managing innovation within an analytics practice

Intended for Knowledge Sharing only

Managing Innovation

Executive Roundtable

Nov 2015


Disclaimer:

Participation in this summit is purely on a personal basis and does not represent VISA,Inc. 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 info of any firm is used in any material.

Director, Analytics & A/B Testing at Visa, Inc.

Enable Decision Making at the

Executives/Product/Marketing level via

actionable insights derived from Data.

RAMKUMAR RAVICHANDRAN

Director, Analytics at Visa, Inc.

Program Management – Analytics, Reporting

Operations and Innovation Practice

ANDREW NOONE


Quick recap of what it is


Philosophy of Innovation


A tree that isn’t growing is decaying internally….




The topic an oxymoron?


THE DISCUSSION IS ALL ABOUT HELPING REALIZE TRUE POTENTIAL…

FROM A GOOF BALL…


TO AN “OSSUMMMMMM” ACTION HERO…


…THROUGH INNER PEACE





Common Myths

INNOVATION, THE HEARTBREAK KID OF CORPORATE WORLD?


REALLY?


An unicorn finding business

Either business focused or technology focused

Only new products are innovation

Outcome is immediate

Only start ups or Labs can innovate

…NOT REALLY!


Anything from a best practice of another area to restructuring

work flow

Ten types of Innovation (Configuration, Offering, Services) ,e.g.,

Newer applications/newer techniques, Improved Delivery, Incremental

RoI, Network Effect of learning

Process, Products and/or a mix of both

Some ideas are ahead of their time, connect the dots later

Learning may be the outcome in itself

Test & Learn culture, Exec support, fit with Strategic Goals &

stakeholder buy in can enable innovation even with mature orgs

Source: https://www.doblin.com/ten-types

Don’t expect oil firms to jump in joy when you pitch Snapchat to them…

https://www.doblin.com/ten-types




How to go about it?

INNOVATION CHARTER


1 Strategic Goals What exactly is needed, why and

where?

2 Tactical Approach Best practices to-do list

3Organizational

Transformation People-Process-Technology-Culture

DEFINE THE STRATEGIC GOALS FOR INNOVATION PROGRAM


Areas Illustrative Goals

Incremental Impact

- Data Products & Algorithms

- Higher Avg Net Profit per users (ARPU, Cost/Loss Rate)

- Improve System Delivery Efficiency & Effectiveness

Better Delivery

- Lower cost/time of Analytics (Dev/Test/Delivery)

- Operationalizing Analytics

- Better User Experience Design: Easy, Flexible,

Modular, Scalable, Fast

- Available everywhere and real time

Network Effect of Learning

- Make Exploratory Analytics/Research/Testing easy and

accessible

- Cross Pollination of ideas

Newer Applications

- Newer Problems

- Newer applications of same techniques

- External inputs (3rd party data, partners)

INNOVATION CHARTER



where?


3Organizational


TACTICAL DETAILS (PLANNING)


The elevator pitch (Fit with the Strategic Goals): “Migrating from HIVE

to Impala will reduce data preparation time by 20%”1

Problem Statement & Estimated Benefit Sizing: “Current data

processing technology will not be able to handle expected loads”2

Type (Product, People, Tech, Culture) & where it fits3

Target Customers: Executives/Analysts/Data Savvy stakeholders/Engineers4

Competitive Benchmarking: Can the current product suite solve with some

changes? Why not any other alternatives?5

SWOT Analysis (with future goals & vision in mind)6

Change/Integration Management: Costs/Speed/Dependencies & RoI7

Project Management: Delivery & Deployment steps; Milestones; Success

Criteria; RASCI assignments; Executive Sponsors; Communications Management 8

TACTICAL DETAILS (EXECUTION)


• Step 1: Gap Analysis, i.e., inventory of current problems and/or future

requirements

• Step 2: Decide on evaluation criteria & test use cases in discussion with the

relevant stakeholder teams - Analytics & Testing, Business Intelligence, Marketing,

Product Management, Engineering, etc.

• Step 3: Research possible solutions & Score for ability to meet needs (Questions #1

through #6)

• Step 4: First round interview to get a better sense of nuances

• Step 5: Request product capability demo or POCs on the test use cases and

evaluate the how well it satisfies the needs in real world (Questions #7 & #8)

• Step 6: Interview with current Customer references

• Step 7: Conduct specific “engineering/security” focused discussion

• Step 8: Cross functional Panel discussion on the POC evaluation readout (what

worked/not; workarounds; nuances; refresh Estimates) and Go/No-Go decision

INNOVATION CHARTER



where?


