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The Evidence-Based Organization:
APlatform for InnovationAPlatform for Innovation
Professor Dr Jan Recker
Woolworths Chair of Retail Innovation
Information Systems School Queensland University of TechnologyInformation Systems School, Queensland University of Technology
Innovation and Evidence pave the way to the future
Innovation, research and customer‐orientated transformation are key to
surviving a rapidly changing retail landscape according to Woolworths Ltd CEOg p y g g p g
Grant O'Brien.
Mr O'Brien addressed the QUT Business Leaders' Forum today saying the
investment of nearly $1 million to fund a Chair of Retail Innovation would help
the sector better recognize the needs of customers
http://www.news.qut.edu.au/cgi‐bin/WebObjects/News.woa/wa/goNewsPage?newsEventID=56077
the sector better recognize the needs of customers.
Innovation and Evidence pave the way to the future
http://hbr.org/2012/10/data‐scientist‐the‐sexiest‐job‐of‐the‐21st‐century/ar/pr
Innovation and Evidence pave the way to the future
http://statements.qld.gov.au/Statement/2013/6/24/queensland‐looking‐for‐data‐gurus
Evidence means ability to innovate
Recognizing the relevance of Evidence
− Relying on status (confidence) rather than facts (evidence)
− Using flawed decision models− Using flawed decision models
+ Seeking an understanding
of true cause-effect relations
+ Realizing the availability of potential evidence
+ O i t diti i t iti f lkl d l f th b+ Opposing tradition, intuition, folklore and rules of thumb
“If the decision is going to be made byIf the decision is going to be made by
facts, then everyone’s facts […]are equal.
If the decision is going to be made on the
basis of people’s opinions, then mine count
for a lot more.“ James Barksdale
former CEO Netscape
EVIDENCE-BASED DECISIONSBasic ConceptsBasic Concepts
“Relying on valid and reliable evidenceRelying on valid and reliable evidence
and translating them into practices that
solve problems and innovatesolve problems and innovate
organizations.”
Levels of Evidence
Which le el is the basis for o r decisions?Which level is the basis for your decisions?
Some examples
Which le el is the basis for o r decisions?Which level is the basis for your decisions?
http://www.youtube.com/wa
tch?v=aXV yaFmQNk
http://www.youtube.com
/watch?v=ksO35s3Bffctch?v=aXV-yaFmQNk /watch?v=ksO35s3Bffc
Some examplesSome examples
Social media usage statistics
(Source: David Cowling, SocialMediaNews.com.au, 2013)
Social network Feb 2012 Feb 2013
Facebook 10,703,160 11,677,680
YouTube 11,000,000 11,000,000YouTube 11,000,000 11,000,000
Blogspot 3,500,000 3,200,000
Tumblr 1,100,000 2,800,000
Li k dI 2 220 000 2 400 000LinkedIn 2,220,000 2,400,000
Twitter 1,800,000 2,200,000
Instagram 250,000 1,101,667
Flickr 920,000 850,000
Pinterest 650,000 630,000
Google+ (estimates) 1 200 000 340 000Google+ (estimates) 1,200,000 340,000
Myspace 520,000 310,000
Some examplesSome examples
Social media “noise” has noSocial media noise has no
measurable impact on short-term
sales.
(But Digital ROI remains key measure
for media selection and marketing
strategies.)
BUT BEWARE
Not all decisions require
scientific examination…
What is your source of evidence?y
E t l External
 Where have other organizations produced relevant
evidence?
 Where has research produced relevant evidence?
 Typically the focus of R&D departments or
collaborations with research institutes
 Internal
 Where do we produce relevant evidence?
 Where can we produce relevant evidence?
Example – creating evidencep g
Forecasting for Promotion PlanningForecasting for Promotion Planning
Example – status quop q
 Promotion planning method
decided by
project team
 Relying on status
(confidence) rather than
facts (evidence)project team
 Method based on linear
regression model
facts (evidence)
 Using flawed decision
modelsregression model
 No systematic review of
accuracy
models
 Seeking an understanding
of true cause-effecty
performed
 conducted daily for 30,000
relations
 Realizing the availability of
items across 1,000 stores
 “we have used this system
i 2004 d it h
potential evidence
 Opposing tradition,
i t iti f lkl d lsince 2004 and it has
served us well”
intuition, folklore and rules
of thumb
Example – creating evidencep g
What is your source of evidence?y
E t l External
 Where have other organizations produced relevant
evidence?
 Where has research produced relevant evidence?
 Typically the focus of R&D departments or collaborations
with research institutes
 Internal
 Where do we produce relevant evidence?
 Where can we produce relevant evidence?
Example – find your internal evidencep y
“What can we learn about success
from within our own company?”from within our own company?
Inserting scientific principles
Positive Deviant
Inserting scientific principles
 What is the
evidence for
success?
Positive Deviant
Positive Deviant
Positive Deviant
Positive Deviant
 Who is truly
successful?
