Description

This curriculum spans the full lifecycle of a large-scale process transformation, equivalent to a multi-phase advisory engagement, covering strategic scoping, stakeholder negotiation, detailed process redesign, governance setup, and post-implementation management across complex, cross-functional workflows.

Module 1: Defining Strategic Objectives and Scope Boundaries

Select whether to align transformation goals with shareholder value targets or operational KPIs when conflicting priorities emerge during board review.
Decide which business units to include in the initial transformation wave based on change readiness assessments and interdependencies.
Determine the threshold for scope inclusion—whether to address legacy system constraints now or defer to a follow-on initiative.
Resolve disagreements between regional leaders on whether transformation outcomes should be standardized globally or adapted locally.
Establish criteria for excluding high-impact but politically sensitive processes from the initial rollout.
Document and socialize the decision to prioritize speed-to-value over comprehensive redesign in the first phase.
Validate that the defined objectives can be measured using existing enterprise data sources without new instrumentation.

Module 2: Stakeholder Alignment and Coalition Building

Identify which functional leaders must be secured as sponsors before launching pilot activities to ensure downstream adoption.
Negotiate shared accountability between IT and operations for process redesign outcomes when ownership is ambiguous.
Decide whether to include union representatives in design workshops for labor-impacted workflows.
Address resistance from middle management by co-developing role transition plans prior to reorganization announcements.
Balance input from external consultants with internal subject matter expertise to maintain organizational credibility.
Manage conflicting expectations between legal, compliance, and business teams on data handling in redesigned processes.
Establish escalation protocols for unresolved stakeholder disputes that threaten timeline adherence.

Module 3: Process Discovery and Baseline Documentation

Select between automated process mining tools and manual workflow interviews based on system log availability and data quality.
Decide whether to map "as-is" processes at the task level or aggregate to major decision points based on transformation depth.
Determine which exceptions and edge cases must be documented due to frequency or risk exposure.
Resolve discrepancies between documented SOPs and actual user behavior observed during shadowing exercises.
Choose whether to include supplier and customer touchpoints in end-to-end process maps.
Classify process variations across regions as inefficiencies to eliminate or legitimate adaptations to preserve.
Validate baseline cycle times and error rates using ERP and CRM system data rather than self-reported metrics.

Module 4: Target State Design and Solution Selection

Decide whether to redesign processes around existing ERP capabilities or require system enhancements.
Select between off-the-shelf workflow automation platforms and custom development based on scalability and maintenance costs.
Determine whether approval hierarchies should be flattened, requiring policy exceptions for financial controls.
Choose to consolidate redundant subprocesses across divisions, despite objections from unit-specific process owners.
Define handoff protocols between automated systems and human actors at exception breakpoints.
Evaluate whether robotic process automation (RPA) is appropriate given underlying application stability and IT change velocity.
Specify data governance rules for master data synchronization across integrated platforms in the target state.

Module 5: Change Impact Assessment and Readiness Planning

Conduct role impact analyses to determine which positions require retraining, redeployment, or reduction.
Decide whether to pilot changes in a single geography or functional silo to test scalability assumptions.
Assess whether current IT infrastructure can support increased data throughput from new process flows.
Identify legacy compliance controls that may be invalidated by redesigned approval sequences.
Estimate the volume of data migration required and assign ownership for cleansing source records.
Plan communication cadence for labor representatives when job responsibilities are materially altered.
Validate that support teams have capacity to handle post-go-live incidents without disrupting BAU operations.

Module 6: Governance Framework and Decision Rights

Establish a steering committee with binding authority to resolve cross-functional conflicts on process ownership.
Define escalation thresholds for budget, timeline, and scope deviations requiring executive review.
Assign final sign-off authority for process design changes between business, IT, and compliance stakeholders.
Implement a change request log to track proposed modifications and prevent scope creep.
Determine whether local units can deviate from standardized processes under defined exceptions.
Set frequency and format for transformation progress reporting to the board and investor relations.
Designate a permanent process owner for each end-to-end workflow post-implementation.

Module 7: Execution, Testing, and Cutover Management

Coordinate parallel run schedules between legacy and new processes to validate accuracy without business disruption.
Decide whether to use phased rollout or big-bang cutover based on interdependencies and rollback complexity.
Assign responsibility for test case development and defect resolution between business and IT teams.
Finalize data migration scripts and conduct dry runs to assess performance under full dataset loads.
Train super-users in advance of general staff training to ensure support coverage at go-live.
Freeze non-critical system changes in integrated applications during the cutover window.
Activate monitoring dashboards and alerting rules to detect process bottlenecks immediately after launch.

Module 8: Performance Monitoring and Continuous Improvement

Implement real-time dashboards to track cycle time, error rate, and compliance adherence against baseline.
Conduct post-implementation reviews at 30, 60, and 90 days to identify unintended consequences.
Adjust process parameters based on user feedback while maintaining control integrity.
Decide whether variances from expected outcomes warrant root cause analysis or are within acceptable noise.
Institutionalize periodic process health checks as part of operational governance routines.
Reconcile actual cost savings and productivity gains with business case projections for audit purposes.
Establish a backlog of incremental improvements for prioritization in future release cycles.