Leading with Data: Boost Your ROI with Open and Big Data

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Transcript of Leading with Data: Boost Your ROI with Open and Big Data

Leading with Data:Boost Your ROI with Open and

Big Data

Join the conversation with @MHBusiness @sonnytambe @JoelGurinUse #worksmarter

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Find me at OpenDataNow.com and @joelgurin

Setting the Stage

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My Journey Through the Datasphere

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.

Setting the Stage

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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Setting the Stage

• Entrepreneurs• Established businesses• Governments• Investors• Scientists• Journalists• Consumers

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Open Data Changes the World For:

Setting the Stage

• 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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What Open Data Isn’t

Setting the Stage

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Liberating Federal Data

Federal Data

[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.

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Open Data Becomes a Priority

President Barack Obama

Federal Data

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Federal Data Today

Federal Data

• “Presumption of openness”• Machine-readable• Reusable• Timely• Developed with consultation

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The New Open Data Policy

Federal Data

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They Agree On – The DATA Act

Data-Driven States and Cities

State and City Data

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Help for K-12 Households

Bill Jackson, CEO

State and City Data

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Data-Driven Cities

How Wired Cities Use New Data•Optimize operations•Monitor infrastructure conditions•Plan infrastructure•Public health •Emergency management

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State and City Data

• Metro Chicago Data• New York: The Mayor’s Geek Squad• Code for Philly• Palo Alto’s open finances

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State and City Data

City Data: Next Bus for Commuters

Sim City Meets Participatory Budgeting

State and City Data

State and City Data

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DC’s Experiment: A City Report Card

Washington Mayor Vincent Gray

State and City Data

• Sharing personal data for public good• Pulse Point: “Enabling Citizen Superheroes”

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Open Data Shapes Reputation and Brands

Reputation and Brands

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Social Media: 2 Billion Tweets a Week

Reputation and Brands

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The Reputation Police

Michael Fertik, CEO

Reputation and Brands

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Sentiment Analysis: Emotion Meets Computation

Reputation and Brands

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Open Data from Consumer Complaints

Courtney Powell and A.J. Fouty, cofounders

Reputation and Brands

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Reputation and Brands

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Driving Business Growth

Driving Business Growth

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Open Data Fuels Businesses in All Sectors

Health Education Energy Use

Financial Services Transportation

Driving Business Growth

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From Weather Insurance to Green Revolution

Climate Corporation offices in San Francisco

Driving Business Growth

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40K Public Companies, Updated Daily

Driving Business Growth

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Healthcare: The Next Big Frontier?

Driving Business Growth

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Driving Business Growth

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Data for Energy Savings

Ogi Kavazovic, VP Marketing & Strategy

Driving Business Growth

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Managing Open Data: A Winning Strategy

Finding the Value: The Open Data 500

Open Data 500

• 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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What’s the Value of Open Data?

Open Data 500

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Open Data 500

• Criteria:– U.S. based– National or regional scale (mostly federal data)– Open Data must be key to business

• 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

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Open Data 500: Assessing the Value Rigorously

www.OpenData500.com

Open Data 500

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Big Data and HR

Prasanna TambeNYU Stern School of Business

ptambe@stern.nyu.eduLeading with Data:

Boost Your ROI with Open and Big DataFebruary 26, 2014

Existing sources of HR data• Data collected during recruiting, hiring

• employment histories (resumes), skills, interview and test evaluations

• Data routinely collected by organizations• performance reviews, task and project evaluations

• Administrative labor market data• regional and industry data on skills, wages,

occupations

But “digital breadcrumbs” are creating a data revolution (courtesy Erik Brynjolfsson)Clickstream/Page views/Web transactions

Email messagesMobile phone/GPS/Location dataWeb links/Blog references/FacebookGoogle/Bing/Yahoo SearchesERP/CRM/SCM transactionsRFID (Radio Frequency Identification), Bar Code DataReal-time machinery diagnostics/engines/equipmentStock market transactionsTwitter feedsWikipedia updatesOnline Databases of resumes

Emerging sources of HR and workforce data

• Online/Internet data• labor market level information on skills and experience,

discussion board posts, software and projects posted online

• Digital traces from work activities• internal knowledge boards, internal corporate network activity,

fine-grained measures of project and task performance

• Social and physical network data• employee referrals, person-to-person communications,

sociometric badges, email networks, internal digital chatter, video and camera data

• Data generated through new assessment tools• online assessment (e.g. MOOCs), test-based video games

Vast increase on data on spatial and temporal movements

• Micro-measurement of personal productivity

• Team productivity

• Organizational productivity

http://www.flickr.com/photos/walkingsf/sets/72157623971287575/

How can the big data "microscope" aid workforce related decisions?

• Remove cognitive biases and reliance on intuition• We don't know what makes us productive

(especially information workers)

• Enables quantification of the impact of HR-related decisions

• What is our inability to retain engineers costing us?

How are employers using analytics?

• Predicting retention/turnover for high-skill employees

• How desk location affects information flows

• Using internal communications to predict employee performance

• What (other) job titles predict success in the opening I am trying to fill?

• Where are we likely to have skill gaps in ten years?

• What is the return on investment to a specific HR policy?

• Can applicant profiles based on Internet data outperform traditional 'signals' (e.g. education)?

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near future?

Lessons learned (so far)• Data is not a substitute for conceptualization

• Knowing the right questions to ask (domain expertise) is critically important

• The interest in analytics is likely to outpace results in the short-run as employers put the right pieces in place

• 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

Potential barriers to using analytics

• A new generation of technical and analytic skills

• Collection and management of new data sources

• Policies regarding data collection and use (privacy)

Questions?Don’t forget to sign up for the next event:

http://bit.ly/mhpworksmarter

Available in print and eBook