On 2006-10-16 18:07:00, Allan Engelhardt wrote in CYBAEA Journal:
The more employees your company has, the less productive each of these employees are. It is a generalization, of course, but a useful one and one that is confirmed by most people who have worked for growing organizations. As the company grows, so does the internal processes and the layers of bureaucracy, and the time spent on communications grows rapidly.
It is, however, useful to look at the actual numbers. How much does productivity decrease as the organization grows? The answers are frankly frighting.
To look at the effect in large organizations, we considered the constituents of the Standard & Poor's S&P 500 index of leading companies in leading industries of the U.S. economy.
For each company we collected information on revenues, gross profit, EBITDA, and the number of employees. After removing some companies with missing or hard-to-use data (e.g. negative profits), we ended up with 475 large, publicly quoted American companies.
As a metric for employee productivity we chose profits per employee. You can re-run the analysis with EBITDA or some other metric and the basic results do not change. See below for how to get the files.
We then plotted in a log-log plot the profits per employee against the number of employees for the 475 companies in nine different industry sectors.
The profit per employee versus the number of employees for 475 of the companies in the S&P 500 index.
(Click on the image for a larger version.)
| Min. | 8,201 |
| 1st Qu. | 88,961 |
| Median | 167,089 |
| Mean | 298,578 |
| 3rd Qu. | 311,342 |
| Max. | 4,689,266 |
Naturally there is enormous variation in employee productivity in such a diverse set of companies and industry sectors. The largest employer is Wal-Mart with $75 billion profit and 1.8 million employees ($41,800/employee). The three top slots in terms of employee productivity are all in the financial sector, with Ambac Financial Group's 354 employees generating $1.66 billion profits ($4.7M per employee). At the bottom we find Darden Restaurants whose 157,300 employees each contribute $8,201 to the company's profits.
However, the trend is clearly downwards. Fitting a power law give a slope of -0.68. This is scary. Three raised to the power of -0.68 is 0.47. This means that when you triple the number of employees, you halve their productivity. Or: When you add 10% employees the productivity of each drops by 6.3%. Of course, since 3 times half is greater than one, your total profits are typically growing.
What causes it? Clearly, there is some element of self-selection: companies sometimes rationally choose to be in high-volume, low-margin markets. But I suspect that is also used as an excuse. There are more possibilities to encounter expensive relationship friction, but also more opportunities to resolve them.
I think it is largely down to communications: the degree to which a vision is shared and the effective dissemination of new ideas ideas and working practices. Innovation velocity is dependent on collaboration; and collaboration among larger groups and creation networks require different skills and tools than what most executives are used to from smaller situations and is therefore often underestimated.
Productivity in large enterprise is clearly a subject that deserves attention. If the S&P companies all achieved their average productivity, then they would between them generate an additional $2.9 trillion profit between them (with both winners and losers, of course).
The data and analysis scripts are available in the file sp500.tar.gz. If you wish to run the analysis, then you must install R, a wonderful software environment for statistical computing and graphics. On many modern systems you can simply type
% pkcon install R
as root and then unpack the files and run the analysis as
$ tar zxvf sp500.tar.gz $ cd sp500 $ ./analysis # Creates sp500.png, sp500.RData, and analysis.Rout $ cat analysis.Rout # View output from analysis command
On legacy systems you can download R from the project site and install it. Then you must either run it and open the analysis.R file in the application, or you can double-click on the sp500.RData file which should launch R with the data and command history loaded (try summary(sp) and summary(fm) to get started). You may also need to pay for a program to unpack the archive.
On 2010-03-08 14:46:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
I needed a fast way of eliminating observed values with zero variance from large data sets using the R statistical computing and analysis platform. In other words, I want to find the columns in a data frame that has zero variance. And as fast as possible, because my data sets are large, many, and changing fast. The final result surprised me a little.
Read more (~501 words).
On 2009-08-17 09:18:00, Allan Engelhardt wrote in CYBAEA Journal:
We knew the potential existed already, of course. Mobile devices in the USA generates some 600 billion transactions per day, each tagged with the location and time. Jeff Jonas: Every call, text message, email and data transfer handled by your mobile device creates a transaction with your space-time coordinate[...].
The mobile operators have this data, of course. We all know this (especially here where we have been using some of it for social network analysis). No real surprises here, except perhaps in the volumes.
But did you know that the operators are sharing your data? What is new, at least to me, is that this data is being provided to third parties that are leveraging specially designed analytics to make sense of our space-time-travel data.
Read more (~449 words, 1 comments).
On 2009-07-27 19:38:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
O'Reilly's recent publication Beautiful Data has a chapter by Jeff Jonas which is enough reason in itself for me to recommend it. The chapter, Data Finds Data, is also available as a PDF download.
Read more (~66 words).
On 2009-07-22 13:37:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
This is by far the best description of why traditional parallel databases (like Teradata, Greenplum et al.) is a evolutionary dead end. But much more than a theoretical discussion, they have built a solution which they call HadoopDB. It is based on Hadoop, PostgreSQL, and Hive and is completely Open Source. Alternative, column-based, backends to PostgreSQL are being implemented now. Read: Announcing release of HadoopDB.
Read more (~83 words).
On 2009-07-22 06:59:00, Allan Engelhardt wrote in CYBAEA Journal:
The nice people at Velocity has released The B2B Content Marketing Workbook. It is behind a registration wall which means we wouldn’t normally recommend it but you can just type junk in the fields if you are not comfortable with giving your personal details to a marketing agency. (Think about it....) If you are relatively new in the B2B world, say having joined a professional services or consulting organization, you may find this one useful.
Read more (~263 words).
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