TDWI - Analytics Rising March 2015 - FINAL

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Gregory Lewandowski, Robert John Lake

March 16, 2015

Analytics Rising…Plan for Success

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Cisco creates solutions built on intelligent networks that solve our customers’ challenges.

John Chambers’ (CEO) stated goal is to be the #1 IT company in the world

Cisco Systems Inc.

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Introduction

Gregory LewandowskiSenior Manager

Analytics CoE & Data Visualization (@lewandog)

Robert John LakeSenior ManagerAnalytics CoE

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Agenda

Introduction

Governing Body

Analytics CoE

Data Science

Lessons Learned

Q&A

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Gregory LewandowskiSenior Manager, GBS BI

Introduction

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Rapid Data Growth Leads to BI Challenges

Business Intelligence

Engineering

MarketingSales

Finance

Supply Chain

Human Resources

InformationTechnology

Custom BI solutions propagating within functions

1

BI skills dispersed in pockets throughout the enterprise

2

Inconsistent tools, processes, and approaches being used

3

Data multiplying in silos in offline tools and systems

4

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Journey to Analytics Excellence

Corporate InitiativeBusiness

Intelligence org formed under CFO

2009Corporate Initiative

Created global shared

services organization under COO

2012Analytics

COEAnalytics as

differentiator & driver of

growth for Cisco

2013Focus

Data Science initiative to develop skills to

capitalize on Analytics

2015

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Global Business Service – Business Intelligence

Vision: Accelerate Cisco’s competitive advantage by understanding the past, managing the present, and changing the future.

Enterprise information

management, data quality, architecture,

policy & governance

Governance

CoE for analytics, data

communication, and innovation

Analytics CoE

Establish and cultivate strategic

relationships with business

functions

Customer

Data supply chain,

solutioning & execution of

delivery services

Delivery

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BI and Analytics Governing Body

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SV

Ps

& V

Ps

Scope & Charter for Governing Structure

Steering Committee • Provide direction and sponsorship for company wide Business Intelligence priorities • Actively promote data driven decision making• Hold Operating Body accountable to commitments; serve as escalation authority.

Participation level: Sustaining 80+% active participation across high profile leaders of the Co. for 2 years

Quarterly cadence

Sr.

Dir

ec

tors Operating Committee

• Execute on direction from Steering Committee• Drive cross functional priority alignment• Facilitate change management & adoption

Monthly cadence

Steering Committee and Operating Body as Governing StructureRepresentation across all business functions

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The Results!

• Raised prominence for BI and Analytics at Cisco

• Passionate Sr. leaders across functions steering direction for the Enterprise

• Change culture and drive Enterprise transformation mindset

• Yielded prioritization of key BI / Analytics initiatives across Cisco – Analytics CoE among TOP 5

Analytics CoE

1

Corporate Hierarchies; Master Data

Management & Governance

2

Application Consolidation &

Governance

4New Business

Models Enablement

3

Relationship Management (Customer,

Partner, Supplier, Employee)

5Top BI /

Analytics Priorities

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Analytics Center of Excellence

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Data Supply Chain

Governance

Analytics

Community

Interpret &

Disseminate

Results

Foster Innovati

on & Drive

Culture Shift

Attract &

Retain Analyti

cal Talent

Branding value

of Analyti

cs

Analytics Vision: What the CoE DrivesAccelerate Cisco’s competitive advantage by understanding

the past, managing the present, and changing the future V

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Data Supply Chain

• Create a process for delivery of “analytics ready” data

• Nirvana (Data at Fingertips):

Near Immediate Access

48 hour turn-around

• Manage analytics platforms

• Extract, transform, load

• Cleanse & profile data [to a point]

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Analytics is only as good as the data – Trust in data quality is paramount

Governance

Data Stewards

Leverage data stewards as subject domain experts

Feedback

Work closely with data governance team if new policies and/or access criteria is needed

Certified Data

The Analytics CoE will consume data from approved sources

QualityMonitoring quality with a business rules engine

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Analytics Community

• Established early credibility through DataViz community

• Carry this over for Analytics CoE

• Resource for industry best practices and up-leveling skills and techniques

• Virtual Community – bring together the multitude of Analytics teams within Cisco

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Frame business problem, anticipated outcomes & value.

Assess data requirements and acquire data within

sandbox.

Deliver final reports and documents and

implement models in production

environment.

Develop data sets for testing, training &

production. Run test through model.

Identify key findings, quantify business value and create executive

summary.

Perform initial data analysis and formulate

hypothesis.

Repeatable Process for Data Analytics

Data AnalyticsProcess

Model Building

Operationalize

Model Planning

Discovery

Communicate Results

Data Prep

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Foster Innovation & Drive Culture Shift

Drive change mindset across Cisco

towards analytics

Increase risk taking – Fail fast and fail

often, learn, move on

Provide opportunities for internal

development

Drive and reward disruptive innovation

Incorporate industry

perspective and outside-in thinking

Leverage contemporary

tools

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Analytical TalentDefine Needs & Team Composition

Develop & Retain

Discover, Attract & Source

Define Roles

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Robert John LakeSenior Manager, GBS BI

Data Science

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Data ScienceCritical Components to Accelerate Success

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Rationale Services Customer Value

• How do we express value?

• How do we build a vendor strategy?

• Not about creating models and machine learning

• Focus on enabling value for our customers

• Time to first insight

• Time to return on Investment

• Less Complexity in maintenance

• Better scalability

• Availability of capabilities

• Creation of revenue

• Reduction of expenses

• Reduction of impact of Risk

• Change perception of their customers

Establish Analytics as a Service

Data ScienceCritical Components to Accelerate Success

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Data ScienceCritical Components to Accelerate Success

Continuous Learning• To retain and enhance skills

• Develop a well-rounded skillset

• Designated career path

• Work with HR to document job and career definitions

• Align skills with academic / industry standards

• Prepare to drive strategic conversations

• Contribute further to the growth and acceleration of the company

• Learn to work effectively in small groups or pods

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Data ScienceCritical Components to Accelerate Success

Cisco Data Science Program ApproachFrom Pervasive Knowledge (L0) to Expertise (L3)

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Data ScienceCritical Components to Accelerate Success

The Solutions Room “AaaS” through analytics led conversation

•Hosting workshops

− Client led hypothesis discussions

− Rapid piloting and or solution development

•Providing a customer experience

− Showcase analytics capability to customers

•Hosting interactive Quarterly Business Reviews (QBRs)

− Dynamic QBR sessions

− Interactive discussion

•Collaboration environment for Data Scientists

•Visualization discovery room

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Leverage Multiple Means to Increase AwarenessInternal & External Events, Industry Participation, Online Community

Maximum Return on InvestmentCost Optimized, Repeatable Model for Scalability & Process Improvement

Relationships & Expert SkillsHigh-Touch Client Relationship Management, Business Acumen and Technical Capabilities in a Single Team, Strong Vendor Strategy

Tangible ValueMake Money, Save Money, Make Business Partners Happy

Branding Value of AnalyticsDrive focus towards Analytics to accelerate Cisco’s competitive advantage

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Lessons Learned

Must be able to show value along the way

Be prepared to find the unexpected

Speed is essential – get started now

Fail Fast, Fail Often, Learn &

Move On

Analytics Leads to Better Questions

Change is hard – Business relationships are critical to success

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TOMORROW starts here.