Requirements Definition
Specific services include:
- Requirements and design sessions involving all affected stakeholders
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Facilitated requirements sessions involving as many as 250 people for 3-5 days
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JAD-like and conference-like sessions maximizing results for everyone involved
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Exception-oriented facilitation process leading quickly to profound knowledge
- Quality-based requirements for project teams
Requirements Engineering Education
The major intersection of quality and software occurs during requirements activities. This series of courses covers the elicitation and modeling of business, data, and process requirements with an emphasis on translating those requirements forward toward implementation. Note: This course series concentrates heavily on the front-end of the software lifecycle. Emphasis is placed on business and functional specification, architectural design, and testing strategies and plans. Technical aspects and nuances of building and integrating technology components is beyond the scope of this series.
Quality-Based Requirements Analysis
Analysis improves the definition of requirements for information systems by better understanding the three types of requirements, how they conflict and interact, and how best to capture and record requirements results to minimize omissions and errors. (3 days)
Quality-Based Data Modeling
Data modeling improves the identification and analysis of data requirements at the enterprise, project, and data base levels. Through a synthesis of basic quality management principles, data model rigor is increased, resulting in the absence of data omissions and defects often encountered with traditional data analysis techniques. (3 days)
Quality-Based Process Modeling
Process modeling improves the thoroughness of business process definitions through a rigorous adaptation of concepts inherited from basic quality management practices. Using principles of customer-supplier and requirement-conformance feedback loops, process models create business definitions that can be easily verified and that reveal scope issues that normally create project problems during the implementation phase. (3 days)
Quality-Based Model Integration
Integration improves the verification process of assuring that all analysis models can be properly integrated into a single whole. Even a small project is likely to develop dozens, if not hundreds, of analysis process and data models in support of its requirements. Even if every model is correct, there still is no assurance that all of the models will fit together properly. Proper integration requires active steps on the part of the analyst to assure project success. (2 days)
Quality-Based Design Transition
Transition improves the activities required to move analysis deliverables on to system design. Many organizations that invest heavily in analysis modeling still lose much of that investment by setting aside the models at the beginning of design to revert to traditional design techniques. Through proper transition techniques, system and data architectures can be derived from the analysis models, maximizing the return on investment in modeling. (2 days)
DOQS Heuristic Patterns
Heuristics for improving data and process modeling
efficiency and effectiveness.
Experienced information technology practitioners have learned over time that there are only a limited number of general problems and situations that actualy cover a majority of situations encountered on informaton technology initiatives. Our research attenpts to isolate these situations and package the results in management and analysis patterns that can be shared and incorporated into client processes and practices.
Current patterns include:
