The management of complex technical problems requires:
1. Design Structure Matrix (DSM)
2. Managing Iterations (including overlapping tasks)
3. Managing system integration (CPM, PERT)
On that note consider:
DSM is a general method of representing and analyzing system models in a variety of application areas. The DSM matrix should include no more than 50-100 tasks. If DSM has about 1000 tasks, then it’s considered too detailed.
The management of iterations includes the planned iterations (launch gate review, spec gate review, critical design review) and the unplanned iterations (misinterpretations of contract clauses, failed commitments, approved design without meeting contract requirements).
CPM is a step-by-step project management technique for process planning that defines critical and non-critical tasks with the goal of preventing time-frame processes and process bottlenecks.
PERT is the technique of planning and controlling time by project management to analyze and represent the tasks involved in completing a given project.
Today, Project Managers are often responsible for gathering teams of people to accomplish tasks and lead them. And they are responsible for the migration process from one platform to another. While Engineering managers hold responsibility for managing a group of engineers who work solely for them.
The existence of many managers in a project results in extra interactions and enhanced iterations concerning the decomposition of the functions and the tasks of a system. I believe that only the engineering manager is furthermore aware of his organization’s architecture as well as the sequencing of technical tasks. Because the engineering manager knows which technical tasks are sequential, which parallel, and which coupled. Additionally, the engineering manager is more aware of the manipulation of the various interactions about the flow of engineering information and communication. Additionally, the engineering manager is aware of the relaxing constraints of the system architecture and his organization as well as where the design and build process is slow and where can be accelerated.
The 5 dysfunctions of an engineering team are caused because of the: (1) absence of trust (is the hardest dysfunction); (2) fear of conflict; (3) lack of commitment; (4) avoidance of accountability; (5) lack of attention to results.
A mechanism to control the time of an engineering project is the Critical Chain Method which supports the modifications of project schedules accounting for limited resources and uncertainties. A DSM can be transformed into a Critical Chain Method. Further, engineering managers must always be ready to handle efficiently the contingency time for potential unscheduled personal and technical disruptions. Experience has shown that contingency time is often wasted because of procrastination, queuing with multitasking, and delays are passed along without any gains.
To shorten the critical path of a project is necessary to: (1) Shorten the task duration or work on a task on the critical path, (2) Change the task constraint to allow for more scheduling flexibility, (3) Revise task dependencies to enable more scheduling flexibility; (4) Break a critical task into smaller tasks that can be worked on the same time by different resources.
Additionally, in this brief proposing model consider the following two tools: DevOps and Spiral development process. The concept of DevOps is founded on building a culture of collaboration between teams that hierarchically function in siloes. The spiral development process is a system development lifecycle (Identify, Design, Construct, Evaluate) method used for risk management that combines the iterative development process model with elements of the waterfall model. The spiral model is also used by S/W engineers and is favored for large expensive and complicated projects.
Every engineering manager and engineer must consider the following 5 ways to leverage existing technology in innovative ways. (1) Exploratory Analysis (need to go back and look at certain data from fairly large populations and discover which of these parameters or variables are related, and which other ones are correlated. Are they causal? Do they have a direct effect? Did they just happen?); (2) Predictive Analysis (need to manage the improvement process of predicting system performance under system changes. Predictive analytics include Informatics, Big Data Analytics, interfaces, Visual Analytics, Modeling & Simulation, and Statistical Engineering); (3) Natural Interfaces (find better interfaces so people and computers can communicate and do better jobs. Natural Interfaces require Natural Language Processing, Machine Learning, Text Mining, Video, Visual Analytics, and Animation); (4) Knowledge Management Tools (requires Intellectual Capital such as best practices and quality function deployment, Computer-based training, Real-Time Alerts, and Knowledge Bases); (5) Real-Time Analytics (monitor Real-Time data flow and tell the engineering managers when a project phase or process changes significantly).
Finally, engineers who need to undertake strategic decisions regarding a design and build project can utilize the following models. The Eisenhower Model; The SWOT Analysis; The Consequences Model; The Conflict Resolution Model; The Flow Model; The Subtle Signals Model; Thinking Outside the Box; The Pareto Principle; The Black Box Model; The Drexler Sibbet Team Performance Model; The Hersey-Blanchard Model.