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How Can Midsize Enterprises Exploit AI and Data Monetization

Alan Duncan

VP Data, Chief Data Officer

Alan Duncan is Vice President for Data and Analytics Strategy and Chief Data Officer (CDO). Mr. Duncan is

a recognized authority and executive leader in the fields of data strategy, business analytics, data-driven

culture and business change, data governance, and data quality. In a career spanning over 26 years, Mr.

Duncan has provided strategic advice for world-class data management, business intelligence, data

warehousing, master data management, document management and knowledge management solutions. He

has worked with clients in a diverse range of industry sectors, including telecommunications, financial

services, retail, state and federal government, natural resources, utilities, and manufacturing.

Connect with Alan

Connect with Gartner

https://www.gartner.com/analyst/51402

https://www.linkedin.com/in/alandduncan/

https://www.linkedin.com/company/2078

https://twitter.com/Gartner_inc

https://twitter.com/Alan_D_Duncan

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“A lot of people think well, you know if we can buy a certain tool, that will solve all of our problems. But the problem is…if you buy a tool for artificial intelligence, you still have to train the tool to make intelligent conclusions based on the data that’s provided”

Jan, Insurance

6 CONFIDENTIAL AND PROPRIETARY I © 2019 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner and ITxpo are registered trademarks of Gartner, Inc. or its affiliates.

Hype Cycle for Artificial Intelligence

Guru 20:1Labor to Software

Cost Ratio

Expert 9:1 Implementer 3:1


When We Interviewed Clients, This Is How They Defined AI

"Capabilities of machines/computers to carry out cognitive tasks and, more specifically, complex decision making tasks, which rely on cognition and learning in continuously changing environments"

— Exec., Telecommunications

"The ability to use computing platforms to automate human-like decision making with the goal of eventually outperforming the human"

— Exec., Transportation

"Algorithms that match and exceed the reasoning ability of human beings that are applied to a wide variety of problems and situations"

— Exec., Government

"A disruptive technology embracing cognitive intelligent 'agents' which has the potential to optimize the delivery of services to our staff and students, which previously would have been done via face-to-face communication or similar"

— Exec., Education

Common AI definitions focus on automation,

increased performance, and a combination of

opportunity and threat in equal measure


Super short version:

Classify and predict

— (faster, more

variously and in

greater volume than

humans can

without AI).

Artificial Intelligence applies advanced analysis and

logic-based techniques including machine

learning to interpret events, support and

automate decisions, and to take actions

▪ Emulates human performance, typically by learning

▪ Comes to its own conclusions

▪ Understands complex content

▪ Engages in natural dialogs with people

▪ Enhances human cognitive performance

▪ Replaces people in execution of

nonroutine tasks

Gartner Definition of AI - FOR NOW!(Green my emphasis)


Have you started adopting AI?

Polling Question 1 of 3

A. Have already invested and deployed

B. In short term planning/actively experimenting

C. In medium or long-term planning

D. On the radar, no action planned

E. No interest

How to participate in our polling

If you are in full screen mode – click Esc

The poll question is on the “Vote” tab.

Please click the box to make your selection.

Upon voting you will see the results.

Thank you!

Q. Polling Question

(please choose 1 answer)

A. Answer

B. Answer

C. Answer

D. Answer

E. Answer


Take comfort! AI is still in early adoption

© 2019 Gartner, Inc.

Q: What are your organization's plans in terms of artificial intelligence?

Base: All Answering, n = 2,882

Source: Gartner 2019 CIO Survey

Percentage of Respondents

No interest

9%

Plan to deploy 2-3 years

29%

Will deploy 12-14 months

25%

Will deploy next 12 months

23%

Have already invested and

deployed

14%


“The art of progress is to preserve order amid change

and to preserve change amid order.”

— Alfred North Whitehead

Ensure your objectives are for business performance –Focus on measurable outcomes


Top performing MSE CIOs are more likely to have business growth as personal objective

70%

57%

64%

45%

51%

67%

49%

56%

32%

27%

0% 10% 20% 30% 40% 50% 60% 70% 80%

Optimizing enterprise operational excellence

Influencing business models

Building business agility

Growing revenue

Growing business margins


Total MSE (n =1,409) Top MSE (n = 83)

Base: role is CIO or most senior IT leader, MSE n varies by segment. Multiple responses allowed.

Which of these strategic business objectives are among your personal job objectives?

2018 CIO Agenda: CIOs in Midsize Enterprises Must Exploit AI and Data Monetization to Grow Their Business © 2019 Gartner, Inc.

