In old economy companies, the introduction of R is typically a button-up process that follows a pattern of three major stages of maturity: At the first stage, guerrilla projects use R parallel to the "official" IT environment. The usage of R is often initiated by interns, student assistants or newly recruited graduates. At the second stage, when the results of the guerrilla projects attract the attention of business departments, R is used as analytic language in proof-of-concept projects. When the proof-of-concept has been successful, the outcome shall be transferred to the production system. At this stage R is being introduced “officially” to the IT environment. While the first and second level of maturity usually do not cause any major problems, the step to the third level is most crucial for the long term success of the implementation of R. This talk will focus on how to master the switch from proof-of-concept to production. It will show based on real world experiences typical road blocks as well as the most important success factors.

1. © 2010 – 2016 eoda GmbH
Implementing R in old economy companies:
How to master the road to production
Oliver Bracht | Chief Data Scientist

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Introduction | Guerilla | 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 GmbHwww.eoda.de
Introduction | Guerilla | Proof of Concept | Production
Core
Pioneer Requirement
Data Science Lab
Introduction of R

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Introduction | Guerilla | Proof of Concept | Production
Data Science Lab
Guerilla Requirement
• Driver:
• Root:
• Data Sources:
• Motivation:
• Mindset:
• Time-to-production:
Core
Already there
Founder and Top-Management
Center
All available
Corporate objective
A natural thing
Introduction of R

5. © 2010 – 2016 eoda GmbHwww.eoda.de
Introduction | Guerilla | Proof of Concept | Production
Core Data Science Lab
Requirement
• Driver:
• Root:
• Data Sources:
• Motivation:
• Mindset:
• Time-to-production:
Requirement
oriented
Data Science
LabReady when ready
Management
Top
Sandbox
Research
Let‘s try
Introduction of R

6. © 2010 – 2016 eoda GmbHwww.eoda.de
Introduction | Guerilla | Proof of Concept | Production
Core Data Science Lab
Requirement
• Driver:
• Root:
• Data Sources:
• Motivation:
• Mindset:
• Time-to-production:
Requirement
Short
Business lines or management
Top
Production / Business
Solving current business problems
Reduce risk by planning / ROI
Introduction of R

7. © 2010 – 2016 eoda GmbHwww.eoda.de
Introduction | Guerilla | Proof of Concept | Production
Core Data Science Lab
Requirement
• Driver:
• Root:
• Data Sources:
• Motivation:
• Mindset:
• Time-to-production:
Core Business
Pioneer
Long
Single Business unit(s)
Bottom
csv copies
Pioneer‘s conviction
Yes, we can
Introduction of R

8. © 2010 – 2016 eoda GmbHwww.eoda.de
Introduction | Guerilla | Proof of Concept | Production
Core Data Science Lab
Pioneer Requirement
New Economy
Enterprises
Old Economy
Introduction of R

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Introduction | Guerilla | Proof of Concept | Production
The pioneer‘s road to production
Level 1: Guerilla
Stakeholders: Data Science
Level 2: Proof of Concept
Stakeholders: Data Science + Business
Level 3: Production
Stakeholders: Data Science + Business + IT

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Introduction | Guerilla | 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: Guerilla

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Introduction | Guerilla | 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: Guerilla

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Introduction | Guerilla | Proof of Concept | Production
Risks
• IT department raises difficulties
• Getting lost in ad-hoc requests
• Becoming everybody's problem solver
Level 1: Guerilla

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Introduction | Guerilla | 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

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Introduction | Guerilla | 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

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Introduction | Guerilla | 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

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Introduction | Guerilla | Proof of Concept | Production
Level 3: Production
• Implementing Proof-of-Concept approaches into Production
• Shift from laboratory to automation
• Shift from hacking to programming

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Introduction | Guerilla | Proof of Concept | Production
Input
Level 3: Production
Business Implementation
Output
Technical Implementation
Analytic

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Introduction | Guerilla | Proof of Concept | Production
Human /
Machine
Level 3: Production
Business Implementation
Technical Implementation
Analytic Human /
Machine

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Introduction | Guerilla | 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

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Introduction | Guerilla | Proof of Concept | Production
Versioning Failure controll
Dependency Management Documentation
Package Building Staging
Testing Deployment
Profiling
Level 3: Production
Sucess Factors

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Introduction | Guerilla | 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

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Introduction | Guerilla | Proof of Concept | Production
Conclusion

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Introduction | Guerilla | Proof of Concept | Production
Statistics,
Methods
Domain-
knowledge
Data Science
Software
Development

24. © 2010 – 2016 eoda GmbHwww.eoda.de
Introduction | Guerilla | Proof of Concept | Production
Guerilla & Proof-of-Concept
Statistics,
Methods
Domain-
knowledge
Software
Development

25. © 2010 – 2016 eoda GmbHwww.eoda.de
Introduction | Guerilla | Proof of Concept | Production
Statistics,
Methods
Domain-
knowledge
Production
Software
Development

26. © 2010 – 2016 eoda GmbH
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