Albeit time is a critical dimension in today’s every business, it is curiously absent from most discussion around Enterprise 2.0. Adoption time scale is an issue we will eventually empirically solve as more and more successful case studies are publicized. Just don’t put too much expectation on this data beyond “fail fast and often”, as Dion Hinchcliffe stated it, since adoption can merely be measured on an individual basis, and each case is unique. But beyond that, even more cruelly absent from the debates going on are operational time scales.
It’s all in the process. Really?
Reducing time consumption in complicated tasks’ chains is one of the main objectives of the sophisticated processes which drive our organizations. (Repeatability and industrialization of production is the other one) To achieve productivity and efficiency improvements, they release the burden of “reinventing the wheel” by minimizing the number, and complexity, of decision which have to take place along the chain.
Recent technologies, like SAP’s Gravity or Thingamy, suggest that BPM can be efficiently improved through collaborative work, which opens a new path to Enterprise 2.0 (I won’t discuss here my personal view on the discrepancy between collaborative enterprise and process based organizations). But even if considered from an integrated-to-the-workflow angle, this approach doesn’t take into account the time factor: how long will it take to optimize a process in a collaborative way? To what extend is “how long” acceptable? When is the result of collaborative work stated satisfactory enough to be considered as an outcome?
Thinking of Enterprise 2.0 from a process perspective doesn’t free us from the major shortcoming of all E2.0 frameworks so far: making decisions is one of the main tasks of organizations. This takes time, and we lack methods to understand, leverage and quantify collaborative decision making’s time scales.
Complexity at work
Processes helped shaping big, complicated organizations from the industrial era, but cannot encompass the complexity of our hyperlinked economy. Industrialization has reached a tipping point beyond which traditional productivity funnels must be rethought. Of course, admitting that organizations are complex adaptive systems brings new, and sometimes overwhelming, challenges, but it also highlights some aspects diretcly relevant to the time issue.
Complex adaptive systems (CAS) are self-similar and embedded, which means that communities and collaborative teams are CAS themselves, and their time scale is independent from the global time scale (of the process, of the company…).
CAS are, well, adaptive, which means that the definition of an absolute time scale is out of reach. Time in execution depends on initial factors, so setting fixed time rules for a collaborative work to provide an outcome seems irrelevant. Timeframes are relative to the environment in which they are measured.
CAS are non-linear, which trumps any attempt to measure time and set it as a process variable in a ‘traditional’ way. Statements like ‘you have two days to come to a consensus and find an answer’ are irrelevant. Instead, several time states, several thinking processes, can cohabit in a collaborative initiative.
Time-relative processes
We need to think differently here. Complexity and quantum theories allow us to encompass time, not as an absolute forward mechanism, but as a probabilistic one. While we cannot quantify the time needed to take a decision, we can measure the percentage of consensual adoption of a collaborative decision. Setting thresholds to this percentage would allow for triggering the next task or process, without compromising the global performance of enterprise.
Instead of being dependent on fixed task-based rules, and to be able to address the operational time scales concern Enterprise 2.0 is facing, my bet is that we will see the emergence of new relative time-based processes, to harness the true power of networked teams and communities. I hope you will add your view on this crucial issue.
