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Compute variances and indices. Cost Variance (CV) = EV − AC = 600 − 550 = +$50k (positive is good → under budget). Schedule Variance (SV) = EV − PV = 600 − 650 = −$50k (negative → behind schedule). Cost Performance Index (CPI) = EV/AC = 600/550 ≈ 1.09 (earning $1.09 per $1 spent), and Schedule Performance Index (SPI) = EV/PV = 600/650 ≈ 0.92 (progressing at ~92% of planned rate). Therefore the project is under budget but behind schedule—Option B. CAPM EVM objectives include interpreting these signals to drive action: analyze drivers of favorable cost (e.g., lower rates, deferred work) and unfavorable schedule (bottlenecks, underestimated tasks, dependency delays). Consider targeted interventions on the critical path (e.g., fast tracking, focused crashing with business cases) while protecting quality. Communicate impacts via forecasts (e.g., EAC using BAC/CPI if trends persist) and update the risk register with schedule-related threats (overtime fatigue, morale) and opportunities (process improvements). Transparent reporting enables informed decisions on trade-offs among scope, time, cost, and risk.

TCPI (to meet BAC) = (BAC − EV) ÷ (BAC − AC). Substituting: (1,000,000 − 400,000) ÷ (1,000,000 − 500,000) = 600,000 ÷ 500,000 = 1.20. A TCPI of 1.20 means the remaining work must be accomplished at 20% better cost efficiency than the project has achieved to date (CPI so far = EV/AC = 0.80). This is a challenging target and signals the need for strong corrective action: tighten change control, address drivers of inefficiency (rework, supplier performance, resource mix), and consider trade-offs in scope, quality, or schedule. If leadership instead approves a revised EAC, the alternative formula TCPI(EAC) = (BAC − EV) ÷ (EAC − AC) applies, which usually yields a lower (more achievable) index. CAPM EVM objectives require interpreting indices, selecting appropriate forecasts, and communicating implications transparently so stakeholders understand feasibility and risk of recovery plans before committing to them.

Risk avoidance changes the plan to eliminate the threat or protect the project from its impact. Replacing a risky custom algorithm with a certified module removes the hazardous activity, thereby avoiding the regulatory non-compliance risk altogether. Mitigation (Option A) would reduce probability or impact (e.g., more testing, fail-safes) but still proceed. Transfer (Option B) shifts financial consequences (e.g., insurance, fixed-price contracts) but does not remove the underlying technical risk. Acceptance (Option D) acknowledges the risk with minimal action beyond reserves or monitoring. CAPM risk management stresses selecting responses aligned with risk appetite, cost-benefit, and constraints. Avoidance often affects scope, cost, or schedule and thus requires integrated change control and stakeholder alignment. Even when avoiding, add secondary risks to the register (e.g., vendor lock-in, integration constraints, licensing limits) and define validation steps to confirm the new module meets performance and security NFRs. Clear traceability supports audits and formal acceptance, especially in regulated domains.

In procurement planning, risk allocation is a key consideration. Firm Fixed Price (FFP) contracts lock in a total price for a defined scope, placing most cost risk on the seller. If actual costs exceed expectations, the seller absorbs the overrun, creating strong incentives for efficiency and scope clarity. For the buyer, FFP offers high cost predictability and simpler administration once scope is baselined. CPFF (Option A) reimburses allowable costs plus a fixed fee; the buyer bears most cost risk and must exercise tighter oversight. T&M (Option B) blends fixed rates with variable quantities; risk is shared, and buyer exposure increases with poor control of hours or materials. CPIF (Option D) adds incentives to align performance, but the buyer still reimburses costs, keeping significant risk. CAPM objectives stress selecting contract types consistent with scope maturity, market conditions, and risk appetite. With FFP, invest in thorough requirements, a robust WBS, and clear acceptance criteria to avoid disputes, and pair with effective change control to manage any needed adjustments.

Backlog refinement (a.k.a. grooming) is a continuous, collaborative activity where the Product Owner and Developers discuss upcoming items, clarify acceptance criteria, split epics into smaller stories, assess dependencies, and estimate effort (often with relative sizing). It improves readiness for Sprint Planning and stabilizes forecasting by reducing uncertainty. It is not a formal Scrum event with a fixed timebox (Option A), though teams often allocate a reasonable portion of capacity (e.g., up to ~10%) to refinement. Option C reframes refinement as management approval, which conflicts with agile empowerment and value-driven ordering. Option D misassigns ownership; while the Product Owner is accountable for ordering and ensuring value, the Developers estimate and advise on feasibility and risks. CAPM’s agile content highlights that effective refinement increases flow predictability, reduces mid-sprint churn, and aligns stakeholders on “Definition of Ready” expectations. Good practices include using examples, DoR checklists, and slicing techniques (e.g., vertical thin slices) to ensure items are implementable within a sprint and meet the team’s Definition of Done when completed.