Which method BEST enables an enterprise to estimate the benefits of a new Software as...

Benefits realization in EGIT depends on identifying and quantifying expected value in a way that is practical given uncertainty and limited history, especially for new digital capabilities like a SaaS application. In many SaaS cases, direct benefit data (e.g., productivity gains, cycle-time reduction, improved conversion, reduced error rates) is uncertain at the outset, and the most workable way to estimate benefits is through heuristic methods—structured expert judgment, analogous estimates from comparable initiatives, stakeholder workshops, and agreed assumptions that can later be validated and refined. ISACA’s benefits management guidance highlights benefits as measurable advantages owned by stakeholders and stresses embedding benefits thinking into business-as-usual decision-making—this commonly relies on practical estimation techniques early in the lifecycle.

By contrast, TCO (C) is primarily a cost estimation method (useful for value discussions, but it does not estimate benefits). Expected monetary value (A) and Monte Carlo (B) are quantitative risk/uncertainty techniques and can help model variability once you already have probability distributions and data; they are typically less feasible as the best general approach for initial benefits estimation of a new SaaS without mature inputs. Heuristic methods best enable an enterprise to form an actionable, governance-ready benefits estimate that can be monitored and adjusted as real results emerge.