iLive2014 Presentation | Casper Blicher Olsen - Internal barriers from taking action upon data - and...

Barriers preventing action-oriented analytics - and how to overcome them

!Casper Blicher Olsen

v2.0

Barriers preventing action-oriented analytics - and how to overcome them

!Specialists in motivation the users online

• Digital strategies, analysis and data visualisation • Digital Marketing • Digital Analytics • Teaching & Training !

• Over 12 years experience • Nordic: Denmark – Norway – Sweden • International Clients

Barriers preventing action-oriented analytics - and how to overcome them

Barriers preventing action-oriented analytics - and how to overcome them

It’s all about the data, right? (What the statistics say)

The digital economy last year

Source: Google Internal

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All that wonderful data Today

All that wonderful data Tomorrow

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Marketers love their data!

The (Second) Evolution of Big Data

Source: Google Trends

Then came Dan Ariely… (…with his definition of big data)

Source: Google Trends

Big DataBig Data is like Teenager Sex: Everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it… !!Quote from Dan Ariely

The impediments to becoming more data driven The adoption barriers organisations face most are managerial and cultural rather than related to data and technology.

Source: MIT Sloan Management Review

The impediments to becoming more data driven The adoption barriers organisations face most are managerial and cultural rather than related to data and technology.

Source: MIT Sloan Management Review

The impediments to becoming more data driven The adoption barriers organisations face most are managerial and cultural rather than related to data and technology.

Source: MIT Sloan Management Review

Research findings:

• Top-performing organisations are twice as likely to apply analytics to activities.

• The biggest challenges in adopting analytics are managerial and cultural.

• Visualising data differently will become increasingly valuable.

It takes more than one person

We might already have individual analytics NINJAS rocking data Chuck Norris style

…but the truth about the rest is something else! And much more boring.

Aligning data visualisation to your analytics processes for better data understanding

The definition of visual analytics From data to visuals to action

Visual analytics is the representation and presentation of data that EXPLOITS OUR VISUAL PERCEPTION ABILITIES in order to AMPLIFY COGNITION.

- Andy Kirk, author of “Data Visualisation: a successful design process”

The core principals of data visualisation From data to visuals to action

What this means…

The visual sense is our dominating sense From data to visuals to action

Source: astro.ku.dk/lys/synet.html

The core principles of data visualisation The visual elements

The core principles of data visualisation From data to visuals to action

The core principles of data visualisation From data to visuals to action

Color (Hue)

The core principles of data visualisation From data to visuals to action

Enclosure + Color (Hue)

The digital analytics maturity steps

Digital Analytics Maturity Framework Making analytics part of the organisation

Technology-centric, engineering-oriented

General Level

Collect

Clean

Convert

Integrate

Store

Report

Inspired by the work of Stephen Few

Digital Analytics Maturity Framework Making analytics part of the organisation

Human-centric, analytics-oriented

General Level

Collect

Clean

Convert

Integrate

Store

Report

Explore

Analyse

Communicate

Monitor

Predict

Technology-centric, engineering-oriented

Inspired by the work of Stephen Few

Digital Analytics Maturity Framework Making analytics part of the organisation

Human-centric, analytics-oriented

Business-centric, changing behaviour

General Level CXO Level

Collect

Clean

Convert

Integrate

Store

Report

Scale

Embed

Transform

Explore

Analyse

Communicate

Monitor

Predict

Digital Analytics Maturity Framework Making analytics part of the organisation

Technology-centric, engineering-oriented

Inspired by the work of Stephen Few

Defining a data-driven organisation From data to visuals to action

The Data-Driven Organisation

Illustration: Google GACP

Collect - Report

Explore - Predict

Scale - Transform

Defining a data-driven organisation From data to visuals to action

Defining a data-driven organisation From data to visuals to action

Going From Zero To Hero

Give the right people the data they can ACT on From data to visuals to action

Illustration: Google GACP

Access to tools and methodologies for better analysis and decisions From data to visuals to action

Illustration: Google GACP

Visualise Analyse Take Action!

