McGraw-Hill Professional Business Insider Work Smarter Webinar Series presents Leading with Data: Boost Your ROI with Open and Big Data.
Joel Gurin and Prasanna Tambe discuss 2 hot new topics - open data and big data! You will learn how you can use them to gain the competitive edge in creating and developing a business and building an effective workforce.
For the webinar recording visit: http://bit.ly/mhpworksmarter
5. Setting the Stage
The GovLab’s Central Hypothesis
When governments and institutions open
themselves to diverse participation and
collaborative problem-solving, and partner
with citizens to make decisions, they are more
effective and legitimate.
6. Setting the Stage
Open Data: Accessible, public data that
people, companies, and organizations
can use to launch new ventures, analyze
patterns and trends, make data-driven
decisions, and solve complex problems.
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7. Setting the Stage
Open Data Changes the World For:
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Entrepreneurs
Established businesses
Governments
Investors
Scientists
Journalists
Consumers
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8. Setting the Stage
What Open Data Isn’t
• Big Data ≠ Open Data ≠ Open
Government
• Big Data: Really, really big datasets
• Open Government: Transparency,
participation, collaboration – with or
without data
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11. Federal Data
Open Data Becomes a Priority
[Open Data is] going to help launch more
businesses. . . . It’s going to help more
entrepreneurs come up with products and
services that we haven’t even imagined yet.
President Barack Obama
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18. Data-Driven Cities
How Wired Cities Use New Data
•Optimize operations
•Monitor infrastructure conditions
•Plan infrastructure
•Public health
•Emergency management
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19. State and City Data
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Metro Chicago Data
New York: The Mayor’s Geek Squad
Code for Philly
Palo Alto’s open finances
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40. Open Data 500
What’s the Value of Open Data?
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McKinsey study: $3 trillion annually worldwide
30 to 140 billion euros for Europe’s public sector data
2 to 9 billion British pounds
$30 billion for U.S. weather data
Tens of billions for U.S. GPS data
Hundreds of billions for U.S. health data
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42. Open Data 500
Open Data 500: Assessing the Value Rigorously
• Criteria:
– U.S. based
– National or regional scale (mostly federal data)
– Open Data must be key to business
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More than 500 companies contacted so far
Wide range of sectors covered
Partnering with Open Data Institute to replicate in the U.K.
Interest from 15 other countries at Open Government
Partnership
www.OpenData500.com
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44. Big Data and HR
Prasanna Tambe
NYU Stern School of Business
ptambe@stern.nyu.edu
Leading with Data:
Boost Your ROI with Open and Big Data
February 26, 2014
45. Existing sources of HR data
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Data collected during recruiting, hiring
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Data routinely collected by organizations
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employment histories (resumes), skills, interview and test
evaluations
performance reviews, task and project evaluations
Administrative labor market data
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regional and industry data on skills, wages, occupations
46. But “digital breadcrumbs” are creating a data
revolution
(courtesy Erik Brynjolfsson)
Clickstream/Page views/Web transactions
Email messages
Mobile phone/GPS/Location data
Web links/Blog references/Facebook
Google/Bing/Yahoo Searches
ERP/CRM/SCM transactions
RFID (Radio Frequency Identification), Bar Code
Data
Real-time machinery diagnostics/engines/equipment
Stock market transactions
Twitter feeds
Wikipedia updates
Online Databases of resumes
47. Emerging sources of HR and workforce data
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Online/Internet data
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Digital traces from work activities
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internal knowledge boards, internal corporate network activity, finegrained measures of project and task performance
Social and physical network data
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labor market level information on skills and experience, discussion board
posts, software and projects posted online
employee referrals, person-to-person communications, sociometric
badges, email networks, internal digital chatter, video and camera data
Data generated through new assessment tools
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online assessment (e.g. MOOCs), test-based video games
48. Vast increase on data on spatial and temporal
movements
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Micro-measurement of personal productivity
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Team productivity
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Organizational productivity
50. How can the big data "microscope" aid
workforce related decisions?
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Remove cognitive biases and reliance on intuition
• W don't know what makes us productive (especially
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information workers)
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Enables quantification of the impact of HR-related decisions
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W is our inability to retain engineers costing us?
hat
51. How are employers using analytics?
now
near future?
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Predicting retention/turnover
for high-skill employees
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Where are we likely to have skill
gaps in ten years?
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How desk location affects
information flows
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What is the return on investment
to a specific HR policy?
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Using internal communications
to predict employee
performance
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Can applicant profiles based on
Internet data outperform
traditional 'signals' (e.g.
education)?
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What (other) job titles predict
success in the opening I am
trying to fill?
52. Lessons learned (so far)
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Data is not a substitute for conceptualization
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Knowing the right questions to ask (domain expertise) is
critically important
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The interest in analytics is likely to outpace results in the
short-run as employers put the right pieces in place
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But we are likely to see a significant increase in the number
of ways data is used for HR-related decision-making within a
few years
53. Potential barriers to using analytics
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A new generation of technical and analytic
skills
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Collection and management of new data
sources
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Policies regarding data collection and use
(privacy)
54. Questions?
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Editor's Notes
I will plan to take about 20-25 minutes
First 10 minutes on emerging types of data
Last 10 minutes no how firms might use it
Last 5 minutes on what employers should be thinking about
Then we will shift to Q & A.
TWO POINTS:
Data that can be useful for HR decision-making is rapidly expanding!
Some thoughts on what HR Professionals should be thinking about for a smooth transition
Go quickly through these – there may be others, not meant to be a comprehensive list
Firms already routinely use these …
Digital traces of online activity have lead to an explosion in the availability of data of all types
Great for social-science research and for data-driven decision-making. What’s new?
1. Evidence of on-the-job performance
2. Scale (hundreds of millions of observations)
But these are new! An expanding world of data that are going to eventually be useful for HR-decision making.
Useful for building applicant profiles and learning about candidates.
(Privacy is important, but defer to later)
The granularity of the data that is being recorded is the big shift here. Enables really fine-grained track of how and where and on what we are spending our time.
An example-at the city level-of spatial and temporal mapping of people’s movements. Used the city level because it’s easy to visualize.
Huge boon for urban planners and designers.
Why can’t the same thing be done for organizations or for workflow?
1. Data helps us uncover insights about what is productive from a workflow standpoint. We don’t know how our email behavior, who we hear from, when we hear from them, message content, impact productivity, but the tools are becoming available that allow us to do that.
Much of what we know relies on intuition, but much of that is wrong. This also applies to “life” productivity, not just productivity at work.
2. “you can manage what you can measure” … helps to provide economic metrics that can be useful for managerial decision-making
The second is high-impact? What is the ROI on work-from-home?
The last of these brings up an important point …. Is it good for workers?
Without conceptualization, too much data can be a hindrance. It’s difficult to manage, and you are just awash in data. Lot of interest right now, but it may take some time to see results. This is nothing new. Technology cycles always involve a lot of upfront investment, and then 3-5 years later, results.