Description

This curriculum spans the technical, governance, and operational dimensions of integrating IT into business process redesign, comparable in scope to a multi-phase enterprise transformation program involving process mining, system integration, and change management across global business units.

Module 1: Strategic Alignment of IT with Business Process Objectives

Conducting a capability gap analysis to identify misalignments between existing IT systems and redesigned process goals.
Selecting enterprise architecture frameworks (e.g., TOGAF, Zachman) based on organizational complexity and governance maturity.
Negotiating IT investment priorities with business units when process redesign requires competing system upgrades.
Defining measurable KPIs that link process performance improvements to underlying IT enablers.
Establishing cross-functional steering committees to resolve conflicts between IT roadmaps and business transformation timelines.
Assessing technical debt in legacy systems that constrain automation and integration in redesigned workflows.

Module 2: Process Discovery and Digital Footprint Analysis

Deploying process mining tools to extract event logs from ERP and CRM systems, ensuring data completeness and timestamp accuracy.
Mapping as-is processes while reconciling discrepancies between documented procedures and actual system usage patterns.
Identifying shadow IT applications used by departments that bypass central IT controls but support critical workflows.
Classifying process variants across business units to determine standardization versus localization requirements.
Integrating user activity data from multiple sources (e.g., SSO, application logs) to create a unified view of process execution.
Validating discovered processes with process owners and frontline staff to correct misinterpretations from log data.

Module 3: Technology Selection and Integration Architecture

Evaluating low-code platforms versus custom development based on process complexity, scalability, and long-term maintenance costs.
Designing API contracts between legacy systems and new process automation tools to ensure data consistency and error handling.
Choosing integration patterns (e.g., event-driven, batch, synchronous) based on process latency requirements and system availability.
Assessing cloud service providers for process hosting based on data sovereignty, compliance, and integration with on-premise systems.
Negotiating vendor SLAs for third-party workflow engines to align with business-critical process uptime requirements.
Implementing middleware for protocol translation when integrating systems using incompatible communication standards.

Module 4: Data Governance and Process Automation

Defining master data ownership and stewardship roles to ensure accurate customer, product, and supplier data in automated workflows.
Implementing data validation rules at process entry points to prevent error propagation in downstream systems.
Designing exception handling routines for robotic process automation (RPA) bots when source system interfaces change unexpectedly.
Establishing audit trails for automated decisions to support regulatory compliance and troubleshooting.
Configuring data masking and access controls in test environments used for process simulation and validation.
Aligning data retention policies with legal requirements when redesigning processes that generate new digital records.

Module 5: Change Management and User Adoption

Developing role-based training content that reflects actual system interactions in the redesigned process, not idealized workflows.
Phasing rollout of new IT-supported processes to minimize disruption in high-volume operational periods.
Configuring system alerts and in-app guidance to support users during transition from legacy to new processes.
Measuring user adoption through system login frequency, task completion rates, and error escalation trends.
Addressing resistance from power users who rely on undocumented workarounds in existing systems.
Coordinating communication timelines between IT deployment schedules and HR change impact assessments.

Module 6: Performance Monitoring and Continuous Improvement

Configuring real-time dashboards that correlate process cycle times with system response metrics and user workload.
Setting dynamic thresholds for process alerts to avoid alarm fatigue in high-variance operational environments.
Conducting root cause analysis when process deviations coincide with system outages or integration failures.
Using A/B testing to compare performance of alternative process designs supported by the same IT infrastructure.
Integrating feedback loops from support tickets and user surveys into process optimization backlogs.
Updating process models in documentation repositories when iterative changes invalidate original workflow diagrams.

Module 7: Risk, Compliance, and Audit Readiness

Documenting segregation of duties in automated workflows to meet internal control requirements for financial reporting.
Implementing version control for process automation scripts to support audit trail reconstruction.
Conducting penetration testing on process-facing applications to identify vulnerabilities in user authentication and data access.
Mapping process data flows to GDPR or CCPA requirements for consent, access, and deletion rights.
Preparing system-generated evidence packages for external auditors to validate control effectiveness.
Enforcing change approval workflows for modifications to production process automation logic.