Bo Strangert (RD12)

Perspectives on coordination of a planning process 

The question about how to develop an innovative perspective in initial project planning was the subject of some previous comments on R&D. I suggested that two complementary formal representations of planning could be useful: one about the theoretical base of the project task, the other about dynamic coordination of the task process itself (RD5, arborg.se).

The arguments for the first type of representation underscored the need of clarifying theoretical possibilities about the task or goal of the project (RD11). In addition to that purpose, formal models should also contribute to the coordination of the planning process. That’s because suitable models should be a tool for shared knowledge and communication among participants in the planning process.

A review of the concept of ’process coordination' in complex tasks will make the idea more comprehensible. Process coordination is about managing the dynamic interplay between diversity and integration in planning. In reality, this concerns thinking and communication among members in a project team, but also access to external expertise, representing various knowledge domains, and possible end-users of the final project products. Innovative work certainly demands an open and spontaneous discourse among participants. Nonetheless, the risk of significant omissions and bias is imminent during discourses about complex matters. Therefore, forming a progressive initial perspective is crucial. It requires a systematic approach to knowledge acquisition and interpretation, as well as disputing and sharing of ideas.

What are then the general conditions for effective management of the process of project planning? A reasonable answer must take into account that complex tasks demand diverse sources of information and the solutions are a matter of continuously integrating information from different sources into coherent structures. This is achieved by gradual elaboration of a plan and its associated planning process. There are some obvious qualifications to be recalled when devising a perspective of planning:

First, apply scientific principles whenever possible! It means using scientific standards for methods and data treatment, making assumptions explicit in reasoning, following logical rules of inferences, and so on. A prerequisite for the type of projects we have in mind here is that project managers should have scientific qualifications.

Second, mind the disparate backgrounds and views of project participants! Even scientifically based knowledge domains may maintain different preferences about language codes, methods, theory-building etcetera. Different experiences, attitudes, and values are major causes of diversity.

Third, devise apt timing and structuring of events and interactions in the process!

On managing uncertainty and diversity

It seems almost paradoxical to write about how to manage uncertainty and diversity. The concept of uncertainty has a sense of being unmanageable, and a similar association often happens when problems of diversity come up. Yet, these qualities are inherent in complex tasks and have to be managed in some way.

It’s a truism that all planning must begin by searching, selecting, and defining crucial qualities of the project task. Some are self-evident in terms of the task description. And substantial qualities, like physical ones, are easier to deal with than fuzzy social and psychological characteristics. But abstract qualities like uncertainty and diversity are persistently difficult to handle. They are essential sources of our incapability to predict events and act effectively.  However, highly improbable events or products can have a great impact, and some of them are results of human innovation (cf.Taleb, 2010). Thus, innovation is somehow intrinsically connected with the capability to control uncertainty and diversity.

For tasks involving complex social and psychological characteristics, a possible conclusion is that it’s not appropriate to manage uncertainty and diversity by meticulously defining and analyzing multitudes of categories and dimensions of substantial qualities (e.g., diagnostic schemes). That’s because the probability of generating a sufficient set of requirement specifications for a solution would below. The logic of verification according to goal requirements seems to be less appropriate than the logic of discovery where necessary means-end structures must be conjectured and tested by suitable methods in relevant contexts. Consequently, management of uncertainty and diversity could be a question of devising appropriate R&D approaches which focus on the challenges of complexity, that is, open systems characterized by diversity, dynamics, uncertainty, and non-transparency.

About methodological tools

The methods include both conceptual representations (formal models and theoretical representations) and empirical operations (experimentation in general and process interventions in particular). For our purposes of discussion, it could be suitable to part the following forms:

Task models. Formal models and theoretical representations of the project task can take account of possible uncertainties, diversity, and dynamics. The character of complex tasks often requires qualitative models in place of quantitative models based on population statistics.

Process models. Formal qualitative plans for representation and interpretation of empirical operations and events during the R&D process. They include models for follow-up and feedback.

Case study design. Description of case characteristics and context, intervention design, simulations and games.

Data representations of empirical operations, events, behavior observations, self-reports of experiences, results of simulations and games.