CIO Non-IT Objectives: All MSEs Versus Top MSEs


2 4 51 3

Innovation Exploration Prototyping Refinement Firefighting

ChallengingStatus Quo

100% 80% 60% 20% 0%

Data ScientistsWork As

Innovators or inventors

Investigators or detectives

Engineers Engineers Investigators

MainObjectives

▪ Disruptive ideas

▪ Discover new business moments

▪ Deductive thinking

▪ Transformative ideas

▪ Explore unknown issues

▪ Look for discontinuities

▪ Inductive thinking

▪ Evolutionary ideas

▪ New problem solving

▪ Improve existing solutions by 20% to 300%

▪ Effective ideas

▪ Improve existing solutions by 1% to 10%

▪ Remediating ideas

▪ Diagnosis

▪ Hypothesisvalidation

Plan ▪ Look for cross-industry insights

▪ Research disruptive indicators

▪ Data scientists must participate in innovation

▪ Fund nondirectedexploration

▪ Leverage deep data science skills

▪ Exploit existing market inefficiencies

▪ Require ROI justification

▪ Ideal for data science lab involvement

▪ Close the business monitoring loop

▪ Go deep in LOB activity

▪ Look for efficiency levers

▪ Focus on critical variables

▪ Tackle cross-function tactical projects

▪ Build versatile skills

▪ Promote SWAT analytics

Use of Data Audacious Massive Selective Selective Selective

Data Supply Model None Data lake Data lake Data warehouse Data lake

Business Benefits of AI in Midsize Enterprises


Innovation: Betting the Farm on Information

▪ Opportunity:

– Improved farming productivity, growth and margins

▪ Data and analytics:

– Soil tested with electrical charges and mapped for precise fertilizer

dosages applied automatically

– Drones equipped with infrared cameras survey for flood, irrigation and

crop stress

– Combines take continuous readings, analyzing data in real-time data on

moisture, yields, etc. via iPads

▪ Results:

– Ability to farm 20,000 acres, up from 700 acres in the 1970s, with only

25 employees

– ROI growth from 14% to 21%, despite 8x increase in cost of

sensor-loaded combines

– Eliminated need for crop diversification to hedge against weather, disease

and market conditions


Exploration: Dark Data Shedding Light on Retail Space Optimization

▪ Opportunity:

– Improve in-store customer experience


– Historical video feeds from existing security cameras

– Video analytics and visualizations from Prism Skylabs to

understand shopper profiles (e.g., sex and estimated age)

and shopping traffic patterns

▪ Results:

– Heat maps identified customer wait times, enabling the

businesses to improve store flow

– Optimized relative product placement

– Improved employee assignments and scheduling improve

customer service levels


Prototyping: Immonet Optimizes Its Product Portfolio With Analytics ▪ Opportunity:

– Target the most valuable real estate agents, who are likely to list most or all of their properties on its real estate business platform and reduce churn.


– Use Oracle Exalytics In-Memory Machine to analyze customer buying patterns, such as increasing mobile applications usage and studying real estate agent behavior to optimize the company's property portfolio.

– Was able to segment customers into key accounts, regular agents and private customers to target the most valuable customers in each segment.

▪ Results:

– Increased customer requests by 300% through better search engine advertising.

– Improved the company's sales by 200% bringing it to the number ʺtwoʺ position among Germany's real estate platforms.

– Reduced agent churn rate by over 50%.


Refinement:Driving Fleet Safety and Performance

▪ Opportunity

– Improving driver competence and retention

▪ Data and Analytics

– Telematics from drivers gathered into a data warehouse and combined with

employee data from other systems

– Sophisticated analytics using IBM SPSS assess drivers for risk factors

such as miles driven, sleep opportunities and pay levels, compared to

company averages

– Analyzing drivers' pay compared versus peers and industry averages, in

combination with other stress factors and employment history

▪ Results

– 20% overall reduction in accidents; 80% reduction in severe accidents (e.g.,

roll-overs)

– 30% reduction in employee turnover leading to savings on recruiting

and training


Firefighting:Big Data Helps Vitens Detect and Remedy Costly Pipe Leaks▪ Opportunity:

– Vitens water supply company needed to simplify the maintenance of 96 water production facilities and 49,000 kilometers of pipes.


– CGI developed a proof of concept solution. It gathered and analyzed data on variables such as pressure, flow, temperature and physical location.

– Using predictive analytics and visualization software, it searched for data patterns that could be used to detect or predict incidents.

▪ Results:

– It was able to detect leaks within a 2.5 kilometer radius in 50% of cases demonstrating that, by using big data and predictive analytics, leaks can be detected and repaired faster.


By 2022, over 50% of midsize

enterprises will improve their

productivity and growth through

adopting artificial intelligence into

their core business operations.

Strategic Planning Assumption


“The value of an idea lies in the using of it.”— Thomas Edison

Accelerate the adoption of AI –focus on business use cases


How well do you track the benefits accruing

from your investments in technology and

data?