 Why are they
ssperformance
Positive Deviant
Positive Deviant
y y
truly
successful?
 Which true
Salesproces
Average
root causes
can we insert
elsewhere?
Number of customers
Finding the True Root Causesg
What Causes Performance?
 “It’s not necessarily the process”
 everyone follows the same process model everyone follows the same process model
 “It’s not the competition”
 process performance independent from local context
 Individual motivation and the willingness to Individual motivation and the willingness to
‘do something extra’
 Clever use of mark-downs
 Culture: collaboration and communication between Culture: collaboration and communication between
departments
 Exchange of ideas inter-departmental
 Creativity: finding new solutions for products Creativity: finding new solutions for products,
display and service; willingly deviate from
standardized process.
 Exchange of knowledge between stores Exchange of knowledge between stores
The Underlying Model: “Research as a Service” 
Inserting scientific principles into emerging evidence‐
b d i tibased organizations.
Research as an innovation support serviceResearch as an innovation support service.
Novel conceptual perspectives
Rigorous scientific principles
Quality empirical evidence
Increased research bandwidth
Unbiased observation
Explores evidence internally
and externally
Ability to develop capability.
Requirements for evidence-based
innovation decisions
Data awarenessData awareness
what data is appropriate?
What data is available?
What is the quality of available data?What is the quality of available data?
The ability to understand scientific concepts
Validity and reliability
St ti ti l i ifi d l iStatistical significance and sample size
Replication and bias
The ability to analyze, interpret and evaluate statistical information
Determine appropriate analyses
Identify appropriate visualizations
Consider limitations and assumptions
Communicate effectively and accurately
23 |
Wrap-Up: From Confidence to EvidenceWrap Up: From Confidence to Evidence
Moving to reliable, valid and ultimately credible
decisionsdecisions.
Means levelling of hierarchiesMeans levelling of hierarchies.
Requires data and scientific analysis capabilities.q y p
Can be provided by university and research institutions, but are
also increasingly sought as internal capability.
Allows capitalizing on external and internal
evidence for organizational innovation.g
24
Key Lessons
Innovations require decisions about unstructured andInnovations require decisions about unstructured and
complex problems. Risk of failure is high.
Evidence-based decision-making increasesg
innovation reliability, credibility and ultimately
chance of success.
Y d h t b t t ilYou do have access to – but not necessarily
awareness of – internal and external evidence.
Data scientists are becoming an essential resourceData scientists are becoming an essential resource.
Prof. Jan Recker
Woolworths Chair of Retail Innovation
Information Systems School
Queensland University of Technology
e j.recker@qut.edu.au
w www janrecker comw www.janrecker.com
t janrecker

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The Evidence-Based Organization: A Platform for Innovation

  • 1. The Evidence-Based Organization: APlatform for InnovationAPlatform for Innovation Professor Dr Jan Recker Woolworths Chair of Retail Innovation Information Systems School Queensland University of TechnologyInformation Systems School, Queensland University of Technology
  • 2. Innovation and Evidence pave the way to the future Innovation, research and customer‐orientated transformation are key to surviving a rapidly changing retail landscape according to Woolworths Ltd CEOg p y g g p g Grant O'Brien. Mr O'Brien addressed the QUT Business Leaders' Forum today saying the investment of nearly $1 million to fund a Chair of Retail Innovation would help the sector better recognize the needs of customers http://www.news.qut.edu.au/cgi‐bin/WebObjects/News.woa/wa/goNewsPage?newsEventID=56077 the sector better recognize the needs of customers.
  • 6. Recognizing the relevance of Evidence − Relying on status (confidence) rather than facts (evidence) − Using flawed decision models− Using flawed decision models + Seeking an understanding of true cause-effect relations + Realizing the availability of potential evidence + O i t diti i t iti f lkl d l f th b+ Opposing tradition, intuition, folklore and rules of thumb “If the decision is going to be made byIf the decision is going to be made by facts, then everyone’s facts […]are equal. If the decision is going to be made on the basis of people’s opinions, then mine count for a lot more.“ James Barksdale former CEO Netscape
  • 7. EVIDENCE-BASED DECISIONSBasic ConceptsBasic Concepts “Relying on valid and reliable evidenceRelying on valid and reliable evidence and translating them into practices that solve problems and innovatesolve problems and innovate organizations.”
  • 8. Levels of Evidence Which le el is the basis for o r decisions?Which level is the basis for your decisions?
