About This Episode
In episode 13 of Data & AI Heads, host Ian Allison speaks with Chris Scholz, a consultant with over a decade of experience spanning Deloitte and other major firms, about one of the most persistent friction points in enterprise data work: the gap between data teams and the office of the CFO. Chris reframes finance not as a non-technical antagonist but as one of the largest and most data-native functions in any organization, one whose needs have fundamentally shifted over the past two to three decades from data aggregation toward advanced insight generation and business storytelling.
Chris traces the evolution of finance data maturity through three broad eras: the early challenge of simply sourcing and storing data, the data warehousing and consolidation era, and today's paradigm where access to data is table stakes and CFOs are demanding predictive analytics, scenario modeling at the customer and SKU level, and narrative context for board and investor presentations. He argues that data teams who remain focused on pipeline delivery without understanding the downstream business use cases are leaving enormous value on the table and quietly fueling an adversarial dynamic with finance leadership.
The conversation closes with practical guidance for data leaders: embed your engineers alongside finance colleagues, eliminate gatekeeping where it is safe to do so, and prioritize learning the language of finance over chasing the latest technical certifications. Chris's core message is clear: understanding what the CFO is accountable for is the single highest-leverage investment a senior data professional can make in their career.
Key Takeaways
- Finance is one of the largest data consumers in any organization, and data teams that recognize this shift their posture from vendor to strategic partner.
- Two to three decades ago, simply sourcing and storing financial data was a major win; today that capability is table stakes, and CFOs expect data teams to drive insight, not just aggregation.
- The most successful finance data projects Chris has been part of involved engineers sitting side by side with the analysts who would use the output, learning what the data actually means to the business rather than building solely to a spec sheet.
- CFOs need to defend numbers in front of boards, investors, and lenders, so data teams must understand that accuracy and narrative context are not preferences but existential requirements for their finance partners.
- Senior data leaders should enable their teams to spend regular, structured time with finance colleagues to understand pain points firsthand, rather than waiting for requirements to arrive as tickets or spec sheets.
- Reducing gatekeeping between data and finance teams accelerates cross-pollination of skills, but must be paired with proper governance, training, and clear accountability to prevent rogue analysis and data validation disputes.
- Investing in learning finance fundamentals and business context will do more for a data professional's long-term career than acquiring another tool certification, because understanding the end use case is what enables truly transformative data work.
- A new class of role, the finance systems manager or director, has emerged in recent years specifically because the integration and governance of finance data tools has become a strategic priority, signaling how seriously the CFO office now takes data infrastructure.
What We Cover
Frequently Asked Questions
Why do data teams and CFO organizations so often end up in an adversarial relationship?
According to Chris Scholz, the tension usually stems from a lack of mutual understanding. Data teams view finance as constantly making demands, while finance sees data teams as disconnected from business outcomes. The root cause is that data professionals often build to technical specifications without understanding what the CFO actually does with the output or what they are accountable for in front of a board or investors. Bridging that knowledge gap significantly reduces friction.
How have the data needs of a CFO organization changed over the past 20 to 30 years?
Chris Scholz describes three phases. Twenty to thirty years ago, simply sourcing and storing financial data in data warehouses or data marts was the primary challenge and a major win. Over the following decade, consolidation and cleansing became the focus as ERP and BI tools matured. Today, data access is table stakes, and CFOs are focused on using that data to generate predictive analytics, trend and pattern recognition, and detