Effective technical due diligence is as much about how you do it as what you cover. For CTOs, investors, and M&A teams embarking on a tech due diligence, following best practices can mean the difference between an insightful review and a superficial one. A thoughtful, methodical approach will yield a more accurate picture of the target company’s technology and ultimately lead to better decision-making. Here is a guide to some best practices, distilled from industry experience and BLS methodology, to ensure your technical due diligence is thorough, efficient, and focused on what matters.
Start by building an experienced, cross-functional diligence team. The ideal technical due diligence team is engineer-led and includes senior experts across the relevant domains of the target’s business. For example, if you’re evaluating a healthcare software company, include a software architect, a cybersecurity specialist, and someone familiar with healthcare IT standards. If hardware is involved, bring in an electrical or mechanical engineer who knows that industry. Seasoned engineers with real-world product development experience tend to make the best diligence leaders. They not only understand technology at a deep level, but they’ve likely seen the kinds of challenges and failures that can occur – which means they know where to look for red flags. It’s often said that in due diligence, “you don’t know what you don’t know”. Having domain experts who have “built it before” ensures that your team does know what to look for. They will be able to intuit where hidden risks might lurk and ask the incisive questions that a less experienced reviewer might miss.
Define upfront what will be examined and to what extent. Technical due diligence can be very broad, so it’s important to scope the effort based on risk areas and the time available. Using the “five pillars” from the previous article is a good template – ensure the plan covers compliance, reliability, security, architecture, and engineering process, at a minimum. Within each, identify any particular focus points. For instance, you might decide that in this deal, cybersecurity and IP ownership are critical to dig into deeply, whereas some other aspects might be lighter touch due to lower risk. A structured checklist or framework can guide this, but remember it’s a starting point. The team should be ready to adapt as they discover information(e.g., if early findings show a potential issue with, say, scalability, then allocate more time to probe that area).
Technical due diligence is not a witch hunt – it’s a conversation. Approach it as a collaborative investigation with the target’s CTO or engineering leaders. Start the process with an in-depth management interview or presentation: let them walk through their architecture, their development process, their known strengths and weaknesses. This sets a collegial tone and often yields candid insights. During the diligence, ask a lot of questions – but frame them constructively. You want the target’s team to be comfortable revealing shortcomings; that only happens if they feel the process is fair and professional, not adversarial. Clarify that the goal is to understand and potentially help plan improvements, not just to find fault.
Reviewing code and infrastructure configuration is an essential part of tech due diligence, but it’s usually impossible to examine everything in detail. A best practice is to do a “guided tour” of the codebase with the target’s lead developers. Have them show you the repository structure, the build process, and walk through some representative sections of code (for example, core modules or components that are critical to the product). Look at how the code is structured and commented. Is it modular? Are there obvious signs of rushed or sloppy coding, like TODOs left in, or large swathes of dead code? Check the version control history for activity patterns – are there recent big changes or churn that suggest instability? Also, examine how issues are tracked (Jira or similar) to gauge how bugs and feature requests are managed internally. For infrastructure, if possible, get a demo of their deployment pipeline and a peek into their cloud environment or data center setup. Evaluate whether they follow Infrastructure-as-Code practices, how they handle backups, and how they monitor systems in production.
Throughout the diligence, keep best-in-class standards in mind as a benchmark. You are essentially evaluating the target company’s technology against an ideal or at least typical standard for a company at that stage and in that domain. For each of the pillars (from compliance to engineering practices), assess where the target stands relative to what you’d expect. For example, if the company is in fintech, compare their security posture against common fintech security requirements (like regular third-party pen tests, encryption standards, etc.). If they’re a SaaS company, check their DevOps maturity against modern SaaS norms (automated deployments, blue-green infrastructure, etc.). This benchmarking helps you identify if any aspect is unusually weak or strong. It also provides context for your findings – maybe the company’s test coverage is only 30%, which sounds low, but if similar startups often have near 0% at that stage, 30% might actually be above-average.
The ultimate output of technical due diligence should be clear findings that inform decision-making and next steps. It’s not enough to simply list issues or praise strengths; you should translate those into business implications and suggestions. For each significant finding, consider what should be done about it and communicate that. For instance, if you discover that the company’s product is not yet ISO 27001 compliant, the report might recommend “Invest in obtaining ISO 27001 certification within 12 months to satisfy enterprise customer requirements,” potentially estimating the effort or cost to do so. If the cloud architecture has a bottleneck, recommend a plan tore-architect that part or use a managed service that can scale. If the engineering team is small but very solid, you might recommend “Retain key engineering staff post-acquisition and consider adding 2-3 developers to accelerate feature development.” By providing these recommendations, the diligence goes from a dry risk audit to a useful roadmap for value creation.
Maintain strict confidentiality and an unbiased stance throughout the process. Technical due diligence often involves accessing sensitive information about the target (code, security setups, etc.). It’s a best practice to formalize data handling: use secure channels for document exchange, limit access to only the diligence team, and destroy or return data after use if required. Also, be mindful of objectivity – confirmation bias can creep in, especially if an acquirer is very excited about a deal. A good diligence team remains neutral and evidence-based in their evaluation. Use data wherever possible (for example, performance metrics, bug counts, test results) to support findings, rather than subjective impressions alone.
By following these best practices – assembling the right engineer-led team, planning and scoping smartly, engaging openly with the target’s tech leaders, examining code and systems strategically, benchmarking against industry norms, and delivering actionable, insightful findings – CTOs and investors can conduct technical due diligence that truly adds value to the deal process. A well-run diligence not only uncovers risks; it also highlights the target’s technical strengths and how to leverage them post-acquisition. It builds a foundation for integration plans or improvement initiatives, and ultimately, it helps all stakeholders have confidence in the transaction. In essence, effective due diligence is about turning every stone efficiently and wisely, so that when it’s time to make an investment decision, you have a clear map of the terrain – both the pitfalls to avoid and the solid ground on which to move forward.