Industry 4.0
applications/strategies overall
Percent
McKinsey & Company 4
Manufacturers are held back by major implementation barriers, many of which rely on internal capabilities
Top 5 barriers mentioned by manufacturers with no/limited progress in Industry 4.0
Additional top barriers mentioned by more advanced manufacturers
Challenges with integrating
data from disparate sourcesLack of necessary talent, e.g., data scientists
Concerns about cybersecurity
when working with third-party providers
Lack of a clear business case that justifies investments in the underlying IT architecture
Difficulty to coordinate actions across different organizational units
Concerns about data ownership when working with third-party providers
Lack of courage to push through radical transformation
Uncertainty about in- vs.
outsourcing and lack of knowledge about providers
SOURCE: McKinsey Industry 4.0 Global Expert Survey
Level of progress
in Industry 4.0
McKinsey & Company 5
Our observations of the most successful manufacturers reveal five effective approaches and perspectives
SOURCE: McKinsey
Don't be afraid of “workarounds” to-
day, but start laying the IT foundations for a more robust solution tomorrow
Build a portfolio of 3rd-party technology
providers
Build a strong internal team with an “agile” mindset
Experiment with new business
models
Focus your efforts on a limited number
of applications
1 2 3 4 5
▪ The most successful manufacturers concentrate on a limited number of Industry 4.0 applications instead of doing everything at once
▪ Our Industry 4.0 diagnostic approach helps identify the biggest value drivers and develop an Industry 4.0 roadmap
▪ Successful manu-facturers overcome operational hurdles (e.g., incompatible data sets) with pragmatic work-arounds instead of waiting for a full-fledged IT transfor-mation
▪ At the same time, manufacturers need to invest in the overall technology stack to lay the foundation for a large-scale rollout
▪ Manufacturers need to create clear criteria to evaluate where capabilities and data should be kept in-house and where to partner with 3rd party providers
▪ For outsourced applications, companies need to develop a good understanding of the market and build capabilities to manage a “best-of-breed” provider structure
▪ Companies need to build up strong internal capabilities and establish a dedicated cross-functional team that drives innovation based on a culture of change and experimentation
▪ Companies must strengthen their capability in business model innovation and experiment with new opportunities for digital integration and data-driven services
McKinsey & Company 6SOURCE: McKinsey
Application Description
▪ From implementing digital documentation systems (for beginners) to using advanced algorithms and big data, e.g., semi-automated root cause analyses (for advanced players)
Digital Quality Management
▪ Cost reductions for industrial robots are driving growing accessibility of automation
▪ Additional potential lies in automation of knowledge work
Next-level automation
▪ Integrating data from process control systems with other data to optimize yield, energy and throughput
▪ Key is to combine available data and create right algorithms
Yield and Energy Optimization
▪ New generation predictive maintenance integrates diverse data sets and uses deep learning algorithms to increase machine availability
▪ Reduces maintenance costs by 10-15%
Predictive maintenance
▪ Gateway to digital manufacturing due to minimal resource requirements and simple, rapidly deployable solutions
▪ Achieves as much as 20-50% OEE improvement
Digital performance management
1 Examples of Industry 4.0 applications that we already see generating a lot of value for manufacturers
McKinsey & Company 7SOURCE: Wirtschaftswoche 2015, survey among 34000 students
7
7
7
8
8
8
9
9
11
11
Fraunhofer Gesellschaft
ProSiebenSat.1 Media AG
Amazon
Crytek
Lufthansa Systems
Daimler
Bundesnachrichtendienst
10
Electronic Arts
Siemens
Porsche
Volkswagen
10
Intel 12
IBM
25
13
BMW
SAP
17
Audi
13
17
Apple 18
Microsoft
44
US tech companies German industrial companies Other German companies
38
12
43
2014102007
Ø 37
131109
28
20
4139
43
08
45
Job openings, in thousand employees
Overall, Germany with an on-going lack of trained computer science employees of ~37,000
Mentions of Top 20 companies by computer science students in %
thereof 16.500 in companies providing IT solutions (IT and telecommunica-tions industry) and 24.500 in industries applying IT solutions
3 War for SW talent is a challenging task – Industrial companies often not first choice
Top 3 companies
mentioned are all US tech companies with
Ø 29% mentions
German industrial companies with Ø11% far less attractive than US tech companies
From the German companies mentioned,
only the ones that are
known to be innovative appeal to graduates
(e.g. Audi, SAP and BMW)
McKinsey & Company 8
3 Given talent and resource restrictions industrialcompanies are looking for help and easy to use solution
We need an analytics platform that can be used without data science background
We have some ideas for online services but cannot afford building the basis for these ourselves
All our software solutions are complete reinventions –there must be a way for more reuse
90% of what we are programming today is not differentiating at all – even worse we are doing a bad job in delivery
I need a data platform to collect data from all my machines in the field, can you help me find someone that offers such a thing?
“
”McKinsey & Company 8
McKinsey & Company 9
3 Machinery industry is quite fragmented with manyspecific verticals …
SOURCE: VDMA, McKinsey
Food and beverage
Pharma/chemical, cosmetics
Non-food
Fresh/frozen food
Dairy
Dry food
Beverages
Solid
Liquid
Medical
Packaging industry example
Split in 15 segments due to different characteristics
Primary
≠
Very segment specific applications
Know-how of complex processes required
Automation know-how differentiating and kept inhouse
Secondary
≠
End of line
≙
Segment unspecific
Simple processes
Mostly small machinery builders with low in-house Automation/ software know-how
Segment specific applications
Medium automation know-how of machine builders
Mixture of complex and simple processes
McKinsey & Company 10
3 … yet several broader solutions from ISVs can providevalue – given they are easy to customize NOT EXHAUSTIVE
UI and workflow optimization for mobile devices
Telematics and asset mgmt. platform for moveable tools/machines
E2E secure communication with remote machines and M2M
Data analytics platform with advanced wizzards
IoT cloud platform to collect data from machines
McKinsey & Company
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Ondrej Burkacky
Thank you!Use the opportunity to discuss openly with me during the break!
Partner, McKinsey & Company
McKinseyDigital.com
