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How to Monetize Digital through x2x Business Models
Cathy Tornbohm
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What Do CEOs Think Digital Business Is?
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What Outcomes Do Clients Want From Digital?
Q: Please choose the top three expected outcomes and/or impacts that digital represents for your enterprise.
Insurance(n = 62)
Banking(n = 88)
More business through digital channels 66% 59%
More revenue from better operations 65% 67%
Tighter partnerships 48% 33%
Changing the basis of competition 32% 20%
Cost reduction 27% 30%
Creating new markets 26% 32%
Engaging and empowering employees 21% 25%
Crossing industry boundaries 8% 15%
Expanding to new geographies 6% 14%
Source: Gartner, January 2016
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Top Three Digital Business Technology Related ChallengesQ21. What are the top three digital business technology-related challenges in your organization?
n=304
Lack historical data
Consumerisation of IT
Need for scalable storage and backend platforms
Difficulty with identifying the opportunities
Regulation and privacy issues — sharing data with other or-ganizations
High-level investment or hype
Making sense of the data or semantic standardization
Trust in IT industry
IT organizations’ mindset
Justification of investments
Digital enablement of employees
Need for new competencies, lack of skills
IT security — such as greater need for user validation and au-thentication
IT leadership
Data management
3%
5%
3%
5%
4%
7%
5%
6%
6%
9%
6%
6%
10%
13%
13%
5%
4%
5%
6%
6%
6%
8%
7%
7%
5%
8%
9%
8%
9%
9%
4%
3%
5%
3%
5%
6%
6%
7%
8%
7%
8%
8%
11%
7%
11%
Ranked First Ranked Second Ranked ThirdSum33%
29%
29%23%
22%
21%
21%
20%19%
19%
15%
14%
13%12%12%
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The Necessary Change of Focus in Back and Middle Office
20th CenturyBusiness Software
Supporting the Administrative Drone
21st CenturyBusiness Software
Supporting Multitasking Knowledge Workers
Author
https://commons.wikimedia.org/wiki/File:Elmer_Candy_Co_Inc_Office_New_Orleans.jpg
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Mode 2 World: Task Support Through App-Style Software
Clients Need an Holistic Approach: Making the Legacy Work with the New
Mode 1 World: Heterogeneous and Hybrid Services
On-Premises Packaged Custom
Exposing APIs: API Management: Security: Integrity: QoS
CorporateApp Store
BUApp Store
RegionalApp Store
PublicApp Store
Cloud
C JE F H K L M N O PA D IGB Q R
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The Internet of (Very Different) Things
0
200
400
600
800
1000
1200
1400
1600 Connected LED lamps
Livestock sensors
Sports equipmentShipment condition monitor
ATM machines Traffic lights
Vending machines
Parking metersHotel door locks
Vehicle sub-systemsWearables
ToysAnti theft and loss tags
Smart electric meters
Outdoor security camerasElectronic shelf edge labels
Thermostats
• Expect 8 billion shipments in 2020.• Many smart versions of existing product markets.• Key challenge: Where to focus?
Shipments in 2020(millions of units) (Selected items for illustration)
Activefreightpallets
Agricultural sensors
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Target Topics by Vertical Industry: Example: IoT
0%
20%
40%
60%
80%
0% 20% 40% 60% 80%
Already implemented IoT
Pla
nnin
g to
impl
emen
t IoT
in th
e fu
ture
Utilities
Oil and Gas
Manufacturing
Technology and Service
Banking
Government
Transportation
Services
Retail
Healthcare Providers
Education
Insurance
Indicators of IoT potential include:
• Own physical assets or real estate
• Culturally and financially able to innovate — both businessand technology
• Looking for novel ways to enhance customer experience
4Q15 Gartner Research Circle IoT Survey, n = 359 organizations who had either implemented IoT or planned to implement IoT. Due to the sample sizes involved for some industries, this graphic should be treated as directional and indicative of general trends but isn't highly statistically significant.
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Target Key Challenges: Example Top IoT ChallengesCybersecurity
Integration
Determine/manage business requirements
Analytics
Networking and communications
Data management
Architecture
Device management
Orchestrate workflows and processes
Application development
0% 10% 20% 30% 40% 50% 60%
Percentage of organizations rating the specified issue as being in their top three IoT challenges. 4Q15 Gartner Research Circle Survey, n = 121, all respondents were from organizations currently using IoT.
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By 2020, autonomous software agents outside of human control will participate in 5% of all economic transactions.
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Permutations of b2b, b2c, m2c, m2b, m2m, b2g and g2g
Shopping bot
IOT thing
Real person consumer
Organization
Shopping bot
IOT thing
Real person consumer
Organization
BuyerSeller
Smart machine Smart machine
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Phase 1: Things as Announcers
Products: • Fitbit
• Turbines• Babolat
Tennis Racket
• Cars, • Hospitals, • Factories,
• Cities
Key Enabling Technologies
• Motion, sound, heat sensors
• Internet connectivity• Recommendation
engines
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Phase 2: Things as Fixed Purchases
Key Enabling Technologies
• CRM Systems• Internet Services
• Decision Management
RequestsService
Receivesmessages
ReportsDisputes
Makes itsown purchases
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Phase 2: Things as fixed purchases…
Take action on behalf of parameters set by
humans
The SneakerBot
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Phase 3: Things as Adaptable Purchasers
Key Enabling Technologies
• CRM Systems• Internet Services
• Decision Management
Chooseamong
multiple options, with outcomes set by humans, such as,
urgency, location, cost- benefit trade off
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Phase 4: Things as Autonomous Purchasers
Key Enabling Technologies:
• Digital IdentityDirectional Examples:
• Roboadvisors• Autonomous vehicles
• Smart homes• Smart cities
• Precision agriculture• Mobile health
monitoring
Decide and take action independentof humans
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Algorithmic Business Sales Models
Demand /Supply Algorithm Heat mapping for demand Real time aerial view of car movement Other analytics (opening app,
destination probabilities)
Surge Pricing Algorithm Automatically detect situations of high
demand and low supply to adjust price
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How does a “Beam Toothbrush” get in on the act?