Automate actions in real time From data to visuals to action

Illustration: Google GACP

Automatisation

How to asses your organisations maturity (Online Analytics Maturity Model)

Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.

Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.

Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.

Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.

Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.

Chief Marketing Officer

Digital Analyst

Marketing Manager

http://goo.gl/r7hMdH

Measure your maturity here:

Online Analytics Maturity Model Stéphane Hamel, Director of Innovation, Cardinal Path.

Case: Kleenex

How Kleenex applied action-oriented analytics COLD AND FLU CAMPAIGN

How Kleenex applied action-oriented analytics COLD AND FLU CAMPAIGN

How Kleenex applied action-oriented analytics COLD AND FLU CAMPAIGN

How Kleenex applied action-oriented analytics COLD AND FLU CAMPAIGN

What can we learn from Kleenex’s approach?

• Applying data to support an adaptive planning process beats the best ‘guesstimates’

• If you can’t find the information you need, think outside the box

• When you have the data make sure to visualise it, and deliver it to people who can take action

• Make the case an internal success story, and get other parts of the business engaged

Case: Target

How Target applied action-oriented analytics PREGNANCY PREDICTION SCORE

How Target applied action-oriented analytics PREGNANCY PREDICTION SCORE

Source:forbes.com

How Target applied action-oriented analytics PREGNANCY PREDICTION SCORE

What did Target do, and what can we learn? • In 2002 Target hired Andrew Pole as an statistician !

• Two guys from marketing: “If we wanted to figure out if a customer is pregnant, even if she didn’t want us to know, can you do that?” !

• They were able to identify about 25 different products that were indicators of pregnancy, including items like unscented lotion, vitamin supplements, hand sanitizers and washcloths.

• Andrew was able to create a model that assigned each shopper a pregnancy prediction score based on their purchases !

• This score was then used to send out relevant coupons and advertisements tailored to each woman at a specific point in her pregnancy !• Target’s Mom and Baby department skyrocketed.

Source:newyorktimes.com

Case: The HIPPO approach

Should we optimise our website for mobile devices? Two scenarios

Scenario #1 (without data)Gut feeling

Business challenge: Should we optimise our website for mobile?

Business challenge: Should we optimise our website for mobile?

Answer: In the absence of data, the HiPPO says no!

Scenario #2 (with data)Data-oriented decision making

Business challenge: Should we optimise our website for mobile?

Answer: Yes, because 11,42% of all our visits are from mobile devices

Woot! What does this mean? Oh boy!

Our mobile traffic is equivalent to: the capacity of Michigan Stadium

Takeaways

Recommendation #1 Something to take home

First, Think Biggest Focus on the biggest and highest- value opportunities

Inspiration: MIT Sloan Management Review

Recommendation #2 Something to take home

Start in the Middle Within each opportunity, start with questions, not data

Inspiration: MIT Sloan Management Review

Recommendation #3 Something to take home

Make Analytics Come Alive Embed insights to drive actions and deliver value

Inspiration: MIT Sloan Management Review

Recommendation #4 Something to take home

Add, Don’t Detract Keep existing capabilities while adding new ones

Inspiration: MIT Sloan Management Review

Recommendation #5 Something to take home

Build the Parts, Plan the Whole Use an information agenda to plan for the future

Inspiration: MIT Sloan Management Review

The core principals of data visualization From data to visuals to action

Finally…

Don’t only think about data, think about action! A key takeaway

“Information is powerful. But it is how we use it that will

define us.”- Zack Matere, Farmer (Soy, Kenya)

- Zack Matere, Farmer (Soy, Kenya)

“Information is powerful. But it is how we use it that will

define us.”

Don’t only think about data, think about action! A key takeaway

Denmark . Norway . Sweden

IIH Nordic A/S, Lille Strandstraede 61254 Copenhagen K, Denmark

www.iihnordic.com

Mail: casper@iihnordic.comCell: +45 6 1 3 1 4 0 0 7Office: +45 7 0 2 0 2 9 1 9

CASPER BLICHER OLSENDigital Analytics & Insights Lead

Thank you