Optimal Decisions in Early Phases – Navigate Uncertainty With Robust Analysis
In the complex world of systems and supportability engineering, good decision support is everything. Decisions made in the early life cycle phases, regarding system design and support solution design, have immense input on the trajectory of a product and determine its performance, cost-effectiveness, and availability throughout the entire lifespan. At the same time, in these early phases, data is limited and immature, making it challenging to obtain precise estimates of key parameters like failure rate and item costs. This must be seen as a reason to skip proper analysis. With Opus Suite, the optimized outcomes and results are robust and far less sensitive to data quality issues as one might think.
Game-Changing Insights from Robust Optimization
Emphasis on Strategic Decision Support Rather Than Data Precision
Many are familiar with the phrase "garbage in - garbage out". While there is of course some truth in that axiom, it must not be seen as a reason to skip analysis altogether. At least not within systems life cycle management. When key decisions are based on gut feeling alone, detrimental consequences like performance issues, maintainability problems and large cost overruns are the rule rather than the exception.
As countless applications of Opus Suite have shown, and as explained in the video clip below, the results from Opus Suite optimization are very robust, and a lot less sensitive to data inaccuracy than one might expect. The strategic decision-making in the early phases really needs the best possible consequence analysis and predictions, but it does not need to be based on high-precision input data. The analytical methodology and proven algorithms in Opus Suite make it possible to gain invaluable insights into a system's performance, costs, and ability to meet its operational requirements, even when data is limited and immature.
Vital Early Insights With Imperfect Data
In the early phases, mature data is a rarity, and reliance on estimations becomes inevitable. To handle uncertainty and generate robust results even with limited data is a game-changer. Simulating and optimizing different scenarios and analyzing the impact of various parameters, facilitates a much better understanding of the trade-offs between capability, availability, costs, and agility. This empowers decision-makers to make informed choices without compromising quality or waiting for perfect data.
Navigating Uncertainty with Robust and Proven Modeling & Analysis Capabilities
Watch our video to discover Opus Suite's unique ability to handle uncertainty and generate robust results in the face of imprecise data. Employing analysis-driven LCM already in the early phases allows you to focus on aspects and parameters that has the biggest impact on cost effectiveness, and also to evaluate and minimize the impact of data uncertainty by through sensitivity analysis. The video below provides further insights into:
- The impact of early analysis: The insights far outweigh the drawbacks of inaccuracies in input data
- Focus on the strategic decisions: System design and support solution design
- Impact and robustness: Illustrating the resilience of results by varying key parameters
Empowering Strategic Choices without Waiting for Perfect Data
Opus Suite enables a mindset shift. Contact us to understand further how it will help you:
- Balance performance and costs
- Optimize system design and support solution design
- Assess performance, resource utilization and costs over time
- Minimize risks
Watch the Video
Watch the video now for a more in-depth explanation and examples that illustrate the robustness of Opus Suite optimization!