What is a good project manager? Reconceptualizing the “do” : an Aristotelian perspective

In Social Science (Organization Studies, Economics, Management Science, Strategy, International Relations, Political Science…) the quest for addressing the question “what is a good practitioner?” has been around for centuries, with the underlying assumptions that good practitioners should lead organizations to higher levels of performance. Hence to ask “what is a good “captain”?” is not a new question, we should add! (e.g. Tsoukas & Cummings, 1997, p. 670; Söderlund, 2004, p. 190). This interrogation leads to consider problems such as the relations between dichotomies Theory and Practice, rigor and relevance of research, ways of knowing and knowledge forms. On the one hand we face the “Enlightenment” assumptions underlying modern positivist Social science, grounded in “unity-of-science dream of transforming and reducing all kinds of knowledge to one basic form and level” and cause-effects relationships (Eikeland, 2012, p. 20), and on the other, the postmodern interpretivist proposal, and its “tendency to make all kinds of knowing equivalent” (Eikeland, 2012, p. 20). In the project management space, this aims at addressing one of the fundamental problems in the field: projects still do not deliver their expected benefits and promises and therefore the socio-economical good (Hodgson & Cicmil, 2007; Bredillet, 2010, Lalonde et al., 2012). The Cartesian tradition supporting projects research and practice for the last 60 years (Bredillet, 2010, p. 4) has led to the lack of relevance to practice of the current conceptual base of project management, despite the sum of research, development of standards, best & good practices and the related development of project management bodies of knowledge (Packendorff, 1995, p. 319-323; Cicmil & Hodgson, 2006, p. 2–6, Hodgson & Cicmil, 2007, p. 436–7; Winter et al., 2006, p. 638). Referring to both Hodgson (2002) and Giddens (1993), we could say that “those who expect a “social-scientific Newton” to revolutionize this young field “are not only waiting for a train that will not arrive, but are in the wrong station altogether” (Hodgson, 2002, p. 809; Giddens, 1993, p. 18). While, in the postmodern stream mainly rooted in the “practice turn” (e.g. Hällgren & Lindahl, 2012), the shift from methodological individualism to social viscosity and the advocated pluralism lead to reinforce the “functional stupidity” (Alvesson & Spicer, 2012, p. 1194) this postmodern stream aims at overcoming. We suggest here that addressing the question “what is a good PM?” requires a philosophy of practice perspective to complement the “usual” philosophy of science perspective. The questioning of the modern Cartesian tradition mirrors a similar one made within Social science (Say, 1964; Koontz, 1961, 1980; Menger, 1985; Warry, 1992; Rothbard, 1997a; Tsoukas & Cummings, 1997; Flyvbjerg, 2001; Boisot & McKelvey, 2010), calling for new thinking. In order to get outside the rationalist ‘box’, Toulmin (1990, p. 11), along with Tsoukas & Cummings (1997, p. 655), suggests a possible path, summarizing the thoughts of many authors: “It can cling to the discredited research program of the purely theoretical (i.e. “modern”) philosophy, which will end up by driving it out of business: it can look for new and less exclusively theoretical ways of working, and develop the methods needed for a more practical (“post-modern”) agenda; or it can return to its pre-17th century traditions, and try to recover the lost (“pre-modern”) topics that were side-tracked by Descartes, but can be usefully taken up for the future” (Toulmin, 1990, p. 11). Thus, paradoxically and interestingly, in their quest for the so-called post-modernism, many authors build on “pre-modern” philosophies such as the Aristotelian one (e.g. MacIntyre, 1985, 2007; Tsoukas & Cummings, 1997; Flyvbjerg, 2001; Blomquist et al., 2010; Lalonde et al., 2012). It is perhaps because the post-modern stream emphasizes a dialogic process restricted to reliance on voice and textual representation, it limits the meaning of communicative praxis, and weaking the practice because it turns away attention from more fundamental issues associated with problem-definition and knowledge-for-use in action (Tedlock, 1983, p. 332–4; Schrag, 1986, p. 30, 46–7; Warry, 1992, p. 157). Eikeland suggests that the Aristotelian “gnoseology allows for reconsidering and reintegrating ways of knowing: traditional, practical, tacit, emotional, experiential, intuitive, etc., marginalised and considered insufficient by modernist [and post-modernist] thinking” (Eikeland, 2012, p. 20—21). By contrast with the modernist one-dimensional thinking and relativist and pluralistic post-modernism, we suggest, in a turn to an Aristotelian pre-modern lens, to re-conceptualise (“re” involving here a “re”-turn to pre-modern thinking) the “do” and to shift the perspective from what a good PM is (philosophy of science lens) to what a good PM does (philosophy of practice lens) (Aristotle, 1926a). As Tsoukas & Cummings put it: “In the Aristotelian tradition to call something good is to make a factual statement. To ask, for example, ’what is a good captain’?’ is not to come up with a list of attributes that good captains share (as modem contingency theorists would have it), but to point out the things that those who are recognized as good captains do.” (Tsoukas & Cummings, 1997, p. 670) Thus, this conversation offers a dialogue and deliberation about a central question: What does a good project manager do? The conversation is organized around a critic of the underlying assumptions supporting the modern, post-modern and pre-modern relations to ways of knowing, forms of knowledge and “practice”.

