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Jake Freivald
Five Hot Trends for 2018Business outcomes and technology priorities in data and analytics
Product Marketing
December, 2017
The Promise of 2018
The Internet of Things Takes Off
The Enhanced Power of Embedded Analytics
Predictions, not “Predictive”
Real Artificial Intelligence
Data Monetization for a Happy CFO
2
Internet of Things
3
Five Hot Trends for 2018
Internet of Things
Smarter devices in the IoT are increasing the need to centralize, contextualize, and manage data to improve decisions and business processes.
ManufacturingSharing smart device data can differentiate commodity products.
Government and Smart CitiesSensors can help central planners decide how to best deploy resources and regulate requirements.
Logistics and Supply ChainThe IoT can bring an aircraft, replacement parts, and a skilled tech to the same place at the same time.
Health CareThe IoT can provide data that can predict, prevent, and help prosecute fraud, theft, and inefficiencies that affect patient outcomes.
Computing power at the edge drives autonomous action closer to the device location to improve response times and reduce traffic to the central processor
Internet of Things
In humans, this is called the reflex arc...
...the greatest strength and weakness of which is that it doesn’t involve the brain.
Photo credit: bit.ly/2AiDXeX
Internet of Things
A dirty little secret
Just like “Big Data” is becoming “data”
...the “Internet of Things” is already mostly just the Internet
Needs communication, context, integration, mastering, analytics,
data discovery, information delivery, reporting, scoring, and presentation
2018 trends to watch: “ Cloud to the edge ”
More IoT deployments go cloud-based
Embedded BI and Analytics
7
Five Hot Trends for 2018
Embedded BI and Analytics
Your brain
It’s always with you, and always on. ...and you don’t need to tap into all of it at once.
You don’t need to do anything special to interact with it....though you may need to focus it sometimes.
Why shouldn’t analytics be the same?
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Embedded BI and Analytics
Issues driving 2018 changes
Pendulum swing: Centralized to decentralized and back again
Embedded is generally not an area for standalone analytical tools
Analytics adoption has hit a wall
Right information, right time is a mantra, but hasn’t been fulfilled
SaaS application adoption
Embedded BI and Analytics
Import all the data
legacy datawarehouse
othercloud
Physically load – and pay for –any needed data
Embedded
legacy datawarehouse
othercloud
Use data as needed
Swivel-chair analytics
Predictions, not “Predictive”
11
Five Hot Trends for 2018
Predictions, Not “Predictive”
The Monty Hall Problem1. You pick a door (say, #1). 2. Monty shows you another
door, empty (say, #2).3. He offers to let you switch
to #3, or stay with #1.What do you choose?
First, the answer: Always switch.
Second, it doesn’t matter whether you agree with me or not: Every statistician knows that’s the right answer.
Third, most ordinary people will go round and round (and round) with this problem.
The analytics? Hard.
The prediction? Easy.
Lesson: Give the prediction.
Predictions, Not “Predictive”
Or... go there!Use predictive analyticsWeather patternsTypical crime levels per typeConcerts and eventsSchool days and weekdaysHolidays and weekendsPaydaysShift / time of day....
Predictions, Not “Predictive”
Market watch
Predictive analytics suddenly becomes AI or machine learning(For that matter, lots of things do. More on that in a moment.)
Prescriptive analytics goes the same route
Market watch
Despite the need for predictions, vendors will tout predictive analytics“for the businessperson”
Predictions, Not “Predictive”
2018 areas we’ll see growth in “predictive analytics” (or shrink-wrapped predictions)
Healthcare: better treatment outcomes
Supply chain management: automated supplier, routing choices
Financial services: though with skepticism / throttling
Customer relationships: e.g., best-offer optimization
Real Artificial Intelligence
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Five Hot Trends for 2018
Real Artificial Intelligence
What is it?
To some extent, who cares?
Self-directing vacuum?
Autonomous farming vehicle?
...okay, fine, some terms
Algorithms
Machine learning”
“Transform
nature of workthe
and the structure
of the workplace
Real Artificial Intelligence
What is it?
To some extent, who cares?
Self-directing vacuum?
Autonomous farming vehicle?
...okay, fine, some terms
Algorithms
Machine learning”
“highly scoped
machine-learning
solutions that target
a specific task
19
Real Artificial Intelligence
Pattern matching across heterogeneous data sets, e.g.,
Metadata
Data
Analytical objects
Specific tasks such as...?
Anomaly detection
Repeated data quality issues
Match/merge assistance
False positives or negatives
Identifying patterns slightly above the noise floor for humans to investigate
Real Artificial Intelligence
Real Artificial Intelligence
Is there anything new?
“Cheap gas”
Storage
Computing power
Bandwidth
AI swarms
...and where will we see failures in 2018?
“AI helps with unbiased decision-making”
“Take humans out of the equation”
To do it right
Help humans, don’t replace them
Create advanced user experiencesSometimes called “augmented intelligence”
Data Monetization for a Happy CFO
22
Five Hot Trends for 2018
Data MonetizationCu
rren
t,sa
tura
tin
g
McKinsey, 12/17
Data Monetization
Are
as f
or
gro
wth
McKinsey, 12/17
McKinsey, 12/17
The changes are new and continuing
Across industries, most respondents agree that the primary objective of their data-and-analytics activities is to generate new revenue.... Of the 41 percent of respondents whose companies have begun to monetize data, a majority say they began doing so just in the past two years.
Defining Your Data Monetization Strategy
Step 1 – Which Information Will Deliver the Most Value?
Step 2 – Where is the Data Coming From?
Step 3 – Is the Data Ready to Be Monetized?
Step 4 – Can All Stakeholders Participate in Data Monetization?
Monetizing Data
Data Monetization
Our experience: externally facing BI applications will yield more measurable returns
Enhance customer “stickiness.” Customers spend more time with you, which gives you more opportunities to interact with them
Competitive advantage. It can give you a leg up on competitors as you offer more value-added services
Process improvement. Reduce cost and eliminate bottlenecks
Increase market share. New data-and-analytics products can open doors you once had a problem opening
27
Data Monetization
Possible types of monetization
Benchmarking!
Offering analytics on top of commodity products
Unify your data with external data (e.g., weather, economy) for additional insights
Interactive e-statements
Data Monetization
Considerations
Make sure your house is in order: mastered and suitable quality data
Customer-facing applications need high-quality data – they know themselves better than you do
Data products often need more than just what you get natively; you might end up reselling data
Recap
The Internet of Things Takes Off
The Enhanced Power of Embedded Analytics
Predictions, not “Predictive”
Real Artificial Intelligence
Data Monetization for a Happy CFO
30
Questions?
31