Unknown Unknowns in Innovative Projects: Early Signs Sensemaking.
| Autor | Russo, Rosaria de Fatima Segger Macri |
| Cargo | Report |
Introduction
Business management, as it is known, must undergo deep and dramatic changes: first, to increase performance in answering market demands; and second to achieve new ways of working, such as through how collaboration and creativity (Hamel, 2007) has been stimulated by the Internet, and counting on the values and attitudes of the new workforce. This high level of novelty brings unpredictable uncertainty to innovative projects (Loch, DeMeyer, & Pich, 2006; Loch, Solt, & Bailey, 2008). As the uncertainty in a project increases, the project team tends to diminish knowledge exchange and combination (Mehta, Hall, & Byrd, 2014). Dealing with this kind of uncertainty is a challenge to Project Management [PM] (Ramasesh & Browning, 2014).
Unpredictable uncertainty is also called unknown unknowns [unk unks] (Wideman, 1992), because there is a complete unawareness of what will occur in the future. De Meyer, Loch and Pich (2002) divided this uncertainty into two other kinds: (a) unforeseen uncertainty, when the event is unlikely to occur or when there is unawareness about its existence, and (b) chaos, when the project starts without stable goals and assumptions. However, Snowden and Boone (2007) and Thamhain (2013) affirm that chaos does not have clear cause-and-effect relationships. Unforeseen uncertainty, in turn, is complex (Snowden & Boone, 2007) and requires emergent actions when it occurs. It was called an accident by Thamhain, (2013, p. 23), because it "can be identified in principle, but the occurrence probability and its specific scope and impact on project performance are difficult, if not impossible, to predict". In this article, we will be use unk unks when referring to this type of uncertainty.
One way to identify unk unks is through the perception of an early sign. The real world is flooded with information, which is often ambiguous, inaccurate and incomplete; much information may be early signs of current cycle interruption, a break, which may be beneficial or harmful for business (Ansoff, 1975). Identification of an early sign can greatly contribute to making better decisions in the early stages of a project (Haji-Kazemi, Andersen, & Krane, 2013). Usually, however, project managers do not act upon them (Williams, Klakegg, Walker, Andersen, & Magnussen, 2012). In order to recognize such a sign, besides realizing that something has changed, its meaning must be understood. Sensemaking is the ideal tool for understanding meaning (Weick, 1995).
These distinct subjects (early signs, sensemaking, and uncertainty) have previously been studied in PM. Several studies (Haji-Kazemi, Andersen, & Klakegg, 2015; Kuosa, 2010; Williams et al., 2012) have assessed early signs management in projects. Stigliani and Ravasi (2012) studied cognitive processes in collective sensemaking in design projects, as Fellows and Liu (2016) assessed cultural influence in sensemaking in projects and innovations. Ramasesh and Browning (2014) have proposed a framework to transform unk unks into knowable events in PM, which include, among many factors, early signs sensemaking. However, none of them focused on understanding how a project manager and team members act to create sensemaking of the early signs of unk unks in innovative projects.
Therefore, this study aims to understand the relevance of perception and making sense of early signs for identifying unk unks in innovative projects prior to change. As a secondary goal, we sought to: (a) identify and understand the causes of unk unks; (b) understand the motivating factors for identifying unk unks, recognized as types of previous management and early sign perception; (c) assess efficiency in identifying unk unks; and (d) assess the relationship between the efficiency in identifying unk unks and the causes and motivating factors.
Next, the article summarizes the theoretical foundation on the subject, highlighting the themes of uncertainty and risks, early signs in projects and sensemaking. Then there is a detailed description of the methodological procedures used in the data collection, and qualitative and quantitative analysis. Finally, we present the results and offer discussion. The authors' expectation is to make a practical contribution by recommending some approaches to PM, processes and the behavior of team members to help make sense of early signs and decrease uncertainty in innovative projects.
Theoretical Background
Uncertainty and risk in projects
Several authors affirm that Risk Management [RM], which is responsible for managing uncertainty in PM, does not deal with high levels of uncertainty (Loch et al., 2006; Murray-Webster & Pellegrinelli, 2010; Pender, 2001; Perminova & Wikstro, 2008). RM requires clear identification of event likelihood, both for risk and for opportunity, and of the level of their consequences in the project plan. The absence of adequate information makes it impossible to generate the planning, execution and appropriate monitoring of projects (Pich, Loch, & Meyer, 2002).
