On 2004-07-13 09:25:00, Allan Engelhardt wrote in CYBAEA Journal:
I proposed a slightly provocative definition of social software when we were discussing it at the July 2004 London Symposium on Social Tools for the Enterprise.
My concern with most current social software tools is that they focus too much on the content. Perhaps this reflects that many of the companies and individuals who are active creating software have a background in knowledge management.
To me, that is the wrong focus. Content is the means to an end, not the end. Think of content as the slug’s trail: it shows you where you’ve been. It reminds you of the path you took to get where you are now. Many active bloggers use their blogs as a sort of extended memory for exactly this purpose. In the enterprise setting, there is tremendous value to be had in making knowledge, experiences, and values explicit and amenable to search and categorisation.
But the real value of social software in the enterprise is not in the content. Content doesn’t do anything. People do; and what makes a difference to the enterprise is people coming together innovating and changing the organisation.
The value of social software is in creating social connections where none existed, or in strengthening existing connections. Key success factors are to make everything addressable (links persist connections) and to make everything a feed. The last point is really important: social software must enable me to discover conversations and then facilitate me contributing to the discussion. That is why e-mail, critical as it is to most businesses, is not a social software tool.
Lee Bryant really stressed the everything is a feed
and the importance of managing feeds (as opposed to individual content items) as critical to the success they have had with the NHS.
[End]
On 2010-07-13 07:47:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
I am not sure apeescape’s ggplot2 area plot with intensity colouring is really the best way of presenting the information, but it had me intrigued enough to replicate it using base R graphics.
The key technique is to draw a gradient line which R does not support natively so we have to roll our own code for that. Unfortunately, lines(..., type="l") does not recycle the colour col= argument, so we end up with rather more loops than I thought would be necessary.
We also get a nice opportunity to use the under-appreciated read.fwf function.
Read more (~535 words).
On 2010-06-22 11:45:00, Allan Engelhardt wrote in CYBAEA Journal:
We have a mild obsession with employee productivity and how that declines as companies get bigger. We have previously found that when you treble the number of workers, you halve their individual productivity which is scary.
We now re-do the analysis four years later and, just because we can, we are using the leading companies of the London stock exchange instead of the largest American companies.
The results still hold. We called it the 3/2 rule: treble the number of workers and you halve their individual productivity. Large companies with ten times the number of employees are ¼ as productive as their smaller competitors.
Employee productivity is a big issue. If all the FTSE-100 companies achieved their average profits per employee, then the index would generate almost £1 trn of additional net profits for the economy.
Read more (~245 words).
On 2010-06-22 11:20:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
We have a mild obsession with employee productivity and how that declines as companies get bigger. We have previously found that when you treble the number of workers, you halve their individual productivity which is mildly scary.
We revisit the analysis for the FTSE-100 constituent companies and find that the relation still holds four years later and across a continent.
Read more (~763 words, 5 comments).
On 2010-06-17 09:05:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
Following on from my previous post about improving performance of R by linking with optimized linear algebra libraries, I thought it would be useful to try out the five benchmarks Revolutions Analytics have on their Revolutionary Performance pages.
Read more (~300 words, 2 comments).
On 2010-06-15 10:21:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
Can we make our analysis using the R statistical computing and analysis platform run faster? Usually the answer is yes, and the best way is to improve your algorithm and variable selection.
But recently David Smith was suggesting that a big benefit of their (commercial) version of R was that it was linked to a to a better linear algebra library. So I decided to investigate.
The quick summary is that it only really makes a difference for fairly artificial benchmark tests. For “normal” work you are unlikely to see a difference most of the time.
Read more (~934 words, 1 comments).
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