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

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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

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  • 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.
  • (maybe skip)?
  • Leading with Data: Boost Your ROI with Open and Big Data

    1. 1. Leading with Data: Boost Your ROI with Open and Big Data Join the conversation with @MHBusiness @sonnytambe @JoelGurin Use #worksmarter
    2. 2. 2
    3. 3. Find me at OpenDataNow.com and @joelgurin 3
    4. 4. Setting the Stage My Journey Through the Datasphere 4
    5. 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. 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. 6
    7. 7. Setting the Stage Open Data Changes the World For: • • • • • • • Entrepreneurs Established businesses Governments Investors Scientists Journalists Consumers 7
    8. 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 8
    9. 9. Setting the Stage 9
    10. 10. Liberating Federal Data
    11. 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 11
    12. 12. Federal Data Federal Data Today 12
    13. 13. Federal Data The New Open Data Policy • • • • • “Presumption of openness” Machine-readable Reusable Timely Developed with consultation 13
    14. 14. Federal Data They Agree On – The DATA Act 14
    15. 15. Data-Driven States and Cities
    16. 16. State and City Data Help for K-12 Households Bill Jackson, CEO 16
    17. 17. State and City Data 17
    18. 18. Data-Driven Cities How Wired Cities Use New Data •Optimize operations •Monitor infrastructure conditions •Plan infrastructure •Public health •Emergency management 18
    19. 19. State and City Data • • • • Metro Chicago Data New York: The Mayor’s Geek Squad Code for Philly Palo Alto’s open finances 19
    20. 20. State and City Data City Data: Next Bus for Commuters
    21. 21. State and City Data Sim City Meets Participatory Budgeting
    22. 22. State and City Data DC’s Experiment: A City Report Card Washington Mayor Vincent Gray 22
    23. 23. State and City Data • Sharing personal data for public good • Pulse Point: “Enabling Citizen Superheroes” 23
    24. 24. Open Data Shapes Reputation and Brands
    25. 25. Reputation and Brands Social Media: 2 Billion Tweets a Week 25
    26. 26. Reputation and Brands The Reputation Police Michael Fertik, CEO 26
    27. 27. Reputation and Brands Sentiment Analysis: Emotion Meets Computation 27
    28. 28. Reputation and Brands Open Data from Consumer Complaints Courtney Powell and A.J. Fouty, cofounders 28
    29. 29. Reputation and Brands 29
    30. 30. Reputation and Brands 30
    31. 31. Driving Business Growth
    32. 32. Driving Business Growth Open Data Fuels Businesses in All Sectors Health Education Financial Services Energy Use Transportation 32
    33. 33. Driving Business Growth From Weather Insurance to Green Revolution Climate Corporation offices in San Francisco 33
    34. 34. Driving Business Growth 40K Public Companies, Updated Daily 34
    35. 35. Driving Business Growth Healthcare: The Next Big Frontier? 35
    36. 36. Driving Business Growth 36
    37. 37. Driving Business Growth Data for Energy Savings Ogi Kavazovic, VP Marketing & Strategy 37
    38. 38. Driving Business Growth Managing Open Data: A Winning Strategy 38
    39. 39. Finding the Value: The Open Data 500
    40. 40. 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
    41. 41. Open Data 500 41
    42. 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 • • • • 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
    43. 43. Open Data 500 43
    44. 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. 45. 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
    46. 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. 47. 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
    48. 48. Vast increase on data on spatial and temporal movements • Micro-measurement of personal productivity • Team productivity • Organizational productivity
    49. 49. http://www.flickr.com/photos/walkingsf/sets/72157623971287575 /
    50. 50. 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
    51. 51. 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?
    52. 52. 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
    53. 53. 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)
    54. 54. Questions? Don’t forget to sign up for the next event: http://bit.ly/mhpworksmarter Available in print and eBook

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