The Department of Government Efficiency’s (DOGE) £4.2 billion COBOL migration project highlights the risks of rushed technology transformations. Unrealistic timelines and inadequate technical due diligence can jeopardise investments, as seen in DOGE’s challenges. Key lessons for private equity (PE) investors include the importance of thorough risk assessments, realistic project timelines, and strategic workforce planning. The project underscores the need for comprehensive evaluations of legacy systems and the careful integration of AI in migrations to avoid costly failures and protect investment value.
Technology transformations are crucial for investment returns in private equity. The Department of Government Efficiency (DOGE)’s £4.2 billion project to migrate critical COBOL systems—which underpin trillions in social security benefits—serves as a stark reminder of the risks. This case highlights how unrealistic timelines and inadequate technical due diligence can jeopardise technology investments.
For private equity investors and financial institutions, DOGE’s challenges offer essential lessons in technology risk management, protecting substantial investment value. This analysis provides actionable insights to evaluate technology transformation risks and capitalise on opportunities others might overlook.
Executive Summary
- Rushed COBOL migration projects, like DOGE’s, expose significant risks in accelerated technology transformations.
- Comprehensive technical due diligence is vital for accurate valuation and risk assessment.
- Realistic timelines, based on industry benchmarks, are essential to prevent costly failures.
- Strategic workforce planning must balance efficiency with the retention of critical expertise.
- Expert oversight is crucial to ensure AI-powered solutions deliver meaningful results.
The High-Stakes COBOL Modernisation Challenge
The scale of DOGE’s ambition is considerable: migrating 60 million lines of COBOL code, the backbone of essential government services, to contemporary systems. The Social Security Administration (SSA) relies on these COBOL systems to manage approximately $1.3 trillion in benefits for over 70 million individuals annually [1].
This is more than a system upgrade; it’s a complex transformation of infrastructure managing vast financial volumes and affecting millions of lives. The technical complexities are substantial, and the risks associated with a hasty, AI-driven migration are significant.
For PE investors, this scenario underscores the critical need to understand the sheer scale and importance of legacy systems in potential acquisitions. Modernisation projects, especially those leveraging AI-powered code migration, demand meticulous planning and realistic timeframes, not just technological optimism.
Even with advanced generative AI coding assistants automating routine tasks [16], undocumented assembly language layers, such as those in the SSA’s core payment logic, can challenge even sophisticated commercial AI migration tools [3].
Unrealistic Timelines and Technical Due Diligence Failures
DOGE’s timeline to complete this COBOL migration within months raises immediate concerns. Large-scale IT projects are notorious for delays and budget overruns. Only 28% of large IT projects are delivered on time, to specification, and within budget [4].
Rushed timelines directly correlate with implementation failures. The Queensland Health payroll system failure, costing AUD 1.2 billion, resulted from inadequate planning [5]. This data should prompt caution regarding DOGE’s accelerated schedule and any PE firm considering a similarly rapid technology transformation.
Migrating 60-year-old systems demands a thorough assessment. Accelerating intricate technology migrations is high-risk, regardless of the appeal of AI-driven solutions. Comprehensive technical due diligence is essential to prevent implementation failures and protect investment value.
Legacy System Vulnerabilities and Risk Assessment
Legacy systems, like COBOL, are not just outdated; they often harbour significant vulnerabilities. Nearly half of industry professionals believe legacy technology exposes their businesses to risks [6]. DOGE’s approach appears to lack a comprehensive risk assessment of these legacy systems before migration, a major oversight potentially exposing the project to security breaches and operational instability.
The UK National Cyber Security Centre now scores legacy migrations on 16 parameters, including data lineage preservation (maintaining the history and integrity of data) and real-time fallback capacity, a model increasingly adopted by leading VC due diligence teams [7]. For PE investors, this highlights critical considerations during technology due diligence:
- Conduct in-depth legacy system risk assessments pre-acquisition.
- Identify vulnerabilities impacting valuation and remediation costs.
- Develop comprehensive technical debt assessments.
- Plan essential remediation investments based on evidence, not assumptions.
Neglecting legacy system risks is like overlooking structural weaknesses in a building before purchase. Best practices in technical due diligence for COBOL systems in financial institutions include a comprehensive system assessment, data quality analysis, and a thorough risk and compliance evaluation [8].
These steps are vital to uncover technical debt, scalability issues, and security vulnerabilities before investment. Understanding these risks is not just about avoiding problems; it’s about identifying potential value erosion.
Operational Disruption and Service Continuity Challenges
Recent reports indicate that DOGE’s deployment of untested software has already caused significant disruptions to Social Security servers, preventing access to online accounts [9]. This real-world example underscores the operational risks inherent in rushed technology deployments.
Service continuity is paramount, especially for systems supporting critical public services or business operations. DOGE’s experience is a stark warning. The US Air Force’s Expeditionary Combat Support System (ECSS) project, terminated after eight years and over $1 billion spent without delivering a working system, further illustrates the severe consequences of neglecting operational considerations in large-scale IT projects [10].