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Spotting the Opportunities: Smart Machines Are Accelerating Disruption in Every Industry
Advertising: Sensor-driven customization
Agriculture: Precision thinning for plants
Education: Grading essays
Financial: Writing earnings reports
Legal: Finding the most-likely-to-win strategy
Medical: Differential diagnosis and treatment plans
Oil and Gas: Machine diagnosis and usage optimization
Retail: A/B testing for physical locations
Transport: Robot valets parking and retrieving cars
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Old marketing models wont work!
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Thing Marketing: Appealing to Algorithms
Low Fat
High Fiber
Sugar Free
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Source: https://wwwwwwwwwwwwwwwwwwwwww.bitnik.org/r/
Random Darknet Shopper
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Opportunity– Chinese families often want to give their babies English names for future study
or business in Western countries
Data and analytics – A 16-year old British schoolgirl developed a website to match a dozen desired
personality traits selected by the parents, along with the gender, to a database of English names
– Candidate names are shared on WeChat social media platform with family and friends to help make a final decision
– After the name is chosen, a printable certificate is generated with the name, its meaning and examples of famous people with that name
Results– Has named nearly 250,000 Chinese babies to-date (Sept 2016), and has
generated almost £50,000
– Avoids embarrassing names like Gandalf or Cinderella pulled from films
Oh Baby! ( 宝宝 )
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Opportunity– Cromaretail.com was dealing with the problem of plenty. Amid varied product
offering, customers were confused and conversions suffered.
– Data and analytics – Worked with Infinite Analytics which helped it understand customer’s social
profile, brand affinity, recent activities, household and macroeconomic data.
– For the product catalog, it utilizes a mix of NLP, Semantic technologies, Machine Learning to match and enrich the product understanding.
Results– In 6 months time, revenue share was up 24.9% and conversions shot up by a
staggering 217%.
– Deployment also resulted in 28.8% increase in orders with recommendations.
Croma converts onlookers into customers with analytics
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Opportunity– Wanted to minimize driving time by taking the best route with the least
amount of traffic and stoplights, and optimize travel expenses
– Data and analytics – UPS engineers devised a plan for route-optimization and used Orion, short for
On-Road Integrated Optimization and Navigation.
– The algorithm used 1,000 pages of code to analyze 200,000 possibilities for each route in real time.
Results– UPS saved 10 million gallons of gas and carbon emissions were reduced by
100,000 metric tons
– The company saved 98 million idle minutes which is about $25 million worth of labor cost each year.
UPS creates its own best possible Route
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Spotting the Opportunities: How to Reimagine Consumption and Consumers
Capital
Production Line
Hotel
Buy a Car/Daily Rental
Taxi and Delivery
Trust and Reputation
Knowledge
Personal Experience
Crowdfunding
Local 3D Printing Service
Airbnb
Share a Car/Hourly Zipcar
Uber Car and Driver
Social Recommendation and Reputation Score
Cloud-Based Virtual Assistant
Community/Network
Fixed Purchase Fungible Access/Time Slice
Reimagining the Nature of "Business"
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Spotting the Opportunities: Network Aggregator Model
Units of physical work
Units of knowledge work
Units of physical product
Units of lending
Units of service
Units of value
Units of funding
Phy
sica
l
Inta
ngib
leH
uman
Digitalize
Automate
3DP
Robots
IoT Wearables
Autonomous VehiclesCognitive
Agents
DemocratizeSharing economy
Drones
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Marketing Essentials Create a seamless process don’t silo off digital offerings Build a branded methodology to unify your story. Collect great publically namable case studies Focus communications on use cases and value of your product or
service not features and functions — Ensure these communications are vertical industry specific and able to
accommodate various audiences. Publish a book on your angle of digital business technology
and strategies, or align with key academics. Create one of more digital business "innovation" center (site, themes).
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Recommended Gartner Research
Mandate Investigation of Smart-Machine-Enabled Services to Accelerate Business Outcomes
Frances Karamouzis and Ruby Jivan (G00269974) Sourcing Smart-Machine-Enabled Services Drives Competitive Advantage and F
uture Patent Revenue
Frances Karamouzis (G00272722)Maverick* Research: When Things Become 'People‘
Don Scheibenreif Jenny Sussin Jim Tully Kristin R. Moyer (G00278110) Digital Business Innovation With Smart Machines
Tom Austin and Hung LeHong (G00265758) Toolkit: Accelerate Digital Business With a Product Creative-Thinking Workshop
for Your Executives
Mark Raskino (G00262520)For more information, stop by Gartner Research Zone.