I happened to read Stowe’s blog about Googles new Googleplex, an interesting illustration of their upcoming working environment, where “Google studied, and tried to quantify, everything about how its employees work, about what kind of spaces they wanted, about how much it mattered for certain groups to be near certain other groups, and so forth”.

The blog brings into discussion the challenges when designing spaces, which support interaction, enabling to “maximize casual collisions of the work force.” Googles solution is based on bent rectangles, interesting enough, but  I love the way how Stowe describes this challenge.  He coins a new term  – coincidensity when putting a challenge to Google: ” It will be interesting to hear if Google measures later on to see if they can actually influence coincidensity — the likelihood of serendipity — this way.”

For me coincidensity is the missing piece when explaining serendipitous processes. The likelihood of serendipity, wow! In fact after a good night’s sleep, this wisdom has crystallized to me. I have been arguing in some contexts the (mis)use of the term serendipity, in some contexts the core of serendipity is clearly misunderstood. So instead of trying to develop various applications and environments for supporting serendipity, what people in fact are doing, is trying to support coincidensity. So, welcome all “coincidensity engines” and “coincidensity machines”, now we have found great and illustrative names for all these initiatives. And this gives us the freedom to use serendipity only in those contexts, where all three vital elements of it – unexpectedness, insight and value are included.