As ever increasing speed and amount of available knowledge are reshaping day after day the world we live in, it looks like a gap is widening between the way most businesses still operate and the capabilities needed to deal with our environment’s growing complexity.
Organizational responses to overall increasing speed too often are costs reductions, automation and optimization. Efficiency has become the new business’ black, and BPR is its credo. But speed isn’t only a factor we have to cope with; it is deeply transforming the nature of our relationships to the world. As Paul Virilio wrote: “The speed of light does not merely transform the world. It becomes the world. Globalization is the speed of light.” When considering speed as an external constraint, companies are keeping themselves deliberately out of many of today’s new fundamental dynamics. Pushing the gas pedal won’t drive anyone faster than the engine was built for, and current business engine was assembled in the — industrial – XIXth century, and amended more than thirty years ago with the rise of the process-driven enterprise.
On every subject, for every aspect of our life, the quantity of information available is so tantalizing, that we cannot simply store all information we need at some time into our memory anymore. Such abundance has transformed our cognitive process: we now mostly remember links and references to information, extending our memory map, our knowledge, to a network of peers and sources. The more information is made available, the stronger and wider this network becomes, and the faster knowledge is able to flow. This networked nature of our representation of the world in turn participates in increasing the global speed of the world.
One major Enterprise 2.0 frameworks’ motto is to help companies to deal better with this information overabundance, to make organizational knowledge expandable and faster to access, with the help of social software: connecting with the right information at the right time. So far so good. Power has shifted from knowledge to knowledge sharing. Cool; but for how long? Even if there is little hope to break the 90-9-1 rule in organizations, information is becoming ubiquitous in an exponential way.
A recent attempt to deal with this growing quantity of knowledge flows is content curation, to allow for a better distribution of information. Unfortunately, this only helps facilitating knowledge acquisition when the desired outcome is already known, since what is relevant to you isn’t necessarily so for someone else, or even in another situation. Context is missing here. What we need is another way to filter information in context, another way to make information usable through non-deterministic tasks. The real power resides in knowledge use, not in knowledge sharing.
Another motto is to start with clear objectives. Business objectives… When quantity of information and speed of transmission are changing our way of thinking, are deeply transforming our lives, is it reasonable to believe that aligning corporate practices with private habits will spare us to rethink the way we work, the way we do business? Can we seriously think that getting from silos to clusters will save us deeper organizational transformations? Yes, we have to set up business objectives to any collaborative initiatives, but we have to consider which new kind of objectives can be achieved through social business, and what it means for the future of business.
Umair Haque recently stated that “Making Room for Reflection Is a Strategic Imperative“. This is a nice injunction, backed with lucid and thoughtful arguments, but can we just “stop doing”, in an environment where speed has become the very stuff of things? I don’t believe so, taking a break is no more an option, and what we really need instead is to think differently. Accelerated growth of available data requires new ways to acquire knowledge and put it into action. In such a situation, unlearning has become as important as learning.
As most of our knowledge is now stored outside of our memory, the challenge not only lies in matching real-world situations with experiences stored in our memory, but also in pairing those situations with the right external connections, in order to gain access to the relevant knowledge. Not only do we have to deal with data, in anything but routine thinking, but with people, and our cognitive process now encompasses our networks. Information retrieval, and learning, had become inherently hyper-connected.
From internal “social” initiatives (let us consider them as knowledge networks rather thantrue collaborative environments for demonstration purpose) to customers’ relationships, present process-based approach to business is broken. Business processes expect a deterministic output; they rely on repeatability and explicit workflows, which often proves itself far from the nature of human relationships. The cognitive process, instead, is a non-linear mechanism, able to make sense from disjointed information. Cognition doesn’t appeal for processes, but for patterns. Furthermore, processes suit perfectly machine-to-machine communication. Human-to-machine communication needs to take into account user experience, which hardly resumes to processes, and human-to-human communication is all about weak signals and pattern recognition.
Venessa Miemis has written a great post about the importance of patterns recognition in the cognitive process. To quote her: “there are strong and weak signals all around us, patterns, which indicate a change has happened, is happening, or has the potential to happen”. Business processes work as long as nothing changes, or at least changes slowly, which happens less and less in present business environments. Dynamic patterns, instead, are emergent phenomena of complex systems. They are highly adaptive and relate not only to existing flows (whether they be knowledge, work, customer journey, etc.), but also to how these flows change over time. In other words, they can be harnessed as predictive tools as well as operational routines design. A simple change in an underlying process might translate into huge and fast modifications of related pattern. Looking at the way patterns change (sometimes dramatically) in our networks provides us critical clues on how to improve broken processes, or on when to seamlessly switch to another one.
Here is a short summary of dynamic patterns versus processes characteristics:
|Designed on purpose||Emergent and self-organizing|
|Hard to change||Highly adaptive|
|Need stability to perform||Require instability to form|
|May cause formation or modification of a single pattern||May emerge from multiple different processes|
Patterns are already used in business context. Emergent practices leveraged from online communities are patterns. Ethnography, and many design thinking methods, invoke pattern recognition to decipher customers’ behavior. Social learning implies the use of patterns in knowledge acquisition. Dynamic patterns are much more adapted to knowledge work than business processes are.
As they can be broken down to processes, monitoring patterns’ evolution in networks represent a promising way to handle the exceptions crippling most of the processes in which human interaction is involved. Integrating pattern recognition into work might require dedicated competencies, but it also requires new approaches. Adaptive Case Managementis a promising framework to help dealing with knowledge flows rather than with processes, considered the fact that not only should we focus on information, but also on the way information, and connections to it, changes over time. Time has come, to understand that information is not only the blood of our networked organizations, but also their bones