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This requires thinking in engineering terms such as: Design Thinking, Systems Engineering, Model Based

During that time we learned all about business modeling, re-engineering, and the like.

The tension between value production and compliance is a false dichotomy based on an old-factory model

Process Model (simplified): A process is a set of ordered steps that takes input and transforms it to Systems Model (simplified): A process becomes a system when it is connected with other elements particularly Program Model (simplified): A program defines the outcomes that the systems and processes are to achieve From this model, we can see where changes are triggered and how they interact at both the program and Where to Improve Compliance The models presented so far help clarify important differences between programs

Performance models (and this includes compliance) based on the reactive audit-fix cycle have not been

support: risk based methods, evidence based processes, along with advancing program maturity through a model

Modeling, simulation, and experimentation are essential to developing options.

apply to evaluate the risks associated with their AI systems, including aspects such as data quality, model

Unfortunately, many of these same companies use a reactive compliance model that was developed only to

on an appropriate MCDA method such as: analytic hierarchical process (AHP), multi-attribute additive model

We have designed each module in bite sized portions. The first module starts April 5th so register today. SYSTEMS MODULE - "Keep it Green" In this module you will learn tools & techniques to always stay in compliance LEAN MODULE - "Keep it Lean" In this module you will learn how to apply Lean tools & techniques to continuously RISK MODULE - "Keep it Certain" In this module you will learn how to improve the probability of keeping

obligations were identified and managed the level of certainty that internal obligations would be met was MODERATE