The Economics of Data, Analytics and Digital Transformation

Source: Bill Schmarzo “Big Data MBA” Course Curriculum “Economics of Data™“ Playing Cards

The Economics of Data, Analytics and Digital Transformation

Bill SchmarzoHitachi Vantara Chief Innovation Officer

Honorary Professor, National University of Ireland-GalwayUniversity of San Francisco, Executive Fellow

Twitter: @schmarzo

Bill Schmarzo “Big Data MBA” Curriculum

Data isthe new oil...and muchmore…


BUSINESS OPTIMIZATION

BUSINESS INSIGHTSBUSINESS

MONITORING

INSIGHTSMONETIZATION

DIGITALTRANSFORMATION

PrescriptiveRecommendations

Big Data Economics

Key Business

Use Cases

How Effective is Your Organization at Leveraging

Data and Analytics to Power your Business Models?

Big Data Business Model Maturity Index

ANALYTICSCHASM


Business Initiative

Stakeholders

Decisions (Use Cases)

Analytic Assets

Data & Instrumentation

Architecture & Technology

Data Science Value Engineering Framework

© Hitachi, Ltd. 2018. All rights reserved.

Leveraging Data Science to Transform Your Economic Value Curve

5

Source: Bill Schmarzo “Big Data MBA” Course Curriculum

Maintenance Spend

Up

tim

e %

Lo Hi

Hi

Up1

Up2

C1 C2

Economic Value Curve ChallengeEconomic Value Curve determines optimization point between multiple variables. Unfortunately, Law of Diminishing Returns dictates that additional spend yields marginal improvements.

Maintenance costs could include direct and indirect costs such as work hours, overtime costs, extra parts and inventory, extra consumables, and the costs associated with fixing parts that were not going to break

Δ

Δ


Transforming the Economic Value Curve

LoHi

Up2

C2

Up3

Original Economic Value Curve

New Economic Value Curve

The way to beat Law of Diminishing Returns is to leverage analytics to create new Economic Value Curve; that

is, increase Uptime (from Up2 to Up3) with less Maintenance spend (from C2 to C3).

C3

Maintenance costs could include direct and indirect costs such as work hours, overtime costs, extra parts and inventory, extra consumables, and the costs associated with fixing parts that were not going to break

Maintenance Spend

Up

tim

e %

Hi


How Might COVID-19 Digitally Transform Healthcare Industry?

Source: https://ourworldindata.org/the-link-between-life-expectancy-and-health-spending-us-focus

COVID-19 will force healthcare organizations to digitally transform by uncovering granular patient, disease,

treatment, wellness, doctor, hospital, etc. insights to re-engineer healthcare services

• Smart Hospitals

• Intelligent Healthcare apps

• Precision medicine

• Personalized preventative care

• Personalized welfare

• Remote wellness diagnostics

• Predictive world health

• ML-assisted imaging diagnostics

• AI-based Digital Assistants

• Prescriptive health monitoring

• Digital therapeutics

• Concierge care

US Economic Value CurveROW Economic Value Curve

https://ourworldindata.org/the-link-between-life-expectancy-and-health-spending-us-focus


Rapid exploration, rapid testing, failure-embracing, continuously-learning and adapting “Scientific Method”

REPEAT

Step 1: Define Hypothesis (Decision)to test or Prediction to make

Step 3: Prepare data; Schema-on-query

Step 4: Visualize the data (Tableau, Pentaho, ggplot2,…)

Step 5: Build analytic models (TensorFlow, Python, Jupyter…)

Step 2: Gather data…and more data (Data Lake: SQL + NoSQL)

HistoricalGoogle Trends

PhysicianNotes

Local Events

Weather Forecast CDC

LawsonEpic

Kronos

Step 6: Evaluate model “goodness of fit” (coefficients, confidence levels)

Source: “Scientific Method: Embrace the Art of Failure”, University of San Francisco School of Management Big Data MBA

Data Science Collaborative Engagement Process


The Art of “Thinking Like A Data Scientist”

5 IdentifyData Sources

76Map Scores to

Recommendations 8Group Metrics

Into ScoresIdentify

Recommendations

1Identify

Business Initiative

Identify Analytic Entities

32Identify

Stakeholders

4Identify / Prioritize

Use Cases

Source: Bill Schmarzo “Big Data MBA” Course Curriculum11

PROPENSITIES

TENDENCIES

INCLINATIONS

PREFERENCES

BEHAVIORS

INTERESTS

PASSIONS

ASSOCIATIONS

AFFILIATIONS

BIASES

AFFINITIES

TASTES

You Don’t Monetize Volume of Data; You Monetize Granularity



Entity-level Asset Models: Patient Analytic Profile

External Patient Data• Diet History (DietPlanner,

MyFitnessPal)

• Physical Exercise History (MapMyRun, FitBit)

• Mental Acuity History (Lumosity, CogniFit)

• Stress History (Stress Doctor, Happify)

• Emotional History (Text, Social)

• Vices History

• Vacation / Relaxation History

• Others…

Patient Care Data• Demographic

• Behavioral Demographics

• Psychographics

• Patient care / treatment history

• Patient vital stats history

• Physician / Nurse care notes

• Patient comments

• Pharmacy

• Others…

Schmarzo Patient Profile Score Variance Trend

Health Score 92 1.89

Wellness Score 92 1.85

Diet Score 67 3.25

Exercise Score 82 2.25

Stress Score 65 1.90

COVID19 At-Risk Score 22 2.35

Cancer At-Risk Score 14 1.74

Pulmonary At-Risk Score 02 1.15

Oncology At-Risk Score 08 1.20

Heart Attack At-Risk Score 09 1.25

Stroke At-Risk Score 06 1.10

….

CONFIDENTIAL – For use by Hitachi and Disney employees under NDA only. © Hitachi, Ltd. 2018. All rights reserved.

Exploiting the Economics of Data, Analytics and Digital Transformation


USF Economic Value of Data Research• Data an asset that never depletes, never wears out, and can be used

across unlimited use cases at zero marginal cost

Customer point of sales data

Sales

Promotional effectiveness

+2.5%

• Economic Multiplier Effect: ratio of the impact of an incremental

increase in investment on the resulting incremental increase in value

• Accounting: “Value in Exchange” methodology for determining asset valuation based upon the acquisition cost of an asset

• Economics: “Value in Use” methodology for determining asset valuation

Marketing

Customer acquisition

+2.0%

Call Center

Customer retention

+3.5%

Product Dev

New product intro

+2.6%


Detailed historical transactions coupled with internal unstructured and publicly-available

data sources

Data transformed into analytic assets (scores, rules, propensities, segments, recommendations)

ANALYTICSDATA

Clusters of decisions around common subject area in support of organization’s key business initiatives

USE CASES

Solving Technology-to-Business Linkage Challenge


To Change The Game, Change Your Frame…

If you buy a Tesla today, I believe you're buying an appreciating asset, not a depreciating asset

– Elon MuskTesla CEO

“”


Role of Artificial Intelligence Agents in Learning

Defining the Utility Function is Critical for Autonomous

“Success”

Get reward New state

StateTake actionAI Agent Environment


steering

electrical

engine or motor

fuelpassenger

suspensionIOT EdgeAnalytics

Real-Time Data Streaming

Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)

Time-seriesData Mgmt

The more the product gets used… the more accurate, more robust, more predictive and consequently more

valuable the product becomes. The value of the product appreciates, not depreciates, with usage

What Powers an “Appreciating” Asset?

Deep Reinforcement Learning ModelRational AI State



steering

electrical

engine or motor

fuelpassenger



Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)



“Success”

Rational AI Agent

State Environment

Deep Reinforcement Learning Model


steering

electrical

engine or motor

fuelpassenger



Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)



“Success”

Rational AI Agent

State Environment



steering

electrical

engine or motor

fuelpassenger



Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)



“Success”

Rational AI Agent

State Environment



steering

electrical

engine or motor

fuelpassenger



Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)



“Success”

Rational AI Agent

State Environment



steering

electrical

engine or motor

fuelpassenger



Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)



“Success”

Rational AI Agent

State Environment



Tesla Autopilot Continuous Learning Environment

•Millions of Miles from 500,000+ Tesla Cars• Billions of Miles from Autopilot

Simulator

steering

electrical

engine or motor

fuelpassenger



Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)



“Success”

Rational AI Agent

State Environment



steering

electrical

engine or motor

fuelpassenger



Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)



“Success”

Rational AI Agent

State Environment



steering

electrical

engine or motor

fuelpassenger



Sensor Data

MachineLearning

Real-timeDecisions

Modeling(Deep

Learning)



“Success”

Rational AI Agent

State Environment



Exploit Economics of Compounding Improvements

Driving and

operational data;

“edge” use cases

Backpropagate

learnings (updated

models)

Law of 1% Compounding 1.01 ^ 365 = 37.8x


Incremental “Use Case-by-Use Case” approach to building, reusing and refining data and analytic assets

enables Attribution of use case Financial Value to enabling Data Sources and Analytic Assets

Data Sources

Analytic Assets

Use Cases

Building and Valuing Digital Assets Use Case-by-Use Case

New

Reused

Not Used

Asset Legend

(1) Vendor Quality$60M

A B C$20M $20M $20M

A B$30M $30M

(2) Vendor Reliability$20M

A B C

D

$10M($30M)

$10M

A B$10M($40M)

C$10M

(3) Optimize Inventory$60M

A B C$15M($45M)

$15M($35M)

D E F$15M $15M

A B$20M($60M)

C$20M($50M)

D$20M

…

Source: Bill Schmarzo “Big Data MBA” Course Curriculum “Economics of Data™“ Playing CardsUse Cases

Cum

ulat

ive V

alue

($$$

)

Lo

Hi

“Economies of Learning” more powerful than the “Economies of Scale”: The more the data and

analytics get used, the more accurate, more effective, more predictive, more valuable they become

Effect #3: Economic Value Accelerates• Refining Analytic Module effectiveness ripples thru

previous use cases that use same Analytic Module –The Google TensorFlow Effect

Effect #2: Economic Value Grows• Data and analytic module re-use shrinks time-to-

value and de-risks use cases

Effect #1: Marginal Costs Flatten• Reusing “curated” data and analytic modules

reduces marginal costs for new use case (no data silos or orphaned analytics)

Schmarzo Economic Digital Asset Valuation Theorem

23Source: Bill Schmarzo “Big Data MBA” Course Curriculum

BILL SCHMARZOHitachi Vantara, Chief Innovation Officer

University San Francisco School of Management, Executive Fellow

Honorary Professor, National University of Ireland-Galway

Top-ranking Blogsv To Achieve Big Data’s Potential, Get It into the Boardroom

v Big Data Business Model Maturity Index

v 6 Laws of Digital Transformation

v History Lesson on Economic-Driven Business Transformation

v User Experience: The New King of the Business

v IOT: Transitioning from Connected to “Smart”

v Learning How to “Think Like a Data Scientist”

Contact [email protected]

Find me on Twitter: @schmarzo

Thank You!

The Economics of Data, Analytics and Digital Transformation

Documents

Transcript of The Economics of Data, Analytics and Digital Transformation