Turning Business Intelligence Into Actionable Insights

Turning Business Intelligence Into

Actionable Insights

#FutureofBI

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Panelists

Dustin SmithProduct Marketing & Community Manager Tableau Software

MODERATOR

Greg Girard Program Director

Omni-Channel Analytics Strategies

Alicia Fiorletta Senior Editor

Retail TouchPoints

Turning Insights into Actions—A Big Data and Analytics Perspective

Greg GirardProgram Director

Omni-Channel Retail Analytics Strategy

7

Big data is big, but not all that big a deal

© IDC Retail Insights Visit us at IDC-ri.com

After all, what’s data without analytics!

8

Where’s your big data?


Sales Analysis $ 5,000,000,000 Total Revenue

$14 $/Transaction 357,142,857 Transactions

20 Attributes/Transaction 7,142,857,143 Transaction Attributes

3 Items/Transactions10 Attributes/Item

10,714,285,714 Item Transaction Attributes

Marketing Decisions4,000 Products

10 Promotion Types20 Channels/Touch Points20 Customer Segments

16,000,000 Intersections/Promotion Event 52 Events/Year 832,000,000 Intersections/Year

Inside and outside your enterprise!

9

Growing Evidence for the Power of Analytics Proficiency

© IDC Visit us at IDC.com and follow us on Twitter: @IDC

Leaders

Laggards

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Fact Finders

Fact Finders

Fumblers

Fumblers

Percent of RespondentsLeaders vs Laggards4

New analysis methods on same type of data

0%

Same analysis methods on Same type of data

-14%

Same analysis methods on New type of data

7%

New analysis methods on New type of data

6%

Sources: •1. Analytical Orientation and Competitiveness: The Difference Between Fact Finders and Fumblers, IDC #227524•2. Strength in Numbers: How Does Data-Driven Decision making Affect Firm Performance? MIT Center for Digital Business•3. IDC and Computerworld 2013 Business Analytics Survey•4. Take Care of Your Quants: Focusing Data Warehousing Resources on Quantitative Analysts Matters, IDC #227524

Benefits3

45% of organizations achieve quantifiable benefits within 6 months

90% of organizations value of benefits met or exceeded expectations

Data-driven companies2

5% more productive6% more profitable

10© IDC Visit us at IDC.com and follow us on Twitter: @IDC

4 V’s of the BDA ECOSYSTEMBUSINESS PROCESSDATA CREATION

END USERSPRODUCERS

VO

LUM

E VELO

CITY VARIETY

VALU

E

11© IDC Visit us at IDC.com and follow us on Twitter: @IDC

IDC BDA ECOSYSTEMBUSINESS PROCESSINFO PROCESSINGDATA ACQUISITIONDATA CREATION

END USERSANALYSTS / SCIENTISTSARCHITECTS / ENGINEERSPRODUCERS

Shared Nothing Scale-out Storage + SSD

MPP + In-Memory Compute

Hadoop

Hi-Speed / -Resiliency Networking

Converged Infrastructure

Cloud

Non-relational DWH

SYSTEMS INTEGRATION

VO

LUM

E VELO

CITY VARIETY

OBJECTIVES

Stream Processing

Event Management

Data Exploration

Contextualized Data

Modeling / Scenarios

Forecasting

DELIVERY MODELS

Access-AnywhereAnalytics Services

Context-Aware Business Applications

ON-DEMAND

Location-Based Services

Alert and Respond

PUSH

Workflow and Interaction Automation

Smart devices and systems

EMBEDDED

Email and Messaging

Mobile Apps Data

Transaction and Usage Logs

Machine and Sensors

Geolocation

Relationships and Social Influence

Real-time Events

Deep Insights

VALU

E

12

The Quest for Maturity

Where are we? Why climb higher?

How did they do it?


can we

13

While we don’t climb mountains….


In a broad societal and economic context retail is at the epicenter of emerging BDA opportunities.

Two classes of retailers are emerging, "BDA haves" and "BDA have nots", immediately making BDA a defining basis of retail competitive advantage.

Higher BDA maturity improves chances of achieving expected or greater-than-expected benefits.

Top 10 distinguishing traits of high achievers span intent, people, process, technology, and data.

14

Dissecting BDA Maturity: “5 by 5”

Dimensions Levels

Ad Hoc Opportunistic Repeatable Managed Optimized

People

Process

Data

Technology

Intent


~90 Sub-dimensions

15


Dimensions Levels


People

Experiment, silos, pilots

Requirements, off-budget funding,

inefficient allocation

Budgets, documents, stakeholders

Metrics-informed

investment, standards

Continuous coordination,

process improvement

Process

Data

Technology

Intent


16


Dimensions Levels


People Skills, collaboration, org structure, training, culture, leadership

Process Data consolidation, analysis, dissemination, consumption, decision-making

Data Quality, relevance, availability, reliability, governance, security, accessibility

Technology Appropriateness, applicability, integration, standards, performance, architecture

Intent Strategy, budgeting, metrics, sponsorship, program/investment justification


17

Some have it, some not so much


FIGURE 1BDA Maturity Distribution: Retail

n = 200Source: IDC's Big Data and Analytics Maturity Benchmark Survey, 2013

18

BDA Maturity Increases Success Rates


n = 200Source: IDC's Big Data and Analytics Maturity Benchmark Survey, 2013

Definitions• Highest achievers.

Recent BDA projects met or exceeded expectations

• Low achievers. Recent BDA project did not meet expectations or delivered no benefits

*Differential = (Repeatable + Managed + Optimized)Highest Achievers - (Repeatable + Managed + Optimized)Low Achievers

1st

3rd

5th

2nd

4th

Skew right

Skew left

19

Keep All Five Dimensions Aligned


20

Essential Guidance for Retail BDA Intent

• Set and Manage BDA Strategy at the Enterprise Level• Fund and Budget BDA Programs Annually with Flexibility

Data• Exploit Enterprise Data Assets• Introduce New Data Types and Analytic Methods

Technology• Ensure Users — Especially Analysts — Are Satisfied with the Tools of Their Trade• Complement BDA Technology with Mobility

People• Complement Skills and Expertise with a Culture of Collaboration• Apply BDA Insights to Management Decision-Making and Customer Interactions• Focus on Collaborative Governance and Closed-Loop Management across IT, LOB and

Analytics

Process• Start with Information Management, Application Development, and Strategy and Planning• Finish with Information Consumption — The Last Mile of BDA Success


21

Contact Information


Greg Girard, Program Director

[email protected]

@gregorydgirard

www.idc-ri.com

https://idc-insights-community.com/retail

mailto:[email protected]

http://www.idc-ri.com/

https://idc-insights-community.com/retail

Help people see and understand their data

#FutureofBI

Q & A

#FutureofBI

Q & A //Panelists

Dustin SmithProduct Marketing & Community Manager Tableau Software

MODERATOR

Greg Girard Program Director

Omni-Channel Analytics Strategies

Alicia Fiorletta Senior Editor

Retail TouchPoints

#FutureofBI

Thanks for attending!View and download this presentation at:

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Turning Business Intelligence Into Actionable Insights

Marketing

Transcript of Turning Business Intelligence Into Actionable Insights