  • 9. Some examples Which le el is the basis for o r decisions?Which level is the basis for your decisions? http://www.youtube.com/wa tch?v=aXV yaFmQNk http://www.youtube.com /watch?v=ksO35s3Bffctch?v=aXV-yaFmQNk /watch?v=ksO35s3Bffc
  • 10. Some examplesSome examples Social media usage statistics (Source: David Cowling, SocialMediaNews.com.au, 2013) Social network Feb 2012 Feb 2013 Facebook 10,703,160 11,677,680 YouTube 11,000,000 11,000,000YouTube 11,000,000 11,000,000 Blogspot 3,500,000 3,200,000 Tumblr 1,100,000 2,800,000 Li k dI 2 220 000 2 400 000LinkedIn 2,220,000 2,400,000 Twitter 1,800,000 2,200,000 Instagram 250,000 1,101,667 Flickr 920,000 850,000 Pinterest 650,000 630,000 Google+ (estimates) 1 200 000 340 000Google+ (estimates) 1,200,000 340,000 Myspace 520,000 310,000
  • 11. Some examplesSome examples Social media “noise” has noSocial media noise has no measurable impact on short-term sales. (But Digital ROI remains key measure for media selection and marketing strategies.)
  • 12. BUT BEWARE Not all decisions require scientific examination…
  • 13. What is your source of evidence?y E t l External  Where have other organizations produced relevant evidence?  Where has research produced relevant evidence?  Typically the focus of R&D departments or collaborations with research institutes  Internal  Where do we produce relevant evidence?  Where can we produce relevant evidence?
  • 14. Example – creating evidencep g Forecasting for Promotion PlanningForecasting for Promotion Planning
  • 15. Example – status quop q  Promotion planning method decided by project team  Relying on status (confidence) rather than facts (evidence)project team  Method based on linear regression model facts (evidence)  Using flawed decision modelsregression model  No systematic review of accuracy models  Seeking an understanding of true cause-effecty performed  conducted daily for 30,000 relations  Realizing the availability of items across 1,000 stores  “we have used this system i 2004 d it h potential evidence  Opposing tradition, i t iti f lkl d lsince 2004 and it has served us well” intuition, folklore and rules of thumb
  • 17. What is your source of evidence?y E t l External  Where have other organizations produced relevant evidence?  Where has research produced relevant evidence?  Typically the focus of R&D departments or collaborations with research institutes  Internal  Where do we produce relevant evidence?  Where can we produce relevant evidence?
  • 18. Example – find your internal evidencep y “What can we learn about success from within our own company?”from within our own company?
  • 19. Inserting scientific principles Positive Deviant Inserting scientific principles  What is the evidence for success? Positive Deviant Positive Deviant Positive Deviant Positive Deviant  Who is truly successful?  Why are they ssperformance Positive Deviant Positive Deviant y y truly successful?  Which true Salesproces Average root causes can we insert elsewhere? Number of customers
  • 20. Finding the True Root Causesg
  • 21. What Causes Performance?  “It’s not necessarily the process”  everyone follows the same process model everyone follows the same process model  “It’s not the competition”  process performance independent from local context  Individual motivation and the willingness to Individual motivation and the willingness to ‘do something extra’  Clever use of mark-downs  Culture: collaboration and communication between Culture: collaboration and communication between departments  Exchange of ideas inter-departmental  Creativity: finding new solutions for products Creativity: finding new solutions for products, display and service; willingly deviate from standardized process.  Exchange of knowledge between stores Exchange of knowledge between stores
  • 22. The Underlying Model: “Research as a Service”  Inserting scientific principles into emerging evidence‐ b d i tibased organizations. Research as an innovation support serviceResearch as an innovation support service. Novel conceptual perspectives Rigorous scientific principles Quality empirical evidence Increased research bandwidth Unbiased observation Explores evidence internally and externally Ability to develop capability.
  • 23. Requirements for evidence-based innovation decisions Data awarenessData awareness what data is appropriate? What data is available? What is the quality of available data?What is the quality of available data? The ability to understand scientific concepts Validity and reliability St ti ti l i ifi d l iStatistical significance and sample size Replication and bias The ability to analyze, interpret and evaluate statistical information Determine appropriate analyses Identify appropriate visualizations Consider limitations and assumptions Communicate effectively and accurately 23 |
  • 24. Wrap-Up: From Confidence to EvidenceWrap Up: From Confidence to Evidence Moving to reliable, valid and ultimately credible decisionsdecisions. Means levelling of hierarchiesMeans levelling of hierarchies. Requires data and scientific analysis capabilities.q y p Can be provided by university and research institutions, but are also increasingly sought as internal capability. Allows capitalizing on external and internal evidence for organizational innovation.g 24
  • 25. Key Lessons Innovations require decisions about unstructured andInnovations require decisions about unstructured and complex problems. Risk of failure is high. Evidence-based decision-making increasesg innovation reliability, credibility and ultimately chance of success. Y d h t b t t ilYou do have access to – but not necessarily awareness of – internal and external evidence. Data scientists are becoming an essential resourceData scientists are becoming an essential resource.
  • 26. Prof. Jan Recker Woolworths Chair of Retail Innovation Information Systems School Queensland University of Technology e j.recker@qut.edu.au w www janrecker comw www.janrecker.com t janrecker