The Evidenc e -Based Organization: A Platform for Innovation A Platform for Innovation Professor Dr Jan Recker Woolworths Chair of Retail Innovation Information Systems School Queensland University of Technology Information Systems School, Queensland University of Technology
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The Evidence-Based Organization: A Platform for Innovation
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The Evidence-Based Organization: APlatform for InnovationA Platform for Innovation
Professor Dr Jan ReckerWoolworths 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 tosurviving a rapidly changing retail landscape according to Woolworths Ltd CEOg p y g g p gGrant O'Brien.Mr O'Brien addressed the QUT Business Leaders' Forum today saying theinvestment of nearly $1 million to fund a Chair of Retail Innovation would helpthe sector better recognize the needs of customers
− Relying on status (confidence) rather than facts (evidence)
− Using flawed decision models− Using flawed decision models
+ Seeking an understandingof 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 by If 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 Barksdaleformer CEO Netscape
“Relying on valid and reliable evidenceRelying on valid and reliable evidenceand translating them into practices thatsolve problems and innovatesolve problems and innovateorganizations.”
Levels of EvidenceWhich le el is the basis for o r decisions?Which level is the basis for your decisions?
Some examplesWhich le el is the basis for o r decisions?Which level is the basis for your decisions?
Some examplesSome examplesSocial media usage statistics(Source: David Cowling, SocialMediaNews.com.au, 2013)Social network Feb 2012 Feb 2013Facebook 10,703,160 11,677,680YouTube 11,000,000 11,000,000YouTube 11,000,000 11,000,000Blogspot 3,500,000 3,200,000Tumblr 1,100,000 2,800,000Li k dI 2 220 000 2 400 000LinkedIn 2,220,000 2,400,000Twitter 1,800,000 2,200,000Instagram 250,000 1,101,667Flickr 920,000 850,000Pinterest 650,000 630,000Google+ (estimates) 1 200 000 340 000Google+ (estimates) 1,200,000 340,000Myspace 520,000 310,000
Some examplesSome examples
Social media “noise” has no Social media noise has no measurable impact on short-term sales.(But Digital ROI remains key measure for media selection and marketing strategies.)
BUT BEWARENot 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 byproject 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 understandingof true cause-effect y
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 l since 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 ss p
erfo
rman
ce
Positive Deviant
Positive Deviant
y ytrulysuccessful?
Which true Sal
es p
roce
s
Average
root causescan we insertelsewhere?
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 perspectivesRigorous scientific principlesQuality empirical evidenceIncreased research bandwidthUnbiased observationExplores evidence internallyand externally
Ability to develop capability.
Requirements for evidence-based innovation decisions
Data awarenessData awarenesswhat 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 conceptsValidity 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 informationDetermine appropriate analyses
Identify appropriate visualizations
Consider limitations and assumptions
Communicate effectively and accurately23 |
Wrap-Up: From Confidence to EvidenceWrap Up: From Confidence to EvidenceMoving to reliable, valid and ultimately credibledecisionsdecisions.
Means levelling of hierarchiesMeans levelling of hierarchies.
Requires data and scientific analysis capabilities.q y pCan 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
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Key LessonsInnovations require decisions about unstructured andInnovations require decisions about unstructured and complex problems. Risk of failure is high.Evidence-based decision-making increases ginnovation 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 InnovationInformation Systems SchoolQueensland University of Technology