Advancing the analytics maturity curve at your organization

Intended for Knowledge Sharing only

Advancing the Analytics Maturity in

your organizationSep 2017

> México | Ciudad de México

Disclaimer:

Participation in this summit is purely on personal basis and is not meant to represent VISA’s position on

this or any other subject and in any form or matter. The talk is based on learning from work across

industries and firms. Care has been taken to ensure no proprietary or work related information of any

firm is used in any material.

Director, Insights at Visa, Inc.

Enable Decision Making at the

Executives/ Product/Marketing level via

actionable insights derived from Data.

RAMKUMAR RAVICHANDRAN



Do these memes ring a bell?



IGNORANCE: I GOT DATA SCIENTISTS FOR PREDICTIONS, JUST GIVE ME MY REPORTS!



IDENTITY CRISIS: REPORTING, DATA ANALYSES, STATISTICS, ALGORITHMS, TESTS???



ACCOUNTABILITY: DATA BAD, ANALYTICS SCREWED UP! NUMBERS UP, “WE” DID IT!



BUDGET 101: COST SHOULD BE KEPT LOW & REVENUE SHOULD BE INCREASED!



AND YEAH - LET’S FIRE ANALYSTS AND GET ARTIFICIAL INTELLIGENCE!!!



Analytics is the bellweather for an organization



ANALYTICS IS A LIVING, BREATHING & GROWING ORGANISM…

https://www.intel.com/content/dam/www/public/us/en/documents/guides/analytics-planning-guide.pdf

https://www.intel.com/content/dam/www/public/us/en/documents/guides/analytics-planning-guide.pdf



A TYPICAL EXAMPLE OF A “MATURE” ANALYTICS ORGANIZATION…

From Business Operations side

• Every major decision has been quantified for

impact (expected incremental over run-rate),

supported with context (user demand),

validated in-market and any historical

precedent.

• Optimal paths planned out for next ‘x’ moves

– Leading indicators monitored and response

paths worked out (Stop/Scale/Change).

• Delivery model for insights and Response

model customized for stakeholders.

• Agility of the business to respond to industry

events, competitor actions, customer

demands highest, since the business drivers

and ownership have been modulated and

multi variate tested & mapped - Pivoting, new

Product/UX, Pricing, campaigns.

• A knowledge bank/idea marketplace for

employees to quickly prototype, iterate and

innovate at scale.

From the Analysts side

• Analytics is a “Strategy” function not just

Support or Product - everyone knows the

“why” and “what will happen” and “what if

we don’t”.

• A driver of Organizational Culture –

Accountability/Transparency,

Collaboration/Assistance, Innovation/Change

Management.

• Doesn’t need to justify investment in

learning, but everyone knows why Analytics is

in their self-interest!

• Analytics is so fine-tuned that it can be

packaged and sold out as a Product to the

industry, e.g., Hive/Google 360!

• Cognitive ready



Interesting, but can you pull it off really?



CHANGE MANAGEMENT PLAYBOOK|STRATEGY

www.theadanswer.com www.flaticon.comwww.aetholdings.com

STRATEGY EXECUTION TRANSFORMATION

Source:

http://www.theadanswer.com/services/branding/

http://www.flaticon.com/free-icons/road_2

https://www.aetholdings.com/transformation/



FIRST STEP IS TO UNDERSTAND, WHY & WHAT WILL END STATE LOOK LIKE…

• Cognitive Function

• Productization/Monetization

• Brand Capital

COMPONENTS DETAILS

Goals• Expected outcome: Business Agility, Strategic, Engagement

• KPI: End-to-end speed, cost efficiency, ability to handle scale,

Stakeholder NPS

Success Criteria • Time bound, Program RoI, NPS (Transitionary), Direct Revenue

Readiness

Assessment

• Baselining the current maturity level

• Biggest bottlenecks across BUs

• Customer “adopt”-ability

• Capability sizing (People-Process-Technology-Culture)

Evaluation Criteria

for Use cases/BU

• Data reliability: Sufficiency, complexity, pipeline reliability,

signal noise/chaos

• Brand Value of Partner BU (Executive Buy-in)

• Need: Repetitiveness/portability, Scale, Speed, Complexity?

