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

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 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

EVIDENCE-BASED DECISIONSBasic ConceptsBasic Concepts

“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?

http://www.youtube.com/watch?v=aXV yaFmQNk

http://www.youtube.com/watch?v=ksO35s3Bffctch?v=aXV-yaFmQNk /watch?v=ksO35s3Bffc

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

24

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

e j.recker@qut.edu.auw www janrecker comw www.janrecker.comt janrecker