We revisited the 3/2 rule of employee productivity using a larger data set and considering each sector independently.
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.
About a year ago we did some work with a London-based private equity fund. The problem was information overload and the idea was to bring together multiple data sources, both public and private, to one data store that could add tags and other meta-data and build synthetic RSS feeds based on search criteria (and even adaptive learning).
Tom Peters made me think about how we define success. If you had a list of companies like Netscape, Microsoft, IBM, HP, and Oracle, which ones would you consider the the winners and which one(s) is the loser(s)?
The truth. It is not always easy to get to it. If you are doing surveys or questionnaires you will know that people do not always reply honestly but are biased towards social norms. Ask for which sexually transmitted diseases a person is currently suffering from, and you will get lower responses than the frequency of the diseases in the population.
The XSLT + AJAX data grid described over on XML.com looks very interesting and solves a real and very common problem. Be sure to try the examples: there are lots of features there.
“Data driven business” is one of the new buzzwords, and we are completely behind an approach to doing business that is fouded on real, observed data and rational decision. John Kay’s recent column Don’t box yourself in when making decisions (from the FT or from John Kay’s site) is a timely reminder of some of the hard limitations of modeling.