• Speed & Resources

• Cognitive readiness

End State



…FOLLOWED BY A QUICK AUDIT EXERCISE

Sl. No. Component Details

1 Estimated benefit sizing“x% strategic decisions based on run-rates and caused us to delay the launch of a major

business line. By launching it earlier, we can increase Revenue by 10%”

2 Problem Statement“Different BUs use different measurement framework, data repositories and lack of

understanding of system dynamics causes us to repeat ideas that had failed in the past”

3 Analytics AuditInput (data size/reliability/noise), Need(Automation, Prediction, Prescription, AI), Tech

Stack, Estimated Opportunity missed, Engagement model, Delivery Framework

4 Partner BU Nirvana Automation, Self Serve, Cognitive, Productization, Branding

5 Partner BU Readiness People, Process, Technology, Culture, Strategic Vision

6 Support Executive, Leadership, Line Managers

7 Competitive benchmarking Can the current set-up work with some changes? Does it need transition?

8 What if we don’t? If we let it be way it is, does it impact big picture by much?

9Change/Integration

ManagementCosts/Speed/Dependencies & RoI

10 Project ManagementDelivery & Deployment steps, Milestones, Success Criteria, RASCI assignments, Executive

Sponsors, Communications Management



…TO COME UP WITH AN ACTION PLAN TO PROVE BENEFIT OF UPLEVELING

PICK

✓ Interview: Stakeholder discussions to find out pressing questions

✓ Evaluate: Per the checklist in the previous slide

✓ Prioritize: Requester; Urgency; Impact (RoI); Investment

✓ Choose “highest PR potential” problem for POC

PROVE

✓ Create action plan – methodology, technology, timelines, expected outcome

template, success criteria

✓ SWAT team – Partner BU rep, Analyst & Technologist

✓ Check-ins & documentation of what worked and did not, do’s/don’ts, challenges

& nuances and their workarounds

✓ Insights communication & Impact estimation

✓ Champion vs. Challenger measurement

SELL✓ Highlight victories and call out incremental benefits

✓ Ramp plans: hiring, cost, time, other areas where it can be used

✓ Branding – Internal, and if possible, external too, make it ‘cool’ and desirable



CHANGE MANAGEMENT PLAYBOOK|EXECUTION



Source:






ANALYTICS VALUE CHAIN: STRATEGY DRIVES EVERY INITIATIVE & ANALYTICS

MEASURES ITS EFFECTIVENESS!

Analytics provides insights into “actions”, Research context on “motivations” & Testing

helps verify the “tactics” in the field and everything has to be productized…

Strategy

Data Tagging

Data Platform

Reporting

Analytics

Research

Cognitive

IterativeLoop Key benefits

Focus on Big Wins

Reduced Wastage

Quick Fixes

Adaptability

Assured execution

Learning for future

initiatives

Optimization



…WITH PROGRESSIVE SOPHISTICATION, THE COMPLEXITY OF QUESTIONS & IMPACT

OF ANALYTICS SHOULD BE BIGGER & MORE INTEGRAL TO THE ORGANIZATION…

60%

20%

10%5% 5%

20%

30%

15%

10%5%

20%

25%

25%

25%

20%

25%

25%

20%

15%

25%

20%

20%

20%

20%

15%

YEAR 1 YEAR 2 YEAR 3 YEAR 4 YEAR 5

Primary source of insights for Decision Making along the Analytics Maturity Curve

Reporting Data Analytics User Research A/B Testing Advanced Analytics/Machine Learning Data Products Cognitive Analytics

ILLUSTRATIVE



…& PROGRESSIVELY MORE VALUABLE MILESTONES BE MADE POSSIBLE

Dimensions Year 1 Year 2 Year 3 Year 4 Year 5

Major

deliverable

indicating

success at

this phase

Foundational

Data Lake

• Operational Analytics, i.e.,

Automated workbooks for

analytics (Self Serve)

• Test & Learn Process and

Framework

• Predictive Model for

KPIs and consequent

simulations (prescriptive

recommendations)

• Outcome Focused

Framework for Portfolio

Management

• Early Data Science

Platform work

• Data Science

Platform

• Cross integration of

Analytics, Research

and Testing at App

Layer (API)

• Streaming Analytics

• Cognitive User

Facing Product

• Monetizeable

products

Learning

objectives

met

• Data knowledge

Repository: Metrics,

lineage, governance

• Strategic KPIs and their

definitions

• What worked vs. not:

Initiatives impact, Testing

results/learning

• Engagement Model,

delivery framework and

who to go to

• Champion Challengers

• Experimentation Results

• Driver relationships

• Data Driven Design

• Innovation Scaling/

Strategy Testing

• System Dynamics

• Champion-

Challenger on Data

Products and

Cognitive solutions

• Customer

receptiveness

Business

objectives

met

• Benchmarking insights:

Top Movers & Shakers,

Segments, Conversion

Funnel, User Journey,

Engagement Trends,

NPS, Brand Awareness,

Customer Influencers,

Risk, Platform

Performance Metrics

• High level Drivers

identification: Growth

segments/levers, Causation

vs. Correlation, Cohort

Maturity Curve, Value

Migration Matrix, Networks

& Influencers, Leading

Indicators, Risk factors

• Data Driven (Analytics,

Research & Testing) impact

• Conversion Rate

Optimization

• Lifecycle Management

• Growth Hacking

• Targeted Campaigns

• Influencer Growth

• Adaptive Models

adoption across

Business Units

• Modular Self Serve

Framework for

Business

• Impact from

Streaming Analytics

• Additional source

of Revenue from

Analytics

• Scalability cost

reduction from AI

• Customer NPS

improvement from

AI

Analytics KPISpeed of insights,

%availability of reports,

interactive dashboards

Progressive Operational KPIs

(YoY), Success rate from

Testing Program, Business

Impact measurement

Progressive Operational KPIs, Business KPI impact, Stakeholder NPS,

Employee Engagement, Progressive high Returns per Analytics team

member

ILLUSTRATIVE



CHANGE MANAGEMENT PLAYBOOK|TRANSFORMATION



Source:





