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Estimating the Numbers of End Users and End User Programmers

Estimating the Numbers of End Users and End User Programmers. Christopher Scaffidi Brad Myers Mary Shaw Carnegie Mellon University EUSES Consortium VL/HCC ’05, Sep 23, 2005. The Old 55M Estimate.

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Estimating the Numbers of End Users and End User Programmers

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  1. Estimating the Numbers of End Users and End User Programmers Christopher Scaffidi Brad Myers Mary Shaw Carnegie Mellon University EUSES Consortium VL/HCC ’05, Sep 23, 2005

  2. The Old 55M Estimate • The number of end-user programmersin the U.S. alone is expected to reach 55 millionby2005, as compared to only 2.75 million professional programmers.

  3. Our New 90M Estimate • The number of usersin U.S. businesses is expected to exceed 90 millionby2012, • including over 55 million users ofspreadsheets and/or databases,as compared to under 3 million professional programmers.

  4. Outline • The Basic 55M Estimation Method • 55M End User Programmers in 2005 • Extending the Method • 90M Users in 2012 • 55M Spreadsheet and/or Database Users in 2012 • Conclusions

  5. History and Purpose of the 55M Estimate • First appeared in COCOMO (circa 1995) • COCOMO is Boehm’s model for estimating the cost of developing software applications • How many people would benefit from COCOMO? • To answer this, Boehm projected… • # of professional programmers (2.75M in 2005) • # of end user programmers (55M in 2005) • .

  6. Step #1: Project Worker Counts for 2005 • Steps to generate the estimate • Get the Bureau of Labor Statistics (BLS) occupation projections for 2005

  7. Step #2: Estimate what Fraction of Workers Use the Computer • Steps to generate the estimate • Get the Bureau of Labor Statistics (BLS) occupation projections for 2005 • Get the BLS computer usage rates by occupation for 1989

  8. Step #3: Multiply and Sum Up • Steps to generate the estimate • Get the Bureau of Labor Statistics (BLS) occupation projections for 2005 • Get the BLS computer usage rates by occupation for 1989 • Multiply worker projections by computer usage rates Sum turns out to be -----> 55 M

  9. Step #4: Apply Adjustments • Steps to generate the estimate • Get the Bureau of Labor Statistics (BLS) occupation projections for 2005 • Get the BLS computer usage rates by occupation for 1989 • Multiply worker projections by computer usage rates • Finally, adjust upward to account for rising usage rates, and adjust downward because not all users are programmers. • Boehm originally relied on judgment to provide adjustments. • The two adjustments actually ended up canceling out!

  10. Our Paper Provides Better Adjustments • Adjustment #1: Rising Usage Rates • Use innovation diffusion to model rising usage rates. • We also extend the estimates to 2012. • Adjustment #2: Not Everybody Programs • Be precise about what aspect of “programming” to address. • We can focus on spreadsheet/database users. • We can focus on users who self-reportedly “do programming.” • Each of these groups vastly outnumbers professionals.

  11. Adjustment #1: Rising Usage Rates • We incorporated additional BLS data • 1984 • 1989 (the only year used in old 55M estimate) • 1993 • 1997

  12. Adjustment #1: Rising Usage Rates

  13. Adjustment #1: Rising Usage Rates • Innovation diffusion theory to the rescue • Innovations diffuse through populations like diseases. • Researchers studied various functional forms for modeling this. • The simplest form (and most generally applicable) is S-shaped

  14. Adjustment #1: Rising Usage Rates • Projecting the computer usage rates • The S-shaped functional form had 3 free parameters (K, m, b) • We have 4 measurements from BLS (1984, 1989, 1993, 1997) • So we can fit to functional form for each occupation category • (Note that with so few points, “goodness of fit” means little.)

  15. Adjustment #1: Rising Usage Rates • Projecting the computer usage rates • The S-shaped functional form had 3 free parameters (K, m, b) • We have 4 measurements from BLS (1984, 1989, 1993, 1997) • So we can fit to functional form for each occupation category • (Note that with so few points, “goodness of fit” means little.) • A somewhat better estimate • Get the BLS’s latest occupation projection (which happens to be for the year 2012) • Plug in t=2012 to forecast future computer usage rates • Multiply and sum as Boehm did • Result: 90M users in 2012

  16. Validation • Does it match 2001 BLS count of workplace users? • BLS modified their questions slightly in 2001 • Our fit predicts 71.9M users; actual = 72.3M • Incorporating this 2001 BLS data into our fit raises our estimate for 2012 from 90M users to 96M users • Does it match 2003 Forrester count? • They found 129M users (work or home) age 18-64 • Our fit predicts 80M workplace users for 2003 • Use BLS 2001 to adjust for age, add in home (non-work) users • Our result for comparison: a little over 123M (to their 129M) • Excellent match.

  17. Examining Assumptions • We replace one assumption for another. • Old assumption: based on judgment • New assumption: applicability of innovation diffusion • Implication of using our assumption • Questionable assumption! Ongoing improvements in computers will probably drive adoption still higher. • Therefore, 90M is probably a lower bound.

  18. Adjustment #2: Not All Users Program • One big count (of all users) isn’t too helpful. • It can only be used to argue, “This sure is big.” • Relative usefulness of a collection of numbers • Not all users have the same needs, strengths, and goals! • How can we break down the estimate into smaller groups, to guide research and development?

  19. Adjustment #2: Not All Users Program • One approach: Group users by application usage. • In 2001, BLS asked how workers use computers. • Total of 72M people used computers at work. • Over 60% of total (45M) used spreadsheets or databases. • About 15% of total (11M) said they “do programming.”

  20. Adjustment #2: Not All Users Program One approach: Group users by application usage. • In 2001, BLS asked how workers use computers. • Total of 72M people used computers at work. • Over 60% of total (45M) used spreadsheets or databases. • About 15% of total (11M) said they “do programming.” • Carrying this forward to yield 2012 lower-bounds... • Total of 90M people will use computers at work. • Over 60% of total (55M) will use spreadsheets or databases. • About 15% of total (13M) will say they “do programming.” • BLS projects only 3M professional programmers. Our Extended Method

  21. Conclusions • New estimates for American workplaces in 2012: • At least 90M users • At least 55M spreadsheet and/or database users • About 13M users will say they “do programming” • Fewer than 3M professional programmers • Our estimates are based on improved adjustments: • Model adoption rates using innovation diffusion theory • Group users according to how they use computers

  22. Thank You • To VL/HCC for the opportunity to present • To NSF, Sloan, and NASA for funding • To Barry Boehm for discussions of his 55M estimate

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