On agent factors

The selection of proper participants, external experts and institutions is vital, and so is the building of inventive project teams. Even if it would be desirable to manage most upcoming divergences in agents’ perspectives, there are some common agent factors that are difficult to uncover and cope (RD3). One delicate type is when professional people are blind to their incapability to understand complicated points outside their own area of competence. For example, they may rely on a commonsense understanding of a point that in fact requires a deeper technical mastery. Cases in point are the frequent misuse of advanced statistics and overgeneralized applications of tailor-made IT-solutions. It is inevitable that such problems occur in a discourse including expertise from different domains. Consequently, it is important to make interpersonal communication explicit and open.

The individual agent factors are moderated by other influences, emanating from cultural and social impetus. Forms of communication and management interventions aim to balance variety against uniformity in discourse.

Control of the planning process

The art of timing and structuring project activities demands a vision of continuous improvement from project start to ultimate applications of results in reality. The process should be flexible and sustainable and use self-correcting measures. 

All reasoning about perspective of planning has up to this point emphasized that it is important to form a sort of mini-model of the whole R&D process from the very beginning of the project. Some formal tools for theoretical development of the mini-model were described in RD5, RD10 and RD11. These abstract tools play a significant role for building both shared knowledge and explicit constraints on disputes. However, the corresponding mini-model for the process coordination demands more requirement specifications about activities, their structures and timing. Accordingly, most specifications are worked out gradually during the process to enrich the design approach. Nevertheless, the initial perspective is essential.

Some features of gradual development

Imagine the emergence of a project idea about a device that decreases the risk of collateral damage in connection with work (cf. RD6). The requirement is that it must not interfere with the work itself, or specifically, with the output and quality of work. Such a general task formulation affords an infinite number of options. Then limit the search space to a device that reinforces the capability of visually observing objects (e.g., threats). It is a natural mode of imaging. Next, within a few seconds you have imagined some functions and qualities of possible devices and, probably, also decided that this could be a viable line of thought. If you have an engineering mind, a technical continuation is self-evident, though even other people most likely will focus on physical design of instruments and so forth. In brief, thinking operates easily with concrete images which are enriched with technical knowhow and follow cultural and practical stereotypes. An additional limiting feature of mental modeling is that the objects in focus tend to be situated in specific contexts.

What about considering the complexity issues early in planning? Because abstract concepts have low priority of access in working memory, they normally have little chance of being attended to in early thinking and communication about possible solutions. Therefore, technical considerations are expected to take the lead in forming the perspective of planning.

How should you avoid being stuck to specific task-and-tool reasoning? A general advice is to think more abstractly in terms of functions. For example, there may be significant alternative functions to the first one in mind (e.g., acoustical observation or electronic measurement). And above all, there are superordinate functions that extend the planning perspective (e.g., intelligence functions, functions for countermeasures and decision making). A brief example of extending a perspective by using functional analysis is described in RD6 and R10. A detailed example is presented in RD1, A2.

Figure 1 is a graphic illustration of the same approach. Its origin is the case study described in RD1 and A2.

Figure 1. Concise outline of an initial perspective on a project plan.

Figure 1 is a display of possible components of an initial planning perspective. The example is about ideas of devising counter-measures against collateral damage. The display shows that an analysis of possible enabling operations points to the fact that intelligence functions are important in connection with risks of collateral damage (i.e. reconnaissance, surveillance and target acquisition). A preliminary goal analysis suggests that the solution will require technical and tactical means. In addition, it should generally be realized in an interoperational context (i.e. coordinated with other forces and resources).

The task analysis and design will be structured and generate tactical requirements which should govern technical ones and also be coordinated with interoperational needs. Conceptual development (CD) and modeling will probably need techniques of simulation and gaming. Scenario construction can be a means for preparing the necessary case studies and experimentation.

In brief, the initial ’planning perspective’ is a holistic image of a complex task achievement for project management to be elaborated progressively

References

Taleb, N.N. (2010). The Black Swan. The Impact of the Highly Improbable. London: Penguin Books

References on this website arborg.se:

RD1. A case approach to study applied research methods

RD3. Comments on context of planning.

RD5. Remarks on planning design and dynamics of goal analysis.

RD6. On formal procedures to support inventive planning: Case examples.

RD10. Choice of perspectives on counteracting collateral damage:

A fictitious case of planning command and control systems.

RD11. Initial project planning: Theoretical considerations.

Applied Research Methods for Development Projects.