Go Open Data Conference Case Study — Fireside Analytics

Fireside Analytics

Making Data Science Accessible to Everyone

Go Open Data Conference Material

Interactive Tableau Public Dashboard: "Where machines could replace humans — and where they can't (yet)" - McKinsey Global Institute (2017)

Workbook: InternationalAutomation

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Where machines could replace humans — and where they can't (yet)

McKinsey analyzed the impact of automation across 54 countries covering 78% of the global labor market to assess the percentage of time spent on activities with the technical potential for automation by adapting currently demonstrated technology.

Use this dashboard to explore the potential for automation in your sector and country of interest.

Variation in potential for automation by sector: Employees Global

  • Agriculture, forestry, fishing and hunting
  • Manufacturing
  • Retail trade
  • Construction
  • Administrative and support and waste management and remediation services
  • Educational services (including privately owned)
  • Health care and social assistance
  • Transportation and warehousing
  • Other services (except federal, state, and local)
  • Accommodation and food services
  • Finance and insurance
  • Professional, scientific, and technical services
  • Wholesale trade
  • Real estate and rental and leasing
  • Information
  • Mining
  • Arts, entertainment, and recreation
  • Utilities
  • Management of companies and enterprises

Automatability % Weighted

  • 30%
  • 60%

Focus

Employees

The grey vertical line represents the global average potential for automation.

Worldwide potential for automation: Employees Sector(s):All

Region

Global

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Focus metric

Source: EMSI; Oxford Economic Forecasting; US Bureau of Labor Statistics; McKinsey analysis

For more on this research, see our article:

Worldwide potential for automation: Employees Sector(s): All

Selections apply to entire dashboard...

Wage data were not available for 8 countries: Bermuda, Cote d'Ivoire, Ethiopia, Ghana, Mozambique, Senegal, Taiwan, and Tanzania. Some country's employee data omitted the informal economy; in these cases, adjustments were made based on discussions with industry experts. Source data for some countries do not contain all 19 sectors.

Employees

View on Tableau Public

Instructions to access R in Data Scientist Workbench.

These are the instructions for the hands-on case study conducted by Fireside Analytics at the Go-Open Data Conference in 2017. We will demonstrate the use of open source programming languages like R and Python in the analysis and visualization of a local Open Data Set. R programming is done in IBM’s cloud hosted environment, Data Scientist Workbench.

The JSON file can be downloaded here:
JSON File

The R Script file can be downloaded here:
Go Open Data Tutorial_RScript