While researching structured collaboration techniques, I came across some interesting work people are doing. Mindquarry, for example, provides a model of collaboration patterns based on 4 elements – people, productivity software, collaborative software and methods. I had earlier referred to Mindtools, who provide a rich set of structured collaboration techniques, like for example starbusting, which is a form of brainstorming. Also, Value based management offers a host of techniques, models and theories.
Essentially, structured technology aided collaboration techniques are a medium through which learning efficiencies can be increased. These techniques:
- are contextual to domain
- are contextual to collaboration type (say, brainstorming vs voting)
- are open or close ended (in terms of time, scope, boundaries etc)
- could be ad-hoc or planned
- are quantifiable (both quantitatively and qualitatively speaking)
- are historically referenceable (audit trails for recorded collaborations)
- have rules of engagement
- can be structured to the desired level (sequence of activities, organization of inputs, permissions and access roles)
- are sensitive to scale of audience, available knowledge and other physical parameters
- result in trackable outputs/analytics
The logical next step, from a design perspective, is to attempt to model them. Aldo de Moor’s paper on Community Memory Activation with Collaboration patterns yields some insights on what patterns could be modelled. The abstract for the paper is:
We present a model of collaboration patterns as reusable conceptual structures capturing essential collaboration requirements. These patterns include goal patterns (what is the collaboration about?), communication patterns (how does communication to accomplish goals take place?), information patterns (what content knowledge is essential to satisfy collaborative and communicative goals?), task patterns (what particular information patterns are needed for particular action or interaction goals?), and meta-patterns (what patterns are necessary to interpret, link and assess the quality of the other collaboration patterns?). We show how these patterns can be used to activate communities of practice by improving their collective, distributed memory of communicative interactions and information. We outline an approach that structures how collaboration patterns in communities of practice can be elicited, represented, analyzed, and applied. By presenting a realistic scenario, we illustrate how community memory could be activated in practice.
The other key component is to understand what is the need to collaborate and the forces impeding the required collaboration. This is key to understanding whether collaboration techniques shall be used, substituted by informal methods or not used at all. It is important to understand if they are “over sold and under used” or are “methods seeking an application” or are really cost-effective or intuitive. We have seen that in software engineering too and this may require change management to implement in enterprises.
In other words, the challenge is not quite really all about the technology or process, but is perhaps more about the individual mindset and the overall objectives with which structured collaboration techniques are to be implemented (basically saying that a great process or tool does not automatically ensure collaboration that follows the process or uses the tool or format).
It goes back to us, as individuals, and how we collaborate as subjects, alone or in teams or in networks. If the capability to collaborate in structured ways is learnt and becomes “native” so will adoption on a more widespread basis. On the other hand, organizations or learning delivery modalities can include, as mandatory components, such patterns, tools or processes as part of the workflow.