Why Implementation and QA Deserve Their Own Seat at the Table

By: Mel Sutton, ALTALLO - Founder

Published: 2026-02-10 · Read time: 8 min · Category: Technology

Felipe Wetter, CEO of Alpenbridge Group, discusses why software implementation and QA deserve dedicated focus, the hidden costs of rushing delivery, and what it takes to build a disciplined implementation function.

[HOST]: At a glance, software implementation and QA feels like something teams should just handle internally. Why doesn't that hold up in practice?

[GUEST]: For most SaaS companies and scaleups, implementation and testing aren't the core expertise (they are for my business, but not for most). Implementation is still critical for delivery and customer success, but the real core is usually the tech itself, followed by customer acquisition.

That's where outsourcing comes in. Outsourcing implementation and testing are really about helping the company scale by letting internal teams focus on what actually differentiates the product instead of spreading themselves too thin.

On top of that, it helps you handle spikes in demand without hiring permanently, maintain high-quality delivery, and keep fixed costs lower (which always helps valuation too).

[HOST]: What do companies most underestimate when they decide to implement or test complex systems themselves?

[GUEST]: In theory, implementation is supposed to be repeatable work, right? I'd say that's wrong.

Tech implementation is full of edge cases, unexpected behavior, and moments where teams hit bugs or dead ends. What looks repeatable on paper quickly breaks down in real environments.

Because of this, the most underestimated part of implementation isn't just execution, but the time, coordination, and prioritization it demands. Teams are constantly forced to decide under pressure what gets fixed now. Without clear prioritization, implementation work easily spills over, pulls focus from core product development, and slows the entire organization down.

[HOST]: What's the most common failure mode you see when a vendor implementation goes wrong?

[GUEST]: From experience, the main reason implementations fail is a lack of clarity around what's actually required to make them work.

Either the end client isn't fully aware of the internal process changes needed to support the new system, or the tech company doesn't scope the work properly. In both cases, the result is the same: delays, poor visibility into progress, missing or incomplete data, and eventually project bottlenecks.

[HOST]: What breaks first when QA is rushed, under-scoped, or treated as a checkbox?

[GUEST]: Your bank account. Jokes aside, when you skip the playbook and rush to deliver, you almost always end up paying for the "time saved" later. Maybe it takes a few days or a few weeks, but once the client starts using the product, the bugs show up. One hotfix after another. Then another patch release.

All of that means more QA time, more UAT, and more hours from implementation teams. Adding up to far more than if things had been done properly the first time. In the end, it simply costs more.

Or worse, depending on the bugs, it can damage your reputation. Clients start thinking, "There's always something broken! they never really fix it." And once that perception sets in, it's extremely hard to undo.

[HOST]: What do hedge funds or vendors usually try before they bring in an external implementation partner?

[GUEST]: When companies try to keep implementation in-house, they often end up stretching existing engineers or ops staff to cover QA as well. The problem is that there's no real specialist focused on implementation and testing. Instead, you have people juggling multiple roles that are all equally important.

That forces them to constantly prioritize one task over another, even when those tasks shouldn't be competing in the first place. And implementation and QA are usually the ones that get pushed back, which eventually shows up as delays, bugs, or quality issues.

[HOST]: At what point does doing this work in-house stop making economic or operational sense?

[GUEST]: It stops making sense when implementation and QA start competing with core product work for the same people and priorities.

The moment engineers or ops teams are constantly context-switching, delaying releases, or firefighting issues that come from rushed or under-resourced implementation, the real cost is already higher than it looks.

At that point, you're not saving money, instead, you're just spreading risk: slower product development, lower quality, frustrated teams, and eventually unhappy customers. That's usually the signal that implementation should be treated as a dedicated function, not a side task.

[HOST]: Who inside the organisation feels the pain first when an implementation fails or slips?

[GUEST]: A failed implementation is the first step toward churn, delayed revenue, missed forecasts, and damaged trust (which is why it should sit at the top of leadership's concerns.)

Having said that, the owners of the business feel the pain the most. They've invested huge amounts of time and energy building the platform, the technology, and bringing in new clients. Especially when the product is complex and requires significant changes on the client side.

