Mobile intelligence—using mobile to drive business insight
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Transcript of Mobile intelligence—using mobile to drive business insight
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Mobile intelligence Using mobile to drive business insight
Discover Performance / June 2014
Discover Performance Strategic insights and critical trends for IT executives
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“When someone has a mobile device in hand, it’s not just about the browser and the app.
Mobility provides new insight
Paul Muller VP of strategic marketing
HP Software @xthestreams
The device itself generates a lot of micro-behavioral information that is very valuable, if you can put it to use — hesitation, clicks, the time it takes to make a choice, and so on. … It’s valuable design and marketing information.”
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Mobile can be an integral part of the business
Mobility in 2014
Maribel Lopez research analyst
Lopez Research @MaribelLopez
“In 2014, everybody has accepted that BYOD is just part of the enterprise landscape… Businesses are trying to define how mobile can make the organization run ‘better and faster.’ Sometimes it’s really easy, like email replacing paper. Other times, it needs to be more thoughtful. For example, ‘How can I use location to make a difference?’”
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© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
“Integration with Big Data will be huge.”
“Mobile provides a lot of context: motion, temperature, humidity, location, speed and many other dimensions. But that type of info is not embedded in our business systems today. Going forward, if we are re-creating our business systems, we have the opportunity to capture this data and do something meaningful with it.”
Maribel Lopez
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© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Mobile apps should tie in to business strategy
Engagement metrics for marketing insights • Are users coming back after
first use? How long does it take for users to come back?
• The length of user sessions – how long do users stick around?
• How do users buy?– what offers influence purchasing behavior?
Hammond, J.S., Murphy, P., Ask, J., Facemire, M., & Curran, R (2013). Measuring Mobile Apps.
Forrester Research. http://hpsw.co/q3E5AtH
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© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Technical metrics for marketing insights
Collect, then act The data gives you more ways to deliver excellent IT service, along with insights that will profit the entire enterprise.
• User platforms – what devices are being used?
• When/how are bugs and crashes appearing?
• Average load times?
Delays with more traffic?
• How much of a devices' resources are in use?
Mobile apps should tie in to business strategy
Hammond, J.S., Murphy, P., Ask, J., Facemire, M., & Curran, R (2013). Measuring Mobile Apps.
Forrester Research. http://hpsw.co/q3E5AtH
Discover Performance Join today
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Embrace analytics CIOs need to bring new insight to the business
1. Know what you know – examine the data coming in from your mobile
devices, decide which data is most valuable, and what actions to take
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Embrace analytics
1. Know what you know – examine the data coming in from your mobile
devices, decide which data is most valuable, and what actions to take
2. Hire (or rent) a data scientist – there is value in adding at least one
expert analyst to your team
CIOs need to bring new insight to the business
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Embrace analytics
1. Know what you know – examine the data coming in from your mobile
devices, decide which data is most valuable, and what actions to take
2. Hire (or rent) a data scientist – there is value in adding at least one
expert analyst to your team
3. Start small and prove value quickly – launch a trial project to immediately prove value
CIOs need to bring new insight to the business
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Embrace analytics
1. Know what you know – examine the data coming in from your mobile
devices, decide which data is most valuable, and what actions to take
2. Hire (or rent) a data scientist – there is value in adding at least one
expert analyst to your team
3. Start small and prove value quickly – launch a trial project to immediately prove value
4. Ingest and analyze – choose your data collection platform or software
according to your information needs
CIOs need to bring new insight to the business
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Embrace analytics
1. Know what you know – examine the data coming in from your mobile
devices, decide which data is most valuable, and what actions to take
2. Hire (or rent) a data scientist – there is value in adding at least one
expert analyst to your team
3. Start small and prove value quickly – launch a trial project to immediately prove value
4. Ingest and analyze – choose your data collection platform or software
according to your information needs
5. Deliver insights to the business – connect data with developers and
marketers who can get things in front of customers quickly
CIOs need to bring new insight to the business
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Do you need a data scientist? “The large companies I interviewed about big data projects said they were not hiring Ph.D. level data scientists on a large scale. Instead they were forming teams of people with quantitative, computational, or business expertise backgrounds.”
Tom Davenport Thomas H. Davenport is the
Professor of IT & Mgmt Babson College
Davenport, T. (2014, March 26). What makes Big Data projects succeed. http://blogs.hbr.org/2014/03/what-makes-big-data-projects-succeed/
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© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
A data science strategy “Your data science strategy has to respect the structure you have in place.”
Keith Macbeath senior principal consultant
HP Software Professional Services Look before you leap
• Think about how IT is organized within your business
• Where will the data scientist can be most useful
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© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
A data science strategy “Your data science strategy has to respect the structure you have in place.”
Keith Macbeath senior principal consultant
HP Software Professional Services Look before you leap
• Think about how IT is organized within your business
• Where will the data scientist can be most useful
Don’t hire a floating data scientist
• Think about where you intent to deploy them
• Have specific problems in mind for them to sink their teeth into
Discover Performance Join today
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
A data science strategy “Your data science strategy has to respect the structure you have in place.”
Keith Macbeath senior principal consultant
HP Software Professional Services Look before you leap
• Think about how IT is organized within your business
• Where will the data scientist can be most useful
Don’t hire a floating data scientist
• Think about where you intent to deploy them
• Have specific problems in mind for them to sink their teeth into
Select a great test case
• Look at all your possibilities and choose an optimal test case
• Make sure to define and prepare for the project
Discover Performance Join today
© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
A data science strategy “Your data science strategy has to respect the structure you have in place.”
Keith Macbeath senior principal consultant
HP Software Professional Services Look before you leap
• Think about how IT is organized within your business
• Where will the data scientist can be most useful
Don’t hire a floating data scientist
• Think about where you intent to deploy them
• Have specific problems in mind for them to sink their teeth into
Select a great test case
• Look at all your possibilities and choose an optimal test case
• Make sure to define and prepare for the project
Create a winning environment
• An environment that lets you comfortably prove data results
• An environment with the flexibility and budget to identify useful patterns
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© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Diagnostics for the enterprise “What broke, how did it break? You need to dive into your data logs. Inspect it the way a coroner investigates a dead body. Go through your data to figure out what went wrong. But rich, real-time data goes beyond post-mortem, letting you keep the patient healthy. Ultimately it’s about using that info proactively. It’s about using data for a better quality of life. For the enterprise.
Paul Muller VP of strategic marketing
HP Software @xthestreams
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© Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Read more on mobile intelligence
Mobile in 2014: Beyond BYOD
How to connect data science and IT
How to turn mobile IT into business insight
Measuring mobile apps, Forrester
HAVEn: See the big picture in Big Data, HP’s Big Data Platform
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