A. We have formal benefits management approach and quantify benefits accrued after-the-fact

B. We capture value stories, case studies and feedback

C. We have some anecdotal evidence of benefits and outcomes

D. We treat any technology delivery as a cost center and don’t really track the benefits

E. Ummmm… say what?!?!






Thank you!

Q. Polling Question


A. Answer

B. Answer

C. Answer

D. Answer

E. Answer


Top MSEs are more likely to use AI-based applications and more likely to use them to enhance market facing activities


Base: All answering, excludes DK, n varies by segment. Multiple responses allowed.

Does your organization use any of these artificial intelligence (AI)-based applications?

2018 CIO Agenda: CIOs in Midsize Enterprises Must Exploit AI and Data Monetization to Grow Their Business

Adoption of AI-Based Applications

3%

12%

2%

2%

3%

4%

13%

11%

5%

9%

5%

6%

7%

11%

17%

20%

2%

11%

13%

15%

25%

31%

33%

38%

0% 5% 10% 15% 20% 25% 30% 35% 40%

Other

HR applications such as resuméscreening

Virtual personal assistants

Anomaly or fraud detection on IoTdata

Call center virtual customer assistants

Sentiment analysis or other opinion-mining analysis

Marketing department customersegmentation

Fraud analysis on transactional data


MSE Top Performers (n = 89) MSE Typical Performers (n = 1,205) MSE Trailing Performers (n = 91)


Consider the Impact of Data Science & Artificial Intelligence

EfficiencyGains

MassivePersonalization

RenderInsights

ReinventDecision Making

CaptureKnowledge

ShareExpertise

The value received

from incorporating

AI into your

strategy will be

proportional to how

much you rethink

your business


Select the Right Use Cases. Right for You!

Search enginesSentiment analysis (or

opinion mining)

Information Retrieval

Spam filtering for email

Speech and handwriting recognition

Spoken language

understanding Stock analysis

Structural health

monitoring

Syntactic pattern

recognition

Topic spotting: categorize

news articles

Weather prediction

Face Detection

Finance –Derivatives

TradingGame playing

Platform/Software As a Service

Internet fraud detection

Machine translation

Medical diagnosis

Mood analysisBrain machine

interface in prosthetics

Optical character

recognition

Recommendation systems

Robot locomotion

Advertising -Targeting

BioinformaticsAutomatic

word completion

Classifying DNA Sequences

Computer Vision – Object

Recognition

Customer Segmentation

Detecting Credit Card

Fraud

•Artificial Intelligence in retail has redefined customer segmentation, marketing and customer experience (provide examples)

Retail

•This sector has seen a tremendous shift to artificial intelligence through autonomous cars

Automotive

•Disruptive models powered by AI are eliminating the need for traditional Driver and Package Handler jobs

Logistics

•Artificial Intelligence has led to development of health management functions like lifestyle management, drug discovery, hospital management etc.

Healthcare

•Applications of Artificial Intelligence finds their way in diagnosing Cancer. Deep Learning drops error rate for breast cancer diagnoses by 85%

Medical

•Companies are leveraging machine learning and AI technologies to increase production and to optimize costs

Oil and Gas


Scale Acceleration:What AI Is Good For

▪ Automate sorting processes and actions.

▪ Automate predictions in detail.

▪ Address historical desires first (not new

business models … yet)

▪ Address data with clear parameters.

▪ Credible, good-quality data with sufficient

scope to fully address the problem.

▪ Pursue reasonable and possible goals.

The moon comes after simple flight.


Questions to Ask Your "AI" Vendor

1. What does AI mean to you (the vendor)? How does this product fulfill that definition?

2. How is your product superior to current options that have no AI?

3. Once I have your product installed, how will its performance improve through AI?

4. How should I expect to devote staff and time to such improvements?

5. How can I see that will happen with data that is related to my project?

6. What data and compute requirements will I need to build the models for the solution?

7. What resources are available to gather and refine data that the AI solution can use such that its outcomes improve?


By 2022, enterprise AI projects with

built-in transparency will be 100%

more likely to get funding from

CIOs.



“While money can’t buy you happiness, it certainly

lets you choose your own form of misery.”

— Groucho Marx

Towards digital business by monetizing data assets -Focus on infonomics & data literacy


How well are you managing and deriving

value from your Information Assets?


A. We are a data-driven business, and have clearly identified ways of measuring and monetizing the value of our data

B. We recognise the need to manage information as an asset, but don’t measure the resulting business impacts and outcomes

C. We have some relevant performance metrics that are used to steer our current business operations, but little in the way of data-driven thinking and innovation

D. We generally are unaware of the opportunities and impacts of data on our business






Thank you!

Q. Polling Question


A. Answer

B. Answer

C. Answer

D. Answer

E. Answer


Top MSE Performers Are More Likely To Have Found Ways to Monetize Data Assets


Base: All answering, n varies by segment. Not including "Other."

