A Framework of Human Systems Engineering

This methodology is designed to identify areas of risk to successful project execution. Risk is defined here as the belief that the project will be challenged or fail given the alignment coefficient and the IE. Figure 3.2illustrates the possible outcomes of the IE.

For this discussion, stability S is defined as follows:

(3.4)

S is used with the alignment coefficient to calculate confidence. If the project has a high alignment coefficient score across the relationships and S is large, it can be plotted in Zone 1, and there is good confidence that the project will succeed. A project that has high alignment coefficient, but low S (Zone 2), is a project of concern with low confidence of success and an analysis warranted to identify why the stability of the environment of the project is low, potentially indicating hidden factors. Zone 4 indicates a project that has both a low alignment coefficient score and low S , which would indicate there should be serious lack of confidence that the project will succeed. Zone 3 has high S but low alignment coefficient; this is an area of concern that may be recoverable, and deeper analysis is warranted to understand why the alignment coefficient scores are low. Figure 3.9plots belief alignment against environment stability; for the purposes of this figure, confidence is defined as

(3.5)

Figure 3.9 Confidence vs. stability.

For both projects, a retrospective study was employed in which the concept of digital twins was used to construct the model using the concepts described above. Six events were identified in which information from sensors was collected and reviewed. Figure 3.10shows the project events used for the model. Different, yet equivalent, events were used because Project One followed a traditional SE and project management approach and Project Two employed SAFe, agile, and scrum methodologies to manage the project.

Figure 3.10 Case study project events.

The case study comparison of Project One and Project Two demonstrates the effects of employing sociotechnical constructs, AI, and HSE into the development environment. Comparatively, the results from the model are plotted showing belief alignment and stability (see Figure 3.11). As noted, belief alignment is generated by calculating the geomean of belief coefficients derived from a series of questions, noted previously. Stability is calculated using 1 minus IE ( S = 1 − IE). Four zones were defined to aid in analysis:

Zone 1 (belief > 0.6; stability > 0.6): Projects scoring in Zone 1 generally have a high probability of success.

Zone 2 (belief > 0.6; stability < 0.6): Projects scoring in Zone 2 demonstrate a high level of confidence in the alignment and cohesiveness of the stakeholders but present challenges in that the environment itself and/or the belief alignment is unstable due to exogenous influences.

Zone 3 (belief < 0.6; stability > 0.6): Projects scoring in Zone 3 demonstrate a low level of confidence in the alignment and cohesiveness of the stakeholders, while the environment itself and/or the belief alignment is relatively stable with minimal expected change or exogenous influences. Note that this stable structure does not mean it is good – only that it is deterministic.

Zone 4 (belief < 0.6; stability < 0.6): Projects scoring in Zone 4 exhibit one or more behaviors and associated risks that are commonly identified root causes of failed projects.

Figure 3.11 Belief alignment and stability results for case study.

Analysis was performed using the conceptual architecture for Epoch 4 as a means of comparing and determining value of evolving SE toward Epoch 4 (see Table 3.1).

Table 3.1 Case study comparative analysis.

Overall, for Project One, eroding belief alignment was evident over the life of the program as the stakeholders did not learn from previous activities and outcomes and instead hardened their own beliefs. Once these patterns were set, the culture of the project made it hard to change the patterns of behavior and project structure. As can be seen, the project had a consistent trajectory leading from initial confidence to the reality of a poorly run project. Conversely, the culture of Project Two employed open communications across all stakeholders and maintained the idea of being a learning organization that actively sought to improve throughout the project life cycle. Continuous alignment and high stability in the project are evidenced by the low variation in measurements for Project Two over time.

While this is an initial study, indications are that the constructs of Epoch 4 will improve success in quality project deployment. As more projects follow these constructs, it is hoped that future studies will prove the value of employing HSE and AI into the development environment.