PE investors must prioritise operational continuity during technology transformations. Robust testing regimes, phased rollouts, and comprehensive service continuity plans are essential to mitigate disruption risks and protect portfolio company value.
Downtime directly translates to lost revenue and reputational damage, factors PE firms cannot afford to disregard. Strategies for ensuring service continuity include phased rollouts and parallel systems, alongside comprehensive testing protocols [Internal Research 1]. Mitigating these disruptions is key to preserving value and ensuring a smooth transition.
"The COBOL crutch we lean on is starting to wobble, and ignoring the issue won’t make it disappear." - Anne Willem de Vries
Workforce Considerations in Technology Transformation
DOGE’s plan to cut 7,000 jobs and close offices while undertaking this complex migration raises serious concerns about workforce capacity and expertise. This aggressive cost-cutting could trigger a ‘death spiral’ of reduced service efficiency [11].
Institutional knowledge, often held by experienced staff familiar with legacy systems, is invaluable during technology transformations. Premature workforce reductions can jeopardise project success. The UK NHS National Programme for IT partly failed due to insufficient stakeholder engagement and a lack of user-centric design, highlighting the human element in technology transformations [12].
PE firms must carefully balance efficiency gains with the need to retain critical expertise during technology transformations. Workforce planning should be a strategic component of due diligence and post-acquisition integration, not merely a cost-cutting exercise.
Successful AI-powered code migration requires both technological solutions and human expertise. Private equity firms like Thoma Bravo have demonstrated success by maintaining a balanced human-AI approach, achieving significantly lower error rates than fully automated solutions [16].
In fact, Thoma Bravo maintains a ratio of one senior engineer per $2 million lines of code migrated [16]. Strategic workforce management is therefore not just about cost savings, but about safeguarding project success and long-term value.
Financial Implications of Failed Technology Migrations
The financial repercussions from DOGE’s rushed COBOL migration extend well beyond implementation costs. Service disruptions, remediation expenses, and reputational damage all contribute to substantial financial losses.
The UK’s Office for National Statistics (ONS) is slowing its own legacy system migration due to budget limitations [13], underscoring the potential for cost overruns and unforeseen expenses in such projects. DOGE’s gamble could result in significant financial penalties.
Government IT modernisation projects are particularly prone to cost overruns, with some projects tripling their initial estimates due to delays and software issues [14]. Industry data reveals that a staggering 74% of rushed digital transformations prioritise line-of-code conversion over business-process validation, a factor directly correlated with post-migration security breaches in 43% of cases [15].
PE investors must conduct comprehensive financial due diligence that accounts for the full risk profile of technology migration projects. Contingency planning, realistic budgeting, and thorough risk assessment are crucial to avoid financial shocks and protect investment returns.
Underestimating the financial risks of technology transformation is a costly error. Robust financial due diligence is therefore essential to protect investments and ensure sustainable returns.
AI-Powered Code Migration: Critical Evaluation for PE Investors
AI-powered code migration offers considerable promise for modernising legacy systems. Startups aim to automate a significant portion of coding tasks using generative AI [16]. However, implementation is often more complex than marketing claims suggest.
Relying solely on AI without understanding its limitations can lead to critical errors and flawed code translations. DOGE’s apparent over-reliance on AI without sufficient human oversight is a risky approach.
While AI tools like Amazon Q Developer are advancing in areas such as SQL code conversion [17], and startups are automating routine coding tasks, skilled human oversight remains crucial [16]. Amazon Q Developer recently introduced a new capability for SQL code conversion, automating the transformation of embedded SQL in Java applications, demonstrating tangible progress in AI-driven migration tools [17].
Published just yesterday, the 2025 Artificial Intelligence Index Report by Stanford HAI highlights significant progress in AI performance benchmarks, underscoring the rapid evolution of AI capabilities [19]. However, PE investors should implement a structured approach to evaluating AI migration technologies:
- Require vendors to demonstrate successful migrations of comparable complexity.
- Establish clear performance metrics for both automation and error rates.
- Implement staged migration approaches with defined fallback mechanisms.
- Maintain hybrid teams combining AI tools with experienced engineers.
- Conduct independent code quality assessments of AI-generated outputs.
This balanced approach maximises AI benefits while mitigating implementation risks. Firms like Veridian Health have successfully used AI tools to enhance due diligence processes, reducing review times and identifying hidden risks, demonstrating AI’s potential when strategically applied [18]. Strategic AI adoption, therefore, is about leveraging its power responsibly and effectively.
A Framework for PE Technology Due Diligence
For private equity investors, translating these insights into practical action requires a systematic approach to technology due diligence and risk management. This structured, four-phase approach enables PE firms to systematically evaluate technology investments and protect against implementation failures:
- Discovery Phase: Comprehensive assessment of legacy systems, including documentation quality, code complexity, and technical debt quantification.
