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© 2010 – 2016 eoda GmbHOliver Bracht
R in the German Mittelstand
Bringing data science to small and medium-sized enterprises
eRum 2016
Oliver Bracht
Chief Data Scientist
Implementing R in the Mittelstand
Bringing data science to small and medium-sized companies
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
About eoda
Interdisciplinary Team
Statisticians | Engineers | Economists | Sociologist | …
Based in Kassel - Germany
Data Science Consulting, Training, Support,
Software and Analytic Services with a focus on R
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Core Data Science Lab
Pioneer Requirement
New Economy
Enterprises
Mittelstand
Introduction of R
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Mittelstand
Statistical Definition
Number of employees between 10 and 500
Turnover between €2 million and €50 million
About 99% of all companies in Germany are SMEs
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
• Mostly family-owned
• CEO is often a member of the owner family
• Successful and profitable ever since
• Often located on the landside, in small towns
• Many global leaders in niche markets
• Mainly industrie and commerce
• Strong engineering culture
The German Mittelstand
Characteristics
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
The German Mittelstand
Characteristics
• Often conservative with regard to IT
• Low notion of employer targeting
• Long term employee relationship
• Low software development skills
• Low analytical maturity level
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
The Mittelstand’s road of implementing R
Level 1: First contact
Level 2: Proof of Concept
Level 3: Production
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
• Company is not using any Data Science Tools so far - beside Excel
• A single person or small group starts using R for certain tasks
• Often interns or entrants
• Software decision independent from the IT-department
• Non strategic decision
• Colleagues, supervisors and management are excited
Level 1: First contact
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Success factors
• Involve IT department as early as possible
• Try to enlarge the internal Data Science Team
• by training (internal, on-site, online)
• by hiring
• Get as soon as possible to the next level
Level 1: First contact
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Risks
• IT department raises difficulties
• Getting lost in ad-hoc requests
• Becoming everybody's problem solver
Level 1: First contact
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
• Use Case Evaluation
• Data Availability
• Analytical Complexity
• Business Value
• Select the most promising use cases for
implementation
• Plan to accomplish more than one use case
Level 2: Proof of Concept
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Level 2: Proof of Concept
Success Factors
• Make sure that implementation is principally possible
• Have your target in mind, don't get lost in details
• Involve business as much as possible
• Don‘t scare business with statistical terms
• Keep analytic approach and business demand
in line
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Level 2: Proof of Concept
Risks
• Promising particular success
• Sticking to your original ideas if they don‘t fit anymore
• Showing preliminary results to business people
• Investing too much energy in optimization and performance
• Communication between Data Science and Business
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Level 3: Production
• Implementing Proof-of-Concept approaches into Production
• Shift from laboratory to automation
• Shift from hacking to programming
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Level 3: Production
Success Factors
• Focus on software developers skills
• Care much about performance
• Put a first stable version on the live system before adding new features
• Open a backlog for future improvements
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Versioning Failure controll
Dependency Management Documentation
Package Building Staging
Testing Deployment
Profiling
Level 3: Production
Sucess Factors
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Output
Technical Implementation
Analytic
Level 3: Production
Risks
• Underestimation of effort for maintenance and bug fixing
• Debugging is harder on Production systems
• Appling code changes without tests on staging systems
• „Unknown“ input
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Conclusion
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Statistics,
Methods
Domain-
knowledge
Data Science
Software
Development
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Guerilla & Proof-of-Concept
Statistics,
Methods
Domain-
knowledge
Software
Development
© 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de
Introduction | First contact | Proof of Concept | Production
Statistics,
Methods
Domain-
knowledge
Production
Software
Development
© 2010 – 2016 eoda GmbHOliver Bracht
@eodaGmbH
@eodaGmbH eodaGmbH
blog.eoda.de
eoda GmbH
Universitätsplatz 12
34127 Kassel - Germany
www.eoda.de/en
info@eoda.de
+49 561 202724-40
The Data Science Specialists.

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R in the Mittelstand: Bringing Data Science to small and mid-size companies.