Despite this, unk unks are precisely the lack of knowledge of future events, which make them unpredictable. Thus, RM "will neither cope with the unknown unknowns, nor with extreme complexity or ambiguity" (Murray-Webster & Pellegrinelli, 2010, p. 12). Lehtiranta (2014) suggests more research about unk unks, which she called unanticipated and unrealistic assumptions, aiming at helping build a holistic approach to RM. Regarding the treatment of this type of uncertainty, only PRINCE2 (Office of Government Commerce [OGC], 2009) cites the monitoring of early signs, calling them signals and early warnings. ISO 31000 (Purdy, 2009) highlights the perception of and response to changes, which may occur slowly or suddenly.
Early signs in PM
The studies about early signs in PM were related to project success (Kappelman, Mckeeman, & Zhang, 2006; Sanchez & Perez, 2004), with issues (Nikander & Eloranta, 1997); with risks (Nikander & Eloranta, 2001); with causes (Nikander, 2002); with frameworks for environmental scanning (Kuosa, 2010); with barriers for detecting them (Williams et al., 2012); and with barriers against effective responses to them (Haji-Kazemi et al., 2015).
The taxonomy used by the authors is varied: preliminary signal (Nikander & Eloranta, 1997, 2001; Project Management Institute [PMI], 2013); early warning signs (Kappelman et al., 2006; Sanchez & Perez, 2004; Williams et al., 2012); warning signs (OGC, 2009); future signs (Hiltunen, 2008). For this study, we adopted the early sign taxonomy. Its nature is characterized as anticipatory, qualitative, ambiguous, fragmented; it may have various formats and may come from several different sources (Blanco, Caron-Fasan, & Lesca, 2003). In this regard, we identified several groups of early signs (Nikander & Eloranta, 1997; Sanchez & Perez, 2004): gut feelings, communication among areas, expression from the various stakeholders, project control and reports, documents, and external sources.
Early signs can be classified into early information and early symptoms (Hiltunen, 2008). Early information consists of a small number of signs with low visibility, making it difficult to interpret, as in the case of gut feelings. Although the first symptoms present a great number of signs, interpretation can also be hindered by the lack of clarity in meaning, such as in the case of a person's behavior change. Williams, Klakegg, Walker, Andersen and Magnussen (2012) found that assessment tools (project review, health assessment, benchmarking, post-project assessment and audit) "are limited in their ability to pick up early warning signs" (p. 47). These authors considered gut feelings to be any perceived sign that was not formalized in an indicator, without a specific focus or issue in mind. Schoemaker and Day (2009) affirm that problems of excessive information, organization filters, and selective perception and people's cognitive biases prevent managers from creating meaning from these signs. That is, even when the sign is perceived, it may not be interpreted correctly.
Kappelman, Mckeeman and Zhang (2006) claim that the signs can come from three sources, dealing with Information Technology projects: product, process and people; the latter two sources are the most prevalent. Corroborating this view, Nikander and Eloranta (2001) concluded that most of the signs are linked to human factors, and are likely to occur at any time in the project. They also noted that the most important characteristics of those who identify the early signs are experience and insight, and that the traditional methods of PM monitoring and control should be used. The person who identifies the sign is not always the decision maker, who may even be outside the project team. However, "we are not very good at picking up early warning signs" (Williams et al., 2012, p. 37). Even, when we can perceive them, we need to make sense of their meaning to the project objectives and requisites.
Sensemaking
Weick (1995) created the concept of sensemaking, involving a broad and consistent approach to information interpretation. In addition to the construction of meaning about something, sensemaking would include notions such as structuring the unknown, placement of stimuli to create models, thought processes using retrospective data to explain surprises, placement of significance from authorship on ideas, individual and collective understanding of situations, development of cognitive maps of the environment, and creation of filters and ways for interpretation.
Sensemaking activities are very close to the concept of organizing, because people organize information and ideas to make sense out of them (Weick, Sutcliffe, & Obstfeld, 2005). The probable flow for sensemaking can be (Weick, 1995, p. 18): "people concerned with identity in the social context of other players engage themselves in ongoing events from which they extract cues and make plausible sense retrospectively while...
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