[HOST]: What's the most expensive or high-impact mistake you've seen caused by poor implementation or testing?

[GUEST]: One of the most dangerous and expensive mistakes in poor implementations happens right at the beginning: misunderstanding the scope of the work.

When the scope isn't clear from the start, teams underestimate the effort required. From there, it's one issue after another: timelines slip, expectations drift on both sides, and what should have been a straightforward implementation turns into constant rework, change requests, and firefighting.

The result is extra hours, delayed go-lives, frustrated clients, lost confidence and ultimately, lost deals.

[HOST]: How do you balance speed versus correctness when clients are under real trading or launch pressure?

[GUEST]: When it comes to speed, you need to have a resource buffer. You have people working on a project, but you also need additional resources who know the solution and can be deployed quickly. And when it comes to correctness, there's really no alternative to constant training. Once people know the system, they still need to stay on top of new features, bug fixes, and updates, and that requires continuous training across the team and a good communication with the product team.

[HOST]: Where does automation genuinely help in QA, and where does it create a false sense of safety?

[GUEST]: Automation helps in QA once testing has been successful, processes are solid, and the system is ready for genuine repetition. It doesn't work well when applied to new or evolving cases. Automated tests can only validate known assumptions.

New features, new integrations, and new client behaviors still require manual testing and human judgment. That's why automation should be used to reinforce stability, not to discover it. The real value in QA comes from balancing manual exploration with automation once things are truly repeatable and bulletproof.

[HOST]: What are clients actually paying for when they engage an outsourced implementation or QA partner?

[GUEST]: You're not paying for an outsourced team just to execute. You're paying for accumulated experience. A strong implementation or QA partner brings lessons from dozens of past projects, which helps with scoping, coordinating, reporting, and process improvement. The real value isn't just the extra capacity, but better outcomes: smoother client delivery, clearer ownership, and a more disciplined implementation function inside the company.

[HOST]: If your firm disappeared tomorrow, what capability would clients struggle the most to recreate internally?

[GUEST]: What's hardest to replace is a specialized team that has seen the same SaaS problems dozens of times across different clients, technologies, and edge cases. A team that knows how to anticipate them before they turn into issues.

That pattern recognition, combined with disciplined execution and strong client coordination, is what typically takes years to build internally.

[HOST]: What's a belief you had about implementation or QA work that turned out to be wrong?

[GUEST]: I always thought that knowing the technology was enough. But over the years, it became clear to me that this isn't. What matters even more is knowing how to structure an implementation: having a clear playbook that turns technical knowledge into a repeatable, predictable process, while accounting for edge cases, potential blockers, and miscommunication.

[HOST]: Why do you think external partners often spot issues internal teams miss?

[GUEST]: External partners often spot issues internal teams miss because their focus is different.

Internal teams are also running UAT, supporting releases, coordinating with DevOps and developers, and handling other responsibilities across the organization. QA teams, in particular, are rarely "just testing"; they're constantly context-switching and firefighting.

External teams, on the other hand, bring dedicated focus and a fresh perspective, which makes it easier to spot gaps, inconsistencies, and risks that busy internal teams simply don't have the bandwidth to catch.

[HOST]: What gets harder as systems become more interconnected across vendors, asset classes, and data sources?

[GUEST]: Great question. There's the technical side, where you need all these different systems to integrate seamlessly, but there's also the question of who owns each part of the process. Small changes ripple across integrations, assumptions break, and failures become harder to trace.

A single-system problem can turn into a coordination and validation problem which makes implementation, testing, and accountability significantly more complex.

[HOST]: What's one problem in financial software implementation or QA that the industry still hasn't solved well?

[GUEST]: I believe a key unsolved issue is predicting real-world complexity without access to real data. Anticipating the full range of variations, edge cases, and failure modes that come from private deals, bespoke agreements, and complex client behavior requires large amounts of data. Data we simply can't access either because of privacy, regulation, and trust make direct access impossible. As a result, teams are forced to design and validate systems without fully understanding the conditions they'll operate under, leaving production to surface the true edge cases.