Enabling Better M&A Decisions by Exposing IT Risks Early

In the context of M&A and business transactions, the client needed to identify and manage technology risks before and after deal execution, including risks related to IT strategy, systems, data, vendors, and post-close operations.
Traditional IT Due Diligence activities were resource-intensive, highly manual, and required reviewing large volumes of documents across multiple functional areas, increasing the risk of oversight and inefficiency.

We supported the client by delivering structured IT Due Diligence (ITDD) services using a proven framework and further improved execution efficiency and quality by applying AI agents leveraging Microsoft Copilot and Power Automate.

Our Approach

IT Due Diligence Framework and Risk Assessment

• Conducted ITDD across key areas including:

  • IT strategy, governance, security, finance, organization, and vendor dependencies

  • Applications, ERP, data, infrastructure, cloud, integrations, and cybersecurity

  • Carve-out and integration design, TSA considerations, and Day 1 / Day 100 operating model risks

• Applied the SC ITDD Framework to systematically evaluate risks, dependencies, and evidence gaps.

• Identified red flags through structured confirmation points, IRL checks, and QA lists.

Execution Support and Vendor Coordination

• Developed ITDD support proposals, interview agendas, checkpoints, and management QA lists.

• Reviewed disclosed materials, seller responses, and outputs from external advisors.

• Coordinated vendor management, progress tracking, and quality reviews when third-party consultants were involved.

AI-Enabled Efficiency Improvement

• Configured AI agents in Microsoft Copilot to search and analyze large volumes of documents across IT, Finance, HR, and Operations folders.

• Used Power Automate to submit structured queries to the AI agents and automatically consolidate responses into Excel files.

• Incorporated human-in-the-loop review to validate AI-generated outputs and ensure reliability and accuracy.

Key Issues Addressed

• Limited visibility into critical IT risks, dependencies, and transition requirements early in the deal lifecycle.

• High manual workload and time pressure during ITDD document reviews.

• Risk of overlooking important information spread across multiple functional document repositories.

• Inefficient consolidation and review of findings across teams.

Results

• Improved decision quality by surfacing critical IT risks, dependencies, and transition considerations early.

• Reduced the risk of missed issues through AI-assisted, cross-functional document analysis.

• Significantly reduced manual workload and review time by automating information aggregation.

• Enabled faster and more structured ITDD execution while maintaining human oversight.

• Delivered actionable outputs, including:

  • ITDD reports with executive summaries

  • Confirmed risk lists and evidence gaps

  • Day 1 and PMI support roadmaps