2 April 2025
Innovation Debt is the friction that must be overcome in order to add a feature or make an improvement to a product. While there are some similarities between Innovation Debt and Technical Debt, and some improvements fit into both categories, Innovation Debt also includes non-technical items, and paying down Technical Debt won't necessarily improve the ease of innovation. By focusing on tasks that can measurably improve innovation delivery, improvements will be easier to justify to non-technical people, and the pace of development will continually accelerate.
Talking to software managers I often hear complaints about features taking too long to ship and teams missing delivery estimates. Digging deeper reveals some form of debt the developer either had to pay down or work around in order to deliver the change. These managers often reminisce about how innovative the organisation used to be and are struggling to figure out what's changed. As technical debt usually doesn't provide any direct benefit to the users there is always tension between developers and management about how much to pay down. If we instead focus on Innovation Debt, the inherent return on investment is easier for non-technical people to justify.
The term Innovation Debt can apply throughout the business including all processes and culture, but in this post I'll focus on software architecture and development processes.
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If it takes a lot of time, money, or effort to deploy a change to production then it's risky to try something innovative. The natural reaction to reduce this risk is to add more layers of manual testing, which slows down the deployment further. Alternatively, the way to reduce risk sustainably is to have an automated deployment process and run it frequently.
New ideas need to be measured in production to ensure that they achieve the desired goals, and then iterated on, or if necessary rolled back as quickly as possible. This is why SaaS webapps are so powerful - if your change can be distributed to users' devices immediately and monitored in real time then the risk of innovating is greatly reduced. The ultimate solution is to use configuration or feature flags to roll out an innovation that can be turned on for a subset of users, monitored, and if necessary turned off within seconds.
If you have insufficient testing developers have no confidence about the safety of their innovation, and figuring out how something is supposed to work delays delivery of the change. Furthermore, defects in production train your developers to be more conservative in future, which kills the culture of innovation in the team.
Conversely if you have too much testing then innovations will break many tests, and fixing them will end up taking the majority of development time. Even running a complete test suite may take so long as to introduce iteration lag and stifle the innovation process.
While too many tests is better than too few, you need to find that sweet spot where testing is an enabler to innovation and not an inhibitor.
Innovation is, by definition, doing something new, so the solution isn't going to be known at the start. Given that developers will need multiple attempts to get it right, the time it takes between attempts becomes significant. One manager told me about a minor innovation in their product which took three years of attempts before finally being abandoned. The innovation debt here is they are working with hardware that is manufactured offsite which means it takes a long time to design and deliver before it can be tested by their developers. To pay down this debt, do as much as possible in software, and/or invest in local testing hardware so the iteration can happen earlier, without requiring full design and build of the final version.
In the same way, upstream dependencies can stifle software innovation while you wait for improvements to be released. Many common libraries aren't well maintained or regularly released, so even when patches are contributed upstream, it can take months or even years to get them reviewed, merged, and released. To unblock innovation it's essential to have some reliable way of forking or patching dependencies until the change is released, for example using patch-package for npm dependencies. Forking and patching should only be a short term solution - if the fix isn't eventually merged upstream then either the maintainer disagrees with the patch or the library is unmaintained. Either way the dependency will ultimately have to be replaced but for now this gives an option for unblocking innovation.
Every product has some essential complexity that cannot be simplified because it models the complexity in the real world or has been highly optimised for some reason such as performance. If you don't know which part of your product is complex, you probably developed it - ask a junior developer and they'll tell you. The problem arises if developers are reluctant to make changes elsewhere in the codebase just in case they break something they don't feel like they fully understand. To mitigate this, hide the complexity in a module behind well defined APIs. The best example I've worked on is where the complexity was with an integration with an archaic government system. Because the original developers had done a great job of encapsulating the code in a module with a well defined API, I was never afraid of breaking the integration.
One mistake I've made is exposing too many endpoints with too many parameters. Specifically a product I worked on had all requests to the database were proxied through, which means the product has to support the entire database API. This was done intentionally as a feature because it exposed a very powerful set of APIs for users to query, without going to the effort of defining all the endpoints ourselves. Eventually, however, it became difficult to innovate because we had no way to know which database APIs were being relied on, so it was too easy to accidentally break backwards compatibility. In the extreme case, if we needed to replace the database it would cause a major disruption, completely breaking for any developer using those APIs. Once this debt was identified we began the slow process of providing specific APIs and migrating requests to use those instead of direct database access.
As well as intentionally broad API definitions, there are also leaky abstractions, which can impact innovation in the same way but due to being unintentional are often not discovered until something breaks.
The resolution for these issues is always a breaking change which becomes more expensive as your usage grows, so it's essential to identify and resolve it as early as possible.
Innovation debt is constantly being added throughout product development, and ultimately it will become impractical for your team to innovate. As the debt is incurred continuously it must also be reduced continuously as part of the normal development process. This work could take up as much as 25% of your team's time, but in my experience the debt is already inflating development effort by that much on each and every change.
The earlier you can identify and start fixing these debts the sooner you start benefiting from quicker and more agile software development.