Sourced artificial intelligence and software context
Models, products, and production services: SAP HCM
The City of San Jose identifies artificial intelligence as a priority growth sector and includes AI training and job-matching programs in its fiscal year 2025 to 2026 economic plan. Translate the workforce setting into personnel structures, actions, infotypes, organization objects, time rules, payroll schemas, and approvals. Require a comparable design explanation. AI product work can join source data, models, application code, evaluation, user feedback, cost controls, access rules, and production support under separate owners.
Evidence to request: Use a hire-to-pay exercise and require personnel, organization, time, payroll, security, and posting decisions. Define the user decision, model boundary, source data, evaluation set, deployment path, access control, cost target, failure response, and approving product owner.
Sourced semiconductors and advanced manufacturing context
Engineering, fabrication, and supply controls: SAP HCM
A July 2025 City of San Jose economic-development release names advanced manufacturing and semiconductors among the industries the city plans to attract, retain, and grow. Set boundaries among SAP HCM, SuccessFactors, identity, time collection, benefits, payroll providers, finance, and reporting. Ask how the team detects, corrects, and reconciles errors. Semiconductor and manufacturing programs may connect product definitions, equipment, process recipes, production schedules, quality results, suppliers, inventory, maintenance, and cost records.
Evidence to request: Review an interface or payroll defect with the affected population, root cause, correction, rerun, reconciliation, and communication. Set the design or plant boundary, product revision, process control, equipment interface, traceability unit, quality release, supplier handoff, change window, and support owner.
Sourced data centers and energy infrastructure context
Capacity, continuity, and facility operations: SAP HCM
San Jose's July 2026 large energy-use project page distinguishes data centers from research laboratories, advanced manufacturing sites, electric-vehicle charging hubs, and other power-intensive facilities. Define testing, cutover, and support ownership. Candidates should cover employee conversion, retroactive changes, time and payroll cycles, roles, transports, exceptions, and sign-off. These facilities can combine power, cooling, networks, physical security, capacity, asset maintenance, environmental controls, backup systems, and tenant or workload commitments.
Evidence to request: Ask for a conversion or release cycle the consultant owned, including data validation, transports, parallel testing, exceptions, and acceptance. Name the facility and workload boundary, capacity unit, power and cooling dependencies, availability target, access model, maintenance path, recovery test, and change authority.