Continuous and Centralized Overview for SE Effectiveness Monitoring
Squore tailored solution for Systems Engineering performance is based on international concepts and standards:
SEI : CMMI Capability Maturity Model Integration
ISO/IEC 15939 Software Engineering
ISO/IEC 15288 Software and Systems Engineering
SE Leading Indicators Guide V2 issued by the INCOSE
Data import capabilities from third party tools already in use for requirement management, configuration and change management, modeling, coding, test management
Evaluation model and Monitoring dashboard implementing INCOSE SE leading indicators
Easy comparison of project progress and performance of project portfolios, on a regular basis or at key milestones
Automated generation of remediation and action plans aligned with predefined rules et triggers
Capitalization of project data for accurate predictive trend analysis
Optimization of the “Time-Cost-Quality” trade-off
SE Management Process Needs Measurement Information for Objective and Impartial Decision Making
In the last few years, Systems Engineering (SE) has become a leading discipline for all major industrial companies delivering complex critical systems.
Despite this, programs and project failures remain too frequent due to increasing complexity, stakeholder diversity, engineering tool silos and heterogeneity...all leading to communication breakdown.
As stated by the INCOSE (International Council on Systems Engineering), the SE Management Process should rely on measurement information both for objective and impartial decision making and for accurate prediction on expected project performance and potential future states.
INCOSE further recommends an exhaustive and regular collection of data involved in the production of the SELI (Systems Engineering Leading Indicators), on a minimal monthly basis (or more during critical phases): implementing an automated and centralized solution is thus essential.
Squore Provides Continuous and Centralized Overview to Optimize Trade off Between Cost, Time and Quality
Squore can be adapted in a specific configuration for the monitoring of Systems Engineering effectiveness. This tailored Squore model helps action making by providing the details and trend of indicators related to the 3 major axes of project performance monitoring:
Meeting of delivery deadlines
Adherence to Budgets constraints
Quality of the achieved system
Squore for Systems Engineering implements INCOSE SE leading indicators
A SE leading indicator is a measure allowing to evaluate how the effectiveness of a project activity is likely to affect system performance objectives (in reference to “Systems Engineering Measurement Primer” published by the INCOSE in 2010).
A leading indicator may be an isolated measure, or a set of measures, which will be used for predictive correlations and for establishing trends.
For example, if requirements validation rate equals 20% a few days before functional requirements review, while their volatility exceeds 50%, this review shall be immediately postponed in order to avoid either process repetition (impacting on-time delivery) or team expansion to comply with time schedule (impacting cost).
Out of the Box Standardized Control Points and KPIs Based on Incose SELI Specifications
For each System in the portfolio, the Squore dashboard provides continuous update of measurements and KPIs, and the follow up of SE indicators all along the life cycle. This can be done periodically or at key milestones.
Requirements KPI and process adherence
Unique Double Drill-Down Combined with Powerful Filtering
This advanced navigation features allow:
To focus on the performance of an agregat or item within a hierarchy of artifacts produced by IS processes (requirements, tests, CR/PR, models, applications, documentation, review, cost…). Nonconformities and regressions are immediately detected (ambiguous requirement, non standard architecture diagram, pending change requirement, budget overruns,…).
OR to focus on a specific indicator (or a combination of indicators) to understand and evaluate “how a specific project activity is likely to affect system performance objective”. For example, how Requirements volatility may affect functional suitability.
Unrivaled in-depth analysis: risky work products are immediately identified, down to the most
elementary configuration items