What a PHCM implementation conversation should cover

QUESTION 01

Who should attend, and what should we bring?

Include affected process owners: HR, payroll, operations, benefits, IT/security, and an empowered sponsor. Not everyone needs every meeting, but each workstream needs a decision maker. Bring a high-level workforce profile, current-system list, major pain points, and fictional examples of difficult cases.

Put the answer into practice

• Summarize employee groups, locations, pay frequencies, policy complexity, and intended modules.
• Identify contracts, renewals, internal staffing limits, and business blackout periods.
• Describe goals without emailing live employee files or posting them in a public form.

QUESTION 02

What is a useful first-meeting agenda?

Use a focused discussion instead of a tour of every feature. A suggested 45-minute agenda is 10 minutes on outcomes and workforce, 10 on scope and systems, 10 on data and handoffs, 10 on testing and responsibilities, and 5 on next steps. This is a planning example, not a fixed PHCM service package.

Put the answer into practice

• Confirm the problem in the buyer’s language and the baseline for improvement.
• Separate must-have workflows from future priorities.
• End with an agreed next deliverable and owner—not an unsupported implementation date.

QUESTION 03

How should we decide the first release?

Start with a coherent business process and its essential dependencies. A small release is not automatically low-risk if payroll or benefits handoffs remain undefined. Identify populations, modules, policies, environments, interfaces, reports, and support responsibilities. Record exclusions as clearly as inclusions.

Put the answer into practice

• Label requirements demonstrated, configurable, third-party-dependent, unverified, or out of scope.
• Confirm availability, configuration, licensing, and connected services for the proposed deployment.
• Define change-control ownership and how changes affect cost, testing, and timing.

QUESTION 04

Who owns data migration and integrations?

Assign ownership by task, not the vague label “the project team.” Name who extracts, cleans, maps, loads, validates, and accepts each dataset. Identify both sending and receiving interface owners. PHCM, the customer, and third parties should have explicit responsibilities in the agreed plan.

Put the answer into practice

• Define authoritative sources, identifiers, effective dates, retained history, and access.
• Plan trial conversions and compare counts, balances, totals, and representative records.
• Specify transfer security, alerts, correction/replay rules, and reconciliation responsibilities.

QUESTION 05

What should decide whether we are ready to go live?

Use evidence-based gates: accepted data, representative testing, resolved critical defects, role-based training, support readiness, and an approved cutover plan. Payroll and benefits need particular care around differences and effective dates. The number of test cycles should follow scope and risk; there is no universal safe count.

Put the answer into practice

• Test normal work, exceptions, late corrections, unauthorized access, interface failures, and recovery.
• Have business owners reconcile results and explain differences before sign-off.
• Name the go/no-go owner, contingency triggers, communications, and post-launch support.

QUESTION 06

What can we responsibly say about cost, timing, and success?

A credible estimate follows scope, data readiness, interfaces, resource availability, and testing needs. Separate subscription and third-party charges from implementation and internal effort. Define measurable operating outcomes and who reviews them after rollout. An industry average cannot substitute for a scoped PHCM proposal.

Put the answer into practice

• Request written assumptions, dependencies, exclusions, and commercial approval before treating an estimate as a commitment.
• Measure unresolved exceptions, reconciliation effort, task completion, and support volume.
• For proposed AI or automation, document the task, approval boundary, data use, and evaluation method.

NIST provides a voluntary framework for managing AI risks. Our buying recommendation is to connect an AI claim to a defined use case, accountable reviewer, and measurable test. NIST AI Risk Management Framework