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Scott Klososky

Digital Transformation & Trends: Technology and Taking the Lead

We are called to be architects of the future, not its victims Buckminster Fuller

The Digital Transformation

A 50-year Historically

Significant Era

(2000 - 2050)

The Digital Transformation

A 50-year Historically

Significant Era

(2000 - 2050)

The Connection of Everything

The Digital Transformation

A 50-year Historically

Significant Era

(2000 - 2050)

Mobility, Wearables, Implantables

The Digital Transformation

A 50-year Historically

Significant Era

(2000 - 2050)

Data/Information Immersion

The Digital Transformation

A 50-year Historically

Significant Era

(2000 - 2050)

Frictionless Communication

The Digital Transformation

A 50-year Historically

Significant Era

(2000 - 2050)

Digitally Augmented Relationships

The Digital Transformation

A 50-year Historically

Significant Era

(2000 - 2050)

Robotic & Software Automation

HUMALOGY

The balance between humanity and technology

H+ Humalogy

TechnologyHumans

0T1

T2T3T4

T5H5

H4

H3H2

H1

Digital Transformation is consistently changing the Humalogical Balance from human activities to technology performed tasks

0 T1 T2 T3 T4 T5H5 H4 H3 H2 H1

H+ Humalogy Scale

0 T1 T2 T3 T4 T5H5 H4 H3 H2 H1

Amazon YouTube

Robotic Surgery AI & DSS

Fully Autonomous

Machines

H+ Humalogy Scale

0 T1 T2 T3 T4 T5H5 H4 H3 H2 H1

Funeral Homes Churches

Doctor Visit Human Decisions

Human Creativity

Amazon YouTube

Robotic Surgery AI & DSS

Fully Autonomous

Machines

H+ Humalogy Scale

0 T1 T2 T3 T4 T5H5 H4 H3 H2 H1

H+ Humalogy ScaleIn 1964, the most valuable company, AT&T, was worth $267 billion in today’s dollars and employed 758,611 people. Today’s telecommunications giant, Google, is worth $370 billion but has only about 55,000 employees

We are now shifting from the Information Age to:

The Age of Entanglement

As technology and humanity continue to converge the repercussions on our future are staggering…

The Transformation Dilemma

Rat

e of

Ch

ang

e

Time

Organizations Change Logarithmically

Technology Changes Exponentially

Strategy Risk Gap

The Transformation Dilemma

Rat

e of

Ch

ang

e

Time

Organizations Change Logarithmically

Technology Changes Exponentially

The Leadersh

ip Legacy

Zone

The Transformation Dilemma

Profit AmplificationThe ability to use technologyto lower costs and raiserevenues at the same time

Profit AmplificationThe ability to use technologyto lower costs and raiserevenues at the same time

Digital Marketing

Digital Operations

Profit AmplificationThe ability to use technologyto lower costs and raiserevenues at the same time

Digital Marketing

Digital Operations

Pre-emptive Knowledge of Technology & Risk

Acc

urat

e Vis

ion

• Focused on Monthly Results• Execution Focused• Ignorance of Trends• Avoid Change• No Future Investments

12 MONTH VIEWLOW BEAM LEADERSHIP

HIGH BEAM LEADERSHIP5 TO 10 YEAR VIEWHigh VQ (Vision Intelligence)

Trend AnalysisWilling to Experiment

Predictive Analysis

Technology & Connection

Web 5.0Integrated Humans and Technology (Transhuman) 2030

Web 1.0Connected Organizations 1995

Web 2.0Connected People 2005

Web 3.0Connected Devices 2014

Web 4.0Connected Information Platforms (Ambient Intelligence) 2022

Web 5.0Integrated Humans and Technology (Transhuman) 2030

Web 1.0Connected Organizations 1995

Web 2.0Connected People 2005

Web 3.0Connected Devices 2014

Web 4.0Connected Information Platforms (Ambient Intelligence) 2022

Dig

ital T

rans

form

atio

n

The Internet of Everything

Three-Cs of IoE

Three-Cs of IoE

• Components (3 types): Physical; connected; locally intelligent (edge analytics)

• Capabilities (4 layers): Monitoring; controlling; optimizing; autonomous decisions

• Convergence: Devices, data flow, automation, and AI are combining to allow autonomous control of device activities

Data Flow and Real-Time Truth...