FLIP THE PRODUCT DEVELOPMENT FLOW WITHIN ANALYTICS FUNCTION…

5


Change Analytics

delivery model

from

“Software

Development”

to…

• (70%)

Stakeholders

requests what is

needed and how

• (30%) Analytics

interviews on

numbers/insights

Performs Analytics,

Create Reports

UAT with

stakeholders

Stakeholders sign-

offs

…to a Product

Development

flow!

• “Persona”

interviews

• Need

Identification

(speed, detail,

frequency, where,

visuals/numbers)

• Analytics

savviness

• Possible Tradeoffs

• Affluence/

Influence

• Customer Rating

• POC – Output

Delivery System,

Engagement Model,

etc.

• Identify fit,

Satisfaction,

• Business need met

• Iterate

• Impact, Usage

• Drop-offs, Funnel,

Repeat Usage

• Platform

performance

• Next Best Products

• Premium Support

• Case Studies

• Optimize & up-level

offering

• Brownbags

• Productize/

Cognitive

IDEATION DESIGN ROLLOUT GROW

…and switch between Agile, Kanban, Continuous based on type of project



…& PAIR UP WITH BEST PRACTICES TO CREATE A SUSTAINABLE TRANSFORMATION

PEO

PLE

• Embed Analytics Maturity Curve Graduation as an Analytics Leadership KPI

• Analytics Maturity Curve Roadmap & Job Family foundational documents

• Design Thinking Focused

• Cross Functional ownership

• 101 Trainings – Marketing, Product, Sales

PROCESS • Borrow best practices from TPM world: Agile, Kanban and Continuous Delivery

• Iterative Learning & Co-development of Analytics

• Documentation: Impact Dashboards, Project Tracker, Knowledge Discovery

Portal, Brand Home Page (Whitepapers, case studies, brownbag),

• Formalized Customer Feedback Channel and Management Strategy

• SMART Goals

TECH

• Data Science Platforms: Data Pipeline/ETL (e.g., UNIFI), Model development,

deployment (Data Science Workbench) and Post Deployment Monitoring,

Management and API framework (Thinkdeep)

• Project Management Trackers

CULTURE

• Business Enablement

• Customer Needs Focused

• Entrepreneurial



Why this, Why now, why here?



BIGGER TRENDS THAT ARE SHAKING UP THE ANALYTICS WORLD FROM INSIDE OUT…

Demand Pressures: Complexity and nature of problems and their solutions,

type of audience & consumption framework evolving

Monetization opportunities- Direct, Indirect, Recurring

Artificial Intelligence, IoE and “Smart”ening of devices/systems faster than

expected.

Evolution of input data sources and integration of multiple insights sources

into decision making (A/B Testing, Research, Predictions/Scores from other

models)

Evolution from Service to Product to Platform (Build Once, Use Everywhere

APIs)

…and without Analytics Maturity Curve progression as top priority, we will lose out!



The parting words…



KEY TAKEAWAYS

Analytics is a bellweather of business maturity. More advanced the

analytics function, more aware and agile is the organization.

Insights (Analytics, Research & Testing) is a Strategy function that should

drive execution and business transformation.

Mature organization have realized that lack of “real” analytics education

drives low engagement and under-utilization. This led to creation of

education programs to best realize full potential of data assets.

Mature organizations with analytics within the DNA are poised to reap

benefits of Data Productization, Incremental Monetization, Industry

beating performance and Artificial Intelligence revolution.

Analytics leadership should chart out the Progression plan for the

organization, lay out milestones/timelines, expected impact and keep the

leadership focused on this transition. This is needed to help them

understand the need for continuous investment and nurturing.



Appendix



THANK YOU!

Would love to hear from you on any of the following forums…

https://twitter.com/decisions_2_0

http://www.slideshare.net/RamkumarRavichandran

https://www.youtube.com/channel/UCODSVC0WQws607clv0k8mQA/videos

http://www.odbms.org/2015/01/ramkumar-ravichandran-visa/

https://www.linkedin.com/pub/ramkumar-ravichandran/10/545/67a

RAMKUMAR RAVICHANDRAN





https://twitter.com/decisions_2_0





Data & Analytics

Advancing the analytics maturity curve at your organization