  • 1. © 2010 – 2016 eoda GmbHOliver Bracht R in the German Mittelstand Bringing data science to small and medium-sized enterprises eRum 2016 Oliver Bracht Chief Data Scientist Implementing R in the Mittelstand Bringing data science to small and medium-sized companies
  • 2. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production About eoda Interdisciplinary Team Statisticians | Engineers | Economists | Sociologist | … Based in Kassel - Germany Data Science Consulting, Training, Support, Software and Analytic Services with a focus on R
  • 3. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Core Data Science Lab Pioneer Requirement New Economy Enterprises Mittelstand Introduction of R
  • 4. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Mittelstand Statistical Definition Number of employees between 10 and 500 Turnover between €2 million and €50 million About 99% of all companies in Germany are SMEs
  • 5. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production • Mostly family-owned • CEO is often a member of the owner family • Successful and profitable ever since • Often located on the landside, in small towns • Many global leaders in niche markets • Mainly industrie and commerce • Strong engineering culture The German Mittelstand Characteristics
  • 6. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production The German Mittelstand Characteristics • Often conservative with regard to IT • Low notion of employer targeting • Long term employee relationship • Low software development skills • Low analytical maturity level
  • 7. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production The Mittelstand’s road of implementing R Level 1: First contact Level 2: Proof of Concept Level 3: Production
  • 8. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production • Company is not using any Data Science Tools so far - beside Excel • A single person or small group starts using R for certain tasks • Often interns or entrants • Software decision independent from the IT-department • Non strategic decision • Colleagues, supervisors and management are excited Level 1: First contact
  • 9. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Success factors • Involve IT department as early as possible • Try to enlarge the internal Data Science Team • by training (internal, on-site, online) • by hiring • Get as soon as possible to the next level Level 1: First contact
  • 10. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Risks • IT department raises difficulties • Getting lost in ad-hoc requests • Becoming everybody's problem solver Level 1: First contact
  • 11. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production • Use Case Evaluation • Data Availability • Analytical Complexity • Business Value • Select the most promising use cases for implementation • Plan to accomplish more than one use case Level 2: Proof of Concept
  • 12. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Level 2: Proof of Concept Success Factors • Make sure that implementation is principally possible • Have your target in mind, don't get lost in details • Involve business as much as possible • Don‘t scare business with statistical terms • Keep analytic approach and business demand in line
  • 13. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Level 2: Proof of Concept Risks • Promising particular success • Sticking to your original ideas if they don‘t fit anymore • Showing preliminary results to business people • Investing too much energy in optimization and performance • Communication between Data Science and Business
  • 14. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Level 3: Production • Implementing Proof-of-Concept approaches into Production • Shift from laboratory to automation • Shift from hacking to programming
  • 15. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Level 3: Production Success Factors • Focus on software developers skills • Care much about performance • Put a first stable version on the live system before adding new features • Open a backlog for future improvements
  • 16. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Versioning Failure controll Dependency Management Documentation Package Building Staging Testing Deployment Profiling Level 3: Production Sucess Factors
  • 17. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Output Technical Implementation Analytic Level 3: Production Risks • Underestimation of effort for maintenance and bug fixing • Debugging is harder on Production systems • Appling code changes without tests on staging systems • „Unknown“ input
  • 18. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Conclusion
  • 19. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Statistics, Methods Domain- knowledge Data Science Software Development
  • 20. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Guerilla & Proof-of-Concept Statistics, Methods Domain- knowledge Software Development
  • 21. © 2010 – 2016 eoda GmbHOliver Bracht www.eoda.de Introduction | First contact | Proof of Concept | Production Statistics, Methods Domain- knowledge Production Software Development
  • 22. © 2010 – 2016 eoda GmbHOliver Bracht @eodaGmbH @eodaGmbH eodaGmbH blog.eoda.de eoda GmbH Universitätsplatz 12 34127 Kassel - Germany www.eoda.de/en info@eoda.de +49 561 202724-40 The Data Science Specialists.