3Organizational


ORGANIZATIONAL TRANSFORMATION

21

PEO

PLE • Hire explorers, improvers and creators & train existing

• Mandate new Learnings and new ideas: 2 better ways a week

• Non Analytics but visionary Mentors/Speakers/Leaders

PR

OC

ESS

• Encourage Shadow IT with guidelines for eventual absorption

• Not only Business Objectives but also Learning Objective Focused

• 90-10 formalized & mandatory

• Analyze the “Analytics” function and improve

• Brown bags/meet ups/Ideation contests

• Long-Short term projects laundry list

TEC

H

• Formalize Research: Web Crawlers, Discussion Forums, Monitor

Google/Linkedin/Business Press (Gartner & Forrester Research)

• Engage Vendors, Research Organizations, Academia

• Formal Knowledge Management: Learn from history & Connect the

dots later

CU

LTU

RE • Fail Fast & Learn Faster

• Reward Innovation: if not in cash, at least in kind & motivation

• Entrepreneurial

• “Innovation” budget




Research Summary

Setting up

right

Analytical

Framework

Data

Collection &

Preparation

AnalysisRecommen

dations

END TO END VIEW OF DECISION ENABLER FRAMEWORK

Intended for Knowledge Sharing only 23

Problem

Statement

Key Challenges today

Possible Solutions

Trends to watch out for

• Ambiguous questions/Give me everything/let me figure out• Need to check my own hypotheses: Domain Experts & Data Savvy• Agile not really “Agile”

• Customer education- effort, possible outcome & prioritization based on strategic objectives (Outcome Focused)

• Leverage past learning, take Proxies (Documentation)• Continuous Development vs. Agile vs. Lean• Enable “easy” learning for “non-coding” Domain experts

• Kyvos Insights enables easier learning for “non-coders”• HP Idol: Google search like capability for Knowledge Management

Data

Collection &

Preparation

AnalysisRecommen

dations

Problem

Statement

Setting up

right

Analytical

Framework




Possible Solutions


• “Siloed” Analytical/Testing/Research• Data Lineage & Governance issues Multi-platform, inconsistent

definitions• Reconciliation issues and blind-sided ness

• Lean Analytics principles: Strategy & Outcome Focused org• Centralized data platforms but custom usage (Data Lineage &

Governance)• Internal Communications, Knowledge Management, Brown bags,

Common Analytics charters

• HP Idol: Google search like capability for Knowledge Management• Developments in “Big Data” Warehousing tech & “API” connectivity

of tools with corporate Open Analytics Platforms• Closer integration of disciplines

Setting up

right

Analytical

Framework

AnalysisRecommen

dations

Problem

Statement

Data

Collection &

Preparation




Possible Solutions


• Instrumentation gaps• Trade offs between Storage efficiency vs. usability• Ease/speed of accessibility & use• Learning curves

• Optimize Data Lake Models (Test & Learn framework) for speed, scalability, flexibility and extensibility – SMM/Columnar/No SQL

• Accessibility & ease of use for Analysts/Domain Experts• Easier rollouts of POC until full roll outs

• Streaming Technologies• Cloud Storage• In Memory processing and other Warehousing tech trends• Kyvos Insights making it easy for non-coders

Setting up

right

Analytical

Framework

Recommen

dations

Problem

Statement

Data

Collection &

Preparation

Analysis




Possible Solutions


• Integration between disciplines/platforms/techs/players/org and corresponding Silo issues

• “One-time” mindset• Iterative learning vs. Co-development• Lack of Strategic Oversight & Outcome Focused approach

• Cultural and Organizational alignment• “Operationalizing Analytics” e.g, Kyvos-Tableau• Focus on documentation• Open Analytics Platform that supports custom delivery (Modular)• Hybrid team model (best of Embedded & Centralized structures)

• Consolidation of tool/service providers (SAS/IBM SPSS/SAP HANA) and expansion of product portfolio (RapidMiner, Rev R)

• Focus on UED by Tool/Service providers• Data instrumentation, Ingestion & blending tech trends

Setting up

right

Analytical

Framework

Problem

Statement

Data

Collection &

Preparation

AnalysisRecommen

dations




Possible Solutions


• Very little time spent on “Analysis of Insights” for consequences• Delivery not optimized for “Analysis of Insights” required for

increasing confidence in the decisions• Lack of User Experience Design principles• Not available when/where/however required

• “Analysis of Insights” by Stakeholders and Analysts has to be made compulsory and made part of Operationalizing Analytics step.

• UED training or Strategist as part of the team• SaaS delivery (Web/App)• Cross validation of insights from various disciplines (Biz Case)

• Newer methods like Deep Learning, Uplift Modeling, etc. popping up on Gartner Hype Cycle

• Technologies like IBM Watson that brings it all together under “Augmented Intelligence” framework

• Natural Language Understanding: Cortana-Power BI; Thoughtspot




In summary

ABSOLUTELY NEED…

Expectations Setting & Management

Measurements, Monitoring, analysis, fine tuning & oversight

Communications & PR Strategy

Forward thinking Vision & “Strategic” tie-ups

29

Executive & stakeholder support

SUMMARY

30

• “Know” that what you have is getting obsolete with every minute

• “Must have” positive & tangible impact on the organizational & stakeholders KPIs

• “Ensure” superior project management, leadership oversight and communication

management

• “Develop” relationships within & outside organization that can be your eyes and

ears

• “Prepare” for ever more increasing pressures on Analytics and innovation might be

the only way out




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

32









https://twitter.com/decisions_2_0





managing innovation within an analytics practice

Data & Analytics