Is your tax technology architecture best practice, or just familiar?

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Is your tax technology architecture best practice, or just familiar?

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Experience often shapes tax technology decisions, but Kathya Capote Peimbert of Vertex argues that familiarity should not be mistaken for evidence when evaluating enterprise architectures

Experience is a powerful guide, right up to the point where what worked before becomes the blueprint for what should work everywhere. In global organisations, experience without comparative perspective can quietly become a constraint.

Some of the largest tax technology decisions rest on surprisingly small samples.

A leader standardises around an architecture because it worked at a previous company. A team replaces a platform because the last implementation failed. A regional solution becomes the global template because it solved an urgent problem well. An adviser recommends an approach they have implemented many times before.

None of those decisions are necessarily wrong. But experience and evidence are not the same thing.

Which raises a difficult question for executives approving multimillion-dollar transformation: how do we actually know what good looks like?

When experience becomes the benchmark

Most organisations never get enough repetitions to build comparative experience. A multinational may undertake a major tax transformation once in a decade. Its leaders learn from what they have seen: their ERP landscape, their providers, their organisational structure, their successes, and, often more powerfully, their failures. Executives bring lessons from previous companies. Advisers bring patterns from previous clients. Technology providers bring deep knowledge of the architectures their own platforms enable.

All of that is valuable, but it also creates a subtle risk. Our experience becomes our reference point, and our reference point becomes our definition of good.

Ten years with one operating model is not ten years of evidence about which operating model works best. Implementing the same architecture 20 times proves the adviser knows how to implement it successfully. It does not prove the architecture is optimal.

Everyone brings expertise. Everyone also brings a lens. The executive challenge is telling them apart.

Best practice, or familiar practice?

Organisations reach for the language of best practice easily. We should be more demanding about what earns the label: best among which alternatives? Measured against which outcomes? Observed across how many operating models, industries, and jurisdictions?

A solution is often called best practice because it worked somewhere else. But “worked” is a low bar for an enterprise architecture decision. Did it scale? Did it reduce complexity, or relocate it? How much manual intervention remained? What was the organisation left maintaining once the implementation team moved on? Those questions separate implementation success from strategic success.

Success also creates bias. Failure gets investigated. Successful implementations get copied. Yesterday’s sensible solution becomes tomorrow’s architectural assumption without ever being tested again.

Knowing what good looks like

The capability global organisations increasingly need is not more experience. It is comparative intelligence: the ability to evaluate a decision not only against what the organisation or its advisers have seen but against the multiple ways the same problem can be solved. That changes the questions.

Not: does this solution work? But: compared with what? Not: has this architecture been implemented successfully? But: under which conditions does it outperform the alternatives? Not: can this provider support our requirements? But: what are we choosing to own, outsource, standardise or duplicate by selecting this model?

None of this requires CFOs or CIOs to become tax technologists. It requires them to ask for transparency about the evidence behind a recommendation. When someone tells the C-suite “this is best practice”, the most valuable response is usually the simplest one: how do we know?

Why the question is getting harder to avoid

This would matter even if tax technology were standing still, which it isn’t. More than 80% of tax administrations surveyed by the OECD are developing application programming interfaces to enable system-to-system interaction with the platforms businesses run on.

As tax processes move closer to enterprise data, these decisions now sit at the intersection of tax, finance, data, and enterprise architecture. Today’s choice shapes tomorrow’s integrations, data flows, providers, controls, and operating model.

It also shapes something less visible on the business case: the distance between the moment a compliance decision is made and the moment it has to be defended. As obligations move into the transaction itself, an architecture is judged not only on whether it produced the right answer but on whether that answer can still be evidenced years later. That is the arc described at Vertex as “Decision-to-Defense”, and it is the part most likely to be underweighted at approval.

In that environment, familiarity gets expensive.

Experience needs perspective

None of this is an argument against experience, or against advisers. Quite the opposite. Experience becomes far more valuable when it is tested against perspectives beyond our own. The strongest advisers do not simply tell an organisation what they have seen work. They explain where it worked, why it did not elsewhere, what alternatives exist, and which assumptions may no longer hold. The strongest internal leaders hold themselves to the same discipline.

That is the difference between accumulated experience and informed judgment. And it may be what good increasingly looks like: not a particular architecture or provider, but an organisation capable of evaluating alternatives without mistaking familiarity for evidence.

So before the next major tax technology investment is approved, the C-suite might ask one deceptively simple question: how do we know this is the best way to solve the problem, and not simply the best way we have seen so far?

Because the quality of a transformation depends on something that comes before the technology. It depends on the quality of the decision that selected it.

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