Prolegomenon to the study of the concepts of maturity and maturity model : from Black Horse to White Knight?

This paper takes its root in a trivial observation: management approaches are unable to provide relevant guidelines to cope with uncertainty, and trust of our modern worlds. Thus, managers are looking for reducing uncertainty through information’s supported decision-making, sustained by ex-ante rationalization. They strive to achieve best possible solution, stability, predictability, and control of “future”. Hence, they turn to a plethora of “prescriptive panaceas”, and “management fads” to bring simple solutions through best practices. However, these solutions are ineffective. They address only one part of a system (e.g. an organization) instead of the whole. They miss the interactions and interdependencies with other parts leading to “suboptimization”. Further classical cause-effects investigations and researches are not very helpful to this regard. Where do we go from there? In this conversation, we want to challenge the assumptions supporting the traditional management approaches and shed some lights on the problem of management discourse fad using the concept of maturity and maturity models in the context of temporary organizations as support for reflexion. Global economy is characterized by use and development of standards and compliance to standards as a practice is said to enable better decision-making by managers in uncertainty, control complexity, and higher performance. Amongst the plethora of standards, organizational maturity and maturity models hold a specific place due to general belief in organizational performance as dependent variable of (business) processes continuous improvement, grounded on a kind of evolutionary metaphor. Our intention is neither to offer a new “evidence based management fad” for practitioners, nor to suggest research gap to scholars. Rather, we want to open an assumption-challenging conversation with regards to main stream approaches (neo-classical economics and organization theory), turning “our eyes away from the blinding light of eternal certitude towards the refracted world of turbid finitude” (Long, 2002, p. 44) generating what Bernstein has named “Cartesian Anxiety” (Bernstein, 1983, p. 18), and revisit the conceptualization of maturity and maturity models. We rely on conventions theory and a systemic-discursive perspective. These two lenses have both information & communication and self-producing systems as common threads. Furthermore the narrative approach is well suited to explore complex way of thinking about organizational phenomena as complex systems. This approach is relevant with our object of curiosity, i.e. the concept of maturity and maturity models, as maturity models (as standards) are discourses and systems of regulations. The main contribution of this conversation is that we suggest moving from a neo-classical “theory of the game” aiming at making the complex world simpler in playing the game, to a “theory of the rules of the game”, aiming at influencing and challenging the rules of the game constitutive of maturity models – conventions, governing systems – making compatible individual calculation and social context, and possible the coordination of relationships and cooperation between agents with or potentially divergent interests and values. A second contribution is the reconceptualization of maturity as structural coupling between conventions, rather than as an independent variable leading to organizational performance.

The Scent of Ancestral Memory

Poetry expresses the physical and spiritual worlds that other kinds of writing cannot. Travelling open our minds and frees our spirit. Creative writings and meditations on life, spirit, grace and relationships, art and nature weave their way through these lyrical poems. Some poems are suitable for study in the Australian Curriculum.

Improving robot vision models for object detection through interaction

We propose a method for learning specific object representations that can be applied (and reused) in visual detection and identification tasks. A machine learning technique called Cartesian Genetic Programming (CGP) is used to create these models based on a series of images. Our research investigates how manipulation actions might allow for the development of better visual models and therefore better robot vision. This paper describes how visual object representations can be learned and improved by performing object manipulation actions, such as, poke, push and pick-up with a humanoid robot. The improvement can be measured and allows for the robot to select and perform the `right' action, i.e. the action with the best possible improvement of the detector.

From vision to actions: Towards adaptive and autonomous humanoid robots

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.