How To Maximize The Value Of Technical Due Diligence

Previously published on Forbes on 11/16/2021

Technical due diligence (TDD) is typically requested by investors prior to closing a growth-stage investment or when acquiring a company. A smart investor should expect a lot more out of TDD than a “yes or no” answer to the question “Are there any red flags that warrant canceling the investment or acquisition?” 

Instead, as I highlighted previously in my article “The Art of Technical Due Diligence,” “Technical due diligence should provide actionable information about the upcoming 24 months, including critical dependencies, risk factors and major technical milestones that will usher in product milestones.” 

TDD allows future board members to track technical milestones and thus anticipate the financial ones. Technical milestones typically precede some of the financial milestones by three to six months — for example, when software needs to be re-architected to deliver the scale to serve the expected growth. 

A good technical due diligence identifies: 

• When and where the past is no longer a predictor of the future.

• What new skills will need to be developed in the technology and product teams.

• What new risks need to be handled.

Here are some examples: 

Scale will hit a wall.

This is almost a universal concern in technical due diligence projects. The deal is based on four times or 10 times revenue growth in the next 24 months, but can the software keep up? If the answer is “no,” investors will want to know what it will take to meet the growth projections: architecture redesign, implementation plan along with schedule, resources and budget estimates.

There is a large amount of technical debt.

Only close inspection of the code by a talented CTO can identify whether the code is ready for the next phase of growth. Some of the more frequent scenarios include:

• The company is generating millions of dollars of revenues on code based on its first prototype, typically a monolith, with layers of dead code that supported use cases that were abandoned in the quest for product-market-fit. This impacts not only operational performance but also hinders the development velocity once the team grows beyond a dozen developers.

• The code base is “legacy” and poorly maintained. This often happens with companies that were early on the market, persevered through years of slow growth and now suddenly take off. The code is based on old technology, has been updated — expediently — over time by different teams of developers and has poor documentation. In this situation, a rewrite from scratch is usually the only practical solution.

• For enterprise companies, another common scenario occurs when the software and the data storage are still single-tenant. Transitioning to a multi-tenant architecture is a problem with a known solution, but it is time-consuming and costly.

Development velocity will tank.

Probably the hardest transition to navigate for a startup is when the size of the userbase dictates that quality trumps new features. When a company has a large number of customers, the cost of a serious bug — let alone a DOA release — becomes prohibitive.

This is when test automation and CI/CD automation (including Infrastructure as Code) need to be deployed, which is usually a painful process because existing code must be “retrofitted” with automated regression tests. In addition, development velocity temporarily stalls before accelerating again once a critical mass of automation has been reached.

Another common scenario occurs when the target company is developing products like “three founders in a garage,” i.e., with very little documentation, limited QA, manual deployments. Scaling the team will require changing processes as well as attitudes and, possibly, the CTO.

Risk arbitration is drastically different.

A company with one million users should look at security — and business continuity — very differently than a company that has 10,000 users. At the risk of oversimplifying, the cost of implementing state-of-the-art security is the same in both scenarios, yet the ROI is different: The cost of being hacked is much greater for the former than the latter. Similarly for business continuity: The cost of a one-day outage may be acceptable for the latter company, but may kill the former company.

One of the companies we reviewed at my organization had grown organically from a prototype to one that stored hundreds of thousands of credit cards in its database. Because the growth has been organic and moderate, no one in the executive team noticed that the company had reached a scale where a hacker could destroy the company.

There is an inefficient development process.

An often-overlooked factor affecting development velocity is the alignment, or misalignment, between the executive team, product team and technology team.

This shows up in two ways: a product road map that is aspirational (i.e., dates are not backed up by engineering estimates) and a product road map that zig-zags (i.e, changes every quarter). This situation is normal, and possibly desired, when the company is searching for product-market-fit but counterproductive when it is attempting to conquer the large market that it has discovered.

Moving from chasing opportunities to a mode where formal business cases for new features are developed cooperatively is challenging for the company’s leadership but essential to ensure stability in the product road map, which, in turn, allows the technology team to develop a technology road map as well as predictable releases.


None of the issues presented above are deal killers, but they can lead to a modification of the terms of the deal. For example, investors may want to increase their investment to cover the rewrite of major components of the products. In all situations, even with a well-performing technical team, TDD delivers a list of major milestones that can be tracked by the investors as the company grows.