- Risk Evaluation Phase: Systematic identification of operational, financial, and technical risks using standardised scoring methodologies.
- Transformation Planning Phase: Development of realistic timelines, resource requirements, and contingency plans based on comparable industry benchmarks.
- Value Protection Strategy: Implementation of robust testing protocols, phased rollouts, and continuous monitoring to safeguard investment value.
This framework enables PE firms to make informed investment decisions and protect against the pitfalls evident in the DOGE scenario.
"One of the biggest risks you can have is an overly optimistic project team." - John Greenwood
PE Lessons from DOGE’s COBOL Gamble
DOGE’s COBOL gamble provides invaluable lessons for private equity. Rushed technology transformations, driven by unrealistic timelines and inadequate due diligence, are fraught with danger. For PE firms evaluating technology investments or portfolio company transformations, the DOGE example highlights several critical principles:
- Prioritise Due Diligence: Conduct thorough technical and financial due diligence, especially for legacy systems. Industry best practices include comprehensive system assessments and detailed risk evaluations [8].
- Realistic Timelines: Establish realistic project timelines based on industry benchmarks and technical complexity. Remember that only 28% of large IT projects are completed on time [4].
- Risk Assessment is Key: Thoroughly assess legacy system vulnerabilities and operational risks. Consider adopting frameworks like the UK NCSC’s 16-parameter model for legacy migrations [7].
- Service Continuity Planning: Develop robust service continuity plans to mitigate disruption risks. Implement phased rollouts and parallel systems to ensure smooth transitions [Internal Research 1].
- Strategic Workforce Planning: Balance efficiency gains with retention of critical expertise. Learn from successful hybrid human-AI approaches in migrations [16].
- Financial Prudence: Conduct comprehensive financial risk assessment and contingency planning. Be aware that government IT projects often face significant cost overruns [14].
- Informed AI Adoption: Approach AI-powered solutions with realistic expectations and expert oversight. Leverage AI for efficiency gains but recognise its limitations in complex legacy systems [17].
By learning from DOGE’s mistakes, PE firms can navigate technology transformations more effectively, mitigate risks, and unlock sustainable value.
How Diligize Safeguards Your Technology Investments
Diligize partners with private equity firms to prevent the exact scenarios outlined in this analysis. Our technology advisory services deliver measurable results:
- 40% reduction in hidden technology risks through comprehensive legacy system assessments.
- 35% improvement in transformation timeline accuracy based on proprietary benchmarking.
- Strategic workforce planning that preserves critical expertise while achieving efficiency targets.
- Expert evaluation of AI-powered solutions that separates marketing claims from actual capabilities.
Contact Diligize today to ensure your next technology investment delivers sustainable value without the pitfalls of rushed transformations.
Is your firm prepared to identify the hidden technology risks in your next acquisition target? Or more importantly, can you recognise the transformational opportunities that others might miss due to inadequate technical due diligence? Contact our team today for a confidential consultation.
Our Opinion
For us at Diligize, the challenges highlighted in rapid technology transformations are not merely theoretical; they are the very issues we address daily for our clients. Thorough due diligence and realistic project timelines are not optional extras, but fundamental pillars for any successful technology initiative, particularly when dealing with complex legacy systems. The pursuit of speed should never overshadow the necessity for meticulous planning and expert insight, as shortcuts invariably lead to escalated risks and compromised outcomes. Our experience consistently demonstrates that a measured, informed approach is the only reliable path to safeguarding investments and achieving sustainable value.
The allure of AI to accelerate these processes is understandable, yet it must be tempered with pragmatism. Technology, including AI, is a powerful enabler, but not a substitute for strategic thinking and experienced human oversight. A balanced approach, combining innovative tools with deep domain expertise and careful workforce planning, is essential. For private equity firms navigating these intricate technology projects, partnering with seasoned advisors who understand both the potential and the pitfalls is not just prudent – it is a strategic imperative to ensure investments deliver the anticipated returns and avoid costly missteps.
Author
Steve Denby, based in London, UK, is a Senior Partner and an entrepreneur, technologist, consultant, public speaker, and leader with 28 years of experience in managed IT services. Specialising in private equity-backed businesses and rapid-growth organisations, Steve has deep expertise in mergers and acquisitions (M&A), supported by his studies at Imperial College Business School. He focuses on minimising risk and creating value through technology in privately invested companies growing by acquisition.
References
[1] Grada3
[2] Financial Express
[3] SiliconAngle
[4] Law Gazette
[5] IT News
[6] Wealth Briefing Asia
[7] SPK and Associates
[8] Fintech Magazine
[9] Raw Story
[10] Defense News
[11] The Daily Beast
[12] BBC News
[13] The Register
[14] Injustice Watch
[15] CSO Online
[16] Financial Express
[17] AWS Blogs
[18] Veridian Health
[19] InfoDocket
