Anand Stephen

Currently, we are engulfed by data. Some humorously call it data obesity; others call it data deluge. Equally, technologies enabling the proliferation of data are changing at a dizzying rate. Given these mutually reinforcing phenomena moving exponentially, we as professionals should ask ourselves which best practices we should carry forward in this new digital age. What methods have stood the test of time that should be carried forward?   Compared to other industries, our industry has developed a robust Quality Management System (QMS). We begin by discussing the critical aspects of any QMS: Quality Control (QC) and Quality Assurance (QA). The contract documents we produce are legal documents backed by the sign and seal of the Professional Engineer in the United States (other equivalents globally).   The QMS provides processes for QC and types of artifacts required to ensure that the Quality Checks are completed. The artifacts serve many purposes. Primarily, they give confidence to various stakeholders that the project design was undertaken with due diligence. They provide audit trails to justify why certain decisions were taken. Finally, in unfortunate circumstances, when we are mandated to defend design decisions legally, the artifacts become critical documents.   We discuss scenarios in the Model-Centric world where no QA artifacts are produced even though Quality Control was completed. We discuss the implications of not making these assurance documents from the vantage point of an Engineer signing and sealing contract documents. Finally, we extend this notion when we take a computational design approach.