Human Resources are complex, both if you mean HR as a Function and if you means humans working within organizations. I am fascinated by such complexity, but sometimes I need a glass of wine (italian, please) to deal with it.
Why Intel is investing in Social Computing
In my post Testing Business Value in Social Networking I shared our results of extensive exploration to determine if there is value in adding professional networking for employee use. The exploratory results moved us forward to creating a modular and integrated social framework to consolidate current "islands" of blogs, forums and wikis and add new capabilities such as the people connection that professional networking brings. We are 1.5 weeks away from launching the first phase of bringing robust social tools in-house to augment and improve the way our employees connect and collaborate today. I get asked a lot about "Why" we are doing this and the value we believe we will bring to Intel. I wanted to share with you the reasons.
Ne segue un articolo bello, interessante ed appassionato... uno di quelli da ritagliare per non perdere tempo a spiegare l'ovvio a chi proprio non ha orecchie. Colgo un paio di idee che bastano e avanzano: Employees Want to Put a Face to a Name, Too much time is lost to find people & information to do your job e, al solito, We reinvent the wheel over and over again.
Open Source will save the world, or will destroy the old economy.
Schiacciati dal peso del potere economico del know-how. L'economia della conoscenza e' arrivata davvero? Forse si', con vent'anni di ritardo, forse... ora vediamo se sara' piu' importante domani inventare una cosa e campare di royalties tutta la vita oppure saper capace di inventare e basta.
Sperss Gaja
Timeline of Trends
Dicono loro: "The presentation of time-oriented data can provide significant insights into both the past and future. The use of timelines that integrate disparate
quantitative time series data and other time-oriented information into a unified visual presentation can reveal patterns, causes, probabilities, and possibilities across complex social, technological, economic, and political systems. Cycles, waves, logistics curves, and other archetypal patterns, when laid over historical data, can provide a deeper understanding of the dynamics of change. Timelines and these archetypal change patterns can also be used in the field of futures studies as key components in a “hypothesis- to-forecast” (exploratory forecast) process to identify potential long-term patterns of change and make long-range (25+ years) forecasts."