Because tax must interpret information drawn from across the organization, tax leaders naturally see where enterprise data fails to connect across systems. That perspective allows them to engage in enterprise data discussions not only as compliance stakeholders but as participants in data integration and architecture decisions. For CDOs, this makes tax an important diagnostic lens for enterprise data strategy.
2. Challenge the assumption functional data success equals enterprise value
Enterprise data often performs well within individual functions. Finance systems support reporting and close processes, operational platforms capture transactions efficiently, and commercial systems record customer and revenue activity. Within those domains, data may appear structured, reliable and complete.
The real test of enterprise data comes when information moves across functions. At that point, definitions may diverge, entity structures may not align and critical context may be lost. Data that works well within one system can become ambiguous once it is combined with information from other parts of the organization. Tax is often one of the first functions to encounter this gap because it must reconcile information drawn from across finance, operations and commercial systems.
3. Shift the conversation from compliance workload to data design
In many organizations, tax becomes involved in enterprise data initiatives only after platforms, data models and governance frameworks have already been defined. By that point, the decisions that determine how data is captured, structured and reused across systems are largely made.
When tax requirements are addressed this late in the process, teams are forced to work around structural data limitations rather than resolve them at source. Manual reconciliation, additional reporting effort and repeated adjustments become symptoms of architectural choices made elsewhere in the organization.
As Campbell explains, the real problem is often not missing data but missing context. Enterprise systems may contain the relevant information, yet lack the attributes needed to interpret it correctly across functions. Without consistent entity structures, timing conventions or classification rules, tax teams must reconstruct meaning after transactions have already been recorded.
For tax leaders, this creates an opportunity to shift the conversation with CDOs. Instead of framing data challenges as compliance workload or reporting complexity, they can highlight how enterprise data design decisions shape tax outcomes from the start.
4. Turn recurring remediation into a case for upstream data investment
In many organizations, tax teams encounter the same data issues repeatedly during reporting cycles, audits and controversy processes. Transactions must be reclassified, filings amended and supporting information reconstructed from multiple systems to establish the correct tax position.
These recurring fixes are often treated as operational workload, but in reality, they are signals that enterprise data is not being captured or structured in ways that support cross-functional use.
As Campbell observes, many organizations end up addressing the same problems annually because the underlying causes are never resolved at the point where data is created.
“The fix is never pushed upstream, so year after year they’re remediating the same issues. You get to controversy and ask, ‘Where did the data come from?’ And there’s no trail, no data lineage,” he says.
For tax leaders, this pattern provides a powerful talking point with CDOs. Repeated tax remediation indicates enterprise data is not retaining the context required for cross-functional interpretation as it moves across systems. Quantifying the scale of these recurring fixes can help justify targeted investment in stronger data governance, clearer lineage and more consistent enterprise data models.
5. Quantify the hidden cost of shadow tax effort
In many organizations, a significant share of tax-related work is conducted outside the tax function. Finance, controllership and reporting teams often spend considerable time extracting, restructuring or reclassifying information to support tax reporting.
This distributed effort rarely appears in the formal tax budget and is instead embedded within finance close processes, operational reporting and shared service activities. As a result, the true cost of preparing tax data often remains invisible.
As Campbell explains, this fragmented effort can create circular inefficiency across the organization. “Teams outside tax are spending time breaking apart data to give tax what they think it needs, while tax teams are reassembling that same information to make it usable,” he says.
Because this work is dispersed across functions, it is rarely recognized as an enterprise data problem when investment decisions are made. The organization experiences the impact through slower reporting cycles, duplicated effort and operational friction, but the root cause often remains hidden. For tax leaders, mapping where this shadow tax effort occurs can transform the conversation around data investment with CDOs.
6. Link data quality to financial confidence and strategic capacity
The impact of poorly contextualized enterprise data extends beyond compliance. When tax teams are compelled to interpret transactions without the full context needed to apply correct treatment, tax positions may later prove uncertain, forcing organizations to revisit reserves or reassess earlier classifications. These issues affect working capital planning and an organization’s confidence in its financial data.
As Campbell notes, incomplete or poorly contextualized information can lead organizations to take positions that later prove difficult to defend. “If tax teams don’t have all the information needed to make judgment, they can end up taking a wrong position that can be overturned on audit.”
Reliable tax data, therefore, supports stronger reporting, less volatility in tax reserves and greater credibility with finance leadership. Meanwhile, CDOs benefit from a strengthened tax data layer that supports transformation programs, advanced analytics and AI initiatives as data moves across systems.
Why tax leaders should engage CDOs on data strategy
Enterprise data strategies shape tax outcomes long before reporting begins, yet tax functions are often involved only after key design decisions have already been made. Engaging earlier allows tax leaders to ensure the information needed to interpret transactions correctly is captured at source, reducing remediation and improving financial reporting. Framing tax requirements in terms of enterprise data design also elevates the role of the tax function, shifting it from reacting to data problems to guiding how enterprise data is structured and governed.
For CDOs, engaging with tax leaders offers direct insight into how enterprise data performs once it moves across organizational boundaries. Tax must interpret transactions spanning finance, operations and commercial systems, often exposing where data loses context or meaning when used outside the system in which it was created. Bringing that perspective into enterprise data strategy helps ensure information is designed not only for efficiency within individual platforms but for reliable interpretation across the organization.