Thinking about any specific data or algorithms your organization owns the IP for, has it found ways to monetize these assets (or otherwise create tangible value from them)?

2018 CIO Agenda: CIOs in Midsize Enterprises Must Exploit AI and Data Monetization to Grow Their Business

Status of Monetizing Data Assets

34%

55%

78%

24% 24%10%

39%

17%

6%

MSE Top Performers (n = 79)

MSE Typical Performers (n = 1,107)

MSE Trailing Performers (n = 85)

Yes, we have found ways to monetizedata

Not yet, but we have a plan to do sowithin the next 12 months

No, and we do not own the IP for anydata or algorithms that can bemonetized within the next 12 months


63%

41%

16%

Sum of "Yes" and "Planning"


The 3-Dimensional Challenges and Opportunities of Infonomics

Monetizing

Information

Generating

measurable

economic benefits

from or

attributable to

available

information

assets

Managing

Information

Applying

traditional asset

management

principles and

practices to

information

Measuring

Information

Gauging and

improving

information’s

economic

characteristics


Generating Economic Benefits from Information

INDIRECT DATA MONETIZATION

▪ Using data to improve efficiencies

▪ Using data to develop new products, markets

▪ Using data to build and solidify partner relationships

▪ Branded indices

DIRECT MONETIZATION

▪ Bartering/trading with information

▪ Information-enhanced products or services

▪ Selling raw data through brokers

▪ Offering data/report subscriptions

100

100

100

100or


What Would You Say? How Would You Prove It?

How are we treating it like any

other asset?

How are we

maximizing the

ways its

monetized?

What is our

organization's

information

worth?Your Board of Directors


By 2022, over 50% of midsize

enterprises will have initiated

specific initiatives to monetize their

data.



Defining Data Literacy: The New Core Capability of Digital Society

Gartner formally defines data literacy as: The ability to read, write and communicate data in context, including an understanding of data sources and constructs,

analytical methods and techniques applied, and the ability to describe the use-case application and resulting value.

Informally … do you “speak data?”

Technology

People Process

Process Technology

People

Data


Process Technology

People

Data

AI Purpose

AI Signal Data AI Training Data

AI Decision Model/Algorithm

AI

Synthesis of Algorithms and Data in AI Solutions


AI

Ac

tio

n


AI

Constituents/Digital Citizens

Subject Matter Expert

Actor

Developer

Training scenarios Engineering and testing

AI operationsLearning

Key Roles & Interactions Within an AI Ecosystem


By 2020, 80% of organizations will

initiate deliberate competency

development in the field of

information literacy, acknowledging

their extreme deficiency.



“If you’re bringing technology that’s

going to displace people, what a lot

of companies are going to do is just

lay people off. So I think again in

terms of workforce, preparation to

me is key…it should be part of a

longer term plan as opposed to an

afterthought” Klaus, Gaming


Make AI strategic and core to the business

Anchor your AI efforts in business outcomes

Be skeptical! Ensure AI solutions match specific user cases

Measure, manage and monetize your data using infonomics

Train and hire for a workforce to be more data literate


Recommended Gartner Research

Predicts 2019: Midsize Enterprise CIOs Lead, Adapt and Evolve Digital Transformation

Alan D. Duncan et al (G00351590)

Midsize Enterprise CIO Priorities and CEO Expectations

James Browning (G00374739)

Midsize Enterprises Go Digital: How to Generate New Revenue Streams

Federic Troni & Ansgar Schulte (G00348925)

Applied Infonomics: How CIOs in Midsize Enterprises Can Monetize Their Data

Alan D. Duncan, Joseph Provenza (G00348755)

Data Science and Machine Learning Offer Five Business Benefits to Midsize Enterprises

Alan D. Duncan | Alexander Linden | Erick Brethenoux (G00346290)

Closing the Digital Talent Gap at Midsize Enterprises

Ansgar Schulte (G00331629)


Recommended Gartner Research

Hype Cycle for Artificial Intelligence, 2018

Svetlana Sicular, Kenneth Brant (G00357478)

Hype Hurts: Steering Clear of Dangerous AI Myths

Tom Austin, Alexander Linden and Mike Rollings (G00324274)

What CIOs Should Ask When Someone Pitches a Project That Uses AI

David Furlonger | Tom Austin (G00338351)

Applied Infonomics: Seven Steps to Monetize Available Information Assets

Douglas Laney, Alan D. Duncan, Lydia Clougherty Jones, Mike Rollings (G00369366)

Artificial Intelligence Demands That CIOs Foster a Data-Literate Society

Alan D. Duncan (G00331626)

Getting Started With Data Literacy and Information as a Second Language: A Gartner

Trend Insight Report

Valerie A. Logan, Alan D. Duncan (G00352314)

Connect with Gartner How Can Midsize Find out more ... · human-like decision making with the goal...

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