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Creating a Data-Driven Decision-Making Culture

Ken Raetz

Principal

Think Data Insights, LLC

• Data Platform architects

• Data Storytellers

• Microsoft SQL Server BI, Power BI

• Business Consultants – We see the pain

• IT Consultants – We know the challenges

• “Data Culture Disrupters” “Data Wranglers”

Who are we?

Who are you?

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Agenda

Our time today…

• Data Analytics Continuum – A History Lesson

• What’s happening today in analytics?

• Data Storytelling and Data Culture

• From Poor to Healthy Data Culture

• Focus on customer studies:

• Healthcare

• Supply Chain

• Finance

• Personal/Individual Strategy

A History Lesson

Descriptive

Diagnostic

Predictive

Prescriptive

Why?

What?

What could?What should?

Descriptive Analytics

Cloud options

on demand

Centralized Data

and Reporting

Reduced cost

and complexityHistorical Only

Reduced cost

and complexityMass Distribution

Reduced cost

and complexityLimited Alignment

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Diagnostic Analytics

Cloud options

on demand

Centralized Data

and Reporting

Reduced cost

and complexityCubes, Drill Down

Reduced cost

and complexityLimited Experts

Reduced cost

and complexity

One Version of

the Truth

Predictive Analytics

Cloud options

on demandForecasting

Reduced cost

and complexityStatistics Driven

Reduced cost

and complexityData Mining

Reduced cost

and complexity

Identify Outliers

and Patterns

Reduced cost

and complexityData-Driven

Prescriptive Analytics

Reduced cost

and complexityPrescribe Actions

Cloud options

on demand

Automated Data

Integration

Reduced cost

and complexityMachine Learning

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The opportunity is bigger than you may think

$1.6T data dividend available

to businesses that embrace data

over the next four years

speed

More people

New analytics

Diverse data

How?

Data source: Microsoft and IDC, April 2014

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Analytics Market Trends

$22.8b by

2020

Traditional

BI Spending Declining

Modern

BI/Analytics Platform

Emerging

Complex

data and data prep

Streaming/

real-time data

Cloud

Data

monetization / Product

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Data Storytelling

Data

Visuals

Narrative

• Know your objective

• Know your audience

• Highlight key findings

• Eliminate fluff

• Not all graphs alike

• Simplify

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Data Storytelling

• Know your objective

• Know your audience

• Highlight key findings

• Eliminate fluff

• Not all graphs alike

• Simplify

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Data Storytelling

• Know your objective

• Know your audience

• Highlight key findings

• Eliminate fluff

• Not all graphs alike

• Simplify

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Data Culture

A set of core beliefs and principles that determine how data will be

incorporated into key business processes.

The degree to which factual information is relied upon for decision-

making determines the healthiness and maturity of an organization’s

data culture.

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What is Data Culture?

• Assumption-driven decision-making

• Siloed reporting systems

• IT holds keys to sophisticated analytics

• Enterprise Data Warehouse with little self-service access

• Unreliable and inaccurate figures

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Poor Data Culture

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Perception

Business-

Owned

InsightsIT

Changing your data culture

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Education

Educate

organization on

analytics

Commitment

Data-driven

decision-making

Teams

Focus on

innovation with

data

New Data Sources

Incorporate all data possible (external

and internal)

Cloud

Leverage cloud

for scalability and

flexibility

Prototype

Short, targeted

prototype

projects

Data Quality

Data veracity

requires data

quality

commitment

Functional Analytics… At Work

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Customer Examples – Healthcare

Sepsis

Epidemic

Up to

$88kPer Case

75%

Longer patient stay

$24bAnnual

spend

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Customer Examples – Healthcare

Solution

• Early detection

• Use data to provide additional predictors of sepsis

• Arrival data

• Historic hospital data

• External data

• Notify delivery team at point-of-care for at-risk patients

Return on Investment?

• Costs lowered to $3,000 per case

• Early detection significantly reduces risk of fatality

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Customer Examples – Healthcare

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

0 5 10 15 20 25 30 35 40

Survival Rate By Hour Undiagnosed

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Customer Examples – Supply Chain

Lost revenue due

to insufficient

supply

Supplier

Performance

On-Time Delivery

Demand Planning

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Customer Examples – Supply Chain

Product Optimization

Customer/Geography Planning

Optimized Supplier Sourcing

Cost-Reducing Logistics Planning

Profit-driven inventory

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Customer Examples – Supply Chain

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Customer Examples – Finance

Streamline

Processes

Customer Segments

Capital Strategy

Stock Price

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• Identify and limit high risk markets, customers

• Leverage data in acquisition scenarios

• Collection strategy for high-risk customers

Manage Risk

• Reduce cost, increase revenue

• Use data to identify inefficiencies

• Model approaches to optimize processes

Streamline Processes

• Data-driven manufacturing

• Tie capital to KPI/objectivesCapital Strategy

• Monitor historical/future events

• Manage key accounts that could affect stock priceStock Price

• Optimize target marget acquisition

• Model-driven customer segmentation

• Identify new segments

Customer Segments

Customer Examples – Finance

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Decentralizing Analytics – The team of the future

Director/Manager

Analytics

Consultant

Data Science

Data

Storytellers

Citizen Data

Scientists

Citizen Data Scientist

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Citizen Data Scientist

“A person who creates or generates models that use

advanced diagnostic analytics or predictive and

prescriptive capabilities, but whose primary job

function is outside the field of statistics and analytics.”

Gartner

Individual/Personal Strategy

• Identify data opportunities (monetization, productize)

• Promote culture of Citizen Data Scientist with peers

• Engage business

• Learn about data quality

• Master the art of data storytelling

• Learn UX principles

• Learn business – MBA, books, videos

• Learn data science (school, online video)

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• Speaks business and IT

• Rapid solutions

• Growing in data science

• Adheres to standards

• Support data quality initiatives

• Trains/mentors others

• Promotes culture of Data

Democratization

Citizen Data Scientist (aka “Data Wrangler”)

Analytics – A New Role

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Creating a Data-Driven Decision-Making Culture

Ken Raetz

Principal

Think Data Insights, LLC