Published on February 26, 2014
Leading with Data: Boost Your ROI with Open and Big Data Join the conversation with @MHBusiness @sonnytambe @JoelGurin Use #worksmarter
Find me at OpenDataNow.com and @joelgurin 3
Setting the Stage My Journey Through the Datasphere 4
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.
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. 6
Setting the Stage Open Data Changes the World For: • • • • • • • Entrepreneurs Established businesses Governments Investors Scientists Journalists Consumers 7
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 8
Setting the Stage 9
Liberating Federal Data
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 11
Federal Data Federal Data Today 12
Federal Data The New Open Data Policy • • • • • “Presumption of openness” Machine-readable Reusable Timely Developed with consultation 13
Federal Data They Agree On – The DATA Act 14
Data-Driven States and Cities
State and City Data Help for K-12 Households Bill Jackson, CEO 16
State and City Data 17
Data-Driven Cities How Wired Cities Use New Data •Optimize operations •Monitor infrastructure conditions •Plan infrastructure •Public health •Emergency management 18
State and City Data • • • • Metro Chicago Data New York: The Mayor’s Geek Squad Code for Philly Palo Alto’s open finances 19
State and City Data City Data: Next Bus for Commuters
State and City Data Sim City Meets Participatory Budgeting
State and City Data DC’s Experiment: A City Report Card Washington Mayor Vincent Gray 22
State and City Data • Sharing personal data for public good • Pulse Point: “Enabling Citizen Superheroes” 23
Open Data Shapes Reputation and Brands
Reputation and Brands Social Media: 2 Billion Tweets a Week 25
Reputation and Brands The Reputation Police Michael Fertik, CEO 26
Reputation and Brands Sentiment Analysis: Emotion Meets Computation 27
Reputation and Brands Open Data from Consumer Complaints Courtney Powell and A.J. Fouty, cofounders 28
Reputation and Brands 29
Reputation and Brands 30
Driving Business Growth
Driving Business Growth Open Data Fuels Businesses in All Sectors Health Education Financial Services Energy Use Transportation 32
Driving Business Growth From Weather Insurance to Green Revolution Climate Corporation offices in San Francisco 33
Driving Business Growth 40K Public Companies, Updated Daily 34
Driving Business Growth Healthcare: The Next Big Frontier? 35
Driving Business Growth 36
Driving Business Growth Data for Energy Savings Ogi Kavazovic, VP Marketing & Strategy 37
Driving Business Growth Managing Open Data: A Winning Strategy 38
Finding the Value: The Open Data 500
Open Data 500 What’s the Value of Open Data? • • • • • • 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 40
Open Data 500 41
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 • • • • 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 42
Open Data 500 43
Big Data and HR Prasanna Tambe NYU Stern School of Business email@example.com Leading with Data: Boost Your ROI with Open and Big Data February 26, 2014
Existing sources of HR data • Data collected during recruiting, hiring • • Data routinely collected by organizations • • employment histories (resumes), skills, interview and test evaluations 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 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
Emerging sources of HR and workforce data • Online/Internet data • • Digital traces from work activities • • internal knowledge boards, internal corporate network activity, finegrained measures of project and task performance Social and physical network data • • 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 • 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
How can the big data "microscope" aid workforce related decisions? • Remove cognitive biases and reliance on intuition • W don't know what makes us productive (especially e information workers) • Enables quantification of the impact of HR-related decisions • W is our inability to retain engineers costing us? hat
How are employers using analytics? now near future? • Predicting retention/turnover for high-skill employees • Where are we likely to have skill gaps in ten years? • How desk location affects information flows • What is the return on investment to a specific HR policy? • Using internal communications to predict employee performance • Can applicant profiles based on Internet data outperform traditional 'signals' (e.g. education)? • What (other) job titles predict success in the opening I am trying to fill?
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)
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