Truth + Visibility = Insight

Truth + Visibility = Insight

Existing Data

Collectable Data

3rd Party Data

Partner Data

DATA INTELLIGENCE MODEL

•Acquisition •Storage •ETL

DATA HARVESTING

DAT

A

Existing Data

Collectable Data

3rd Party Data

Partner Data

DATA INTELLIGENCE MODEL

•Acquisition •Storage •ETL

•Structure •Reporting •Dashboards

DATA ARCHITECTURE

DATA HARVESTING

DAT

A

INFO

RMAT

ION

Existing Data

Collectable Data

3rd Party Data

Partner Data

DATA INTELLIGENCE MODEL

•Acquisition •Storage •ETL

•Structure •Reporting •Dashboards

•Rules •Mashups •Science

DATA ALCHEMY

DATA ARCHITECTURE

DATA HARVESTING

DAT

A

INFO

RMAT

ION

Existing Data

Collectable Data

3rd Party Data

Partner Data

DATA INTELLIGENCE MODEL

•Analytics •Pattern Recognition •Visualization

DATA STORYTELLING

•Acquisition •Storage •ETL

•Structure •Reporting •Dashboards

•Rules •Mashups •Science

DATA ALCHEMY

DATA ARCHITECTURE

DATA HARVESTING

DAT

A

INFO

RMAT

ION

KNOW

LEDG

E

Existing Data

Collectable Data

3rd Party Data

Partner Data

DATA INTELLIGENCE MODEL

•Augmented Intelligence

•Analytics •Pattern Recognition •Visualization

INSIGHT

DATA STORYTELLING

•Acquisition •Storage •ETL

•Structure •Reporting •Dashboards

•Rules •Mashups •Science

DATA ALCHEMY

DATA ARCHITECTURE

DATA HARVESTING

DAT

A

INFO

RMAT

ION

KNOW

LEDG

E

WIS

DOM

Existing Data

Collectable Data

3rd Party Data

Partner Data

DATA INTELLIGENCE MODEL

•Augmented Intelligence

STRATEGIC VALUE

•Analytics •Pattern Recognition •Visualization

INSIGHT

DATA STORYTELLING

•Acquisition •Storage •ETL

•Structure •Reporting •DashboardsOPERATIONAL

VALUE

•Rules •Mashups •Science

DATA ALCHEMY

DATA ARCHITECTURE

DATA HARVESTING

DAT

A

INFO

RMAT

ION

KNOW

LEDG

E

WIS

DOM

BUSINESS INTELLIGENCE

BIG DATA

Existing Data

Collectable Data

3rd Party Data

Partner Data

DATA INTELLIGENCE MODEL

Provide visualization services, predictive analysis algorithms, & mash ups

Become a broker of industry data so that you can provide performance insights

Collect sensor data, aggregate, analyze, provide alerts, and store

Data (insight) as a Service to Customers

The Case Study: Smart Cities

The Case Study: Smart Cities

The Case Study: Smart Cities

Underlying Network Architecture

A holistic design with blueprints

A Unified Citizen Mobile app

High level Risk Control

DEFINITION: A city with pervasive digital architecture that optimizes the efficiency of operation, citizen safety and convenience, with a high level of automation

A high level of automated software and device control

Winning in a Competitive Market

Digital Maturity: A performance level

Digital Readiness: A state of human capacity

Digital Transformation: A time in history

Winning in a Competitive Market

What will be the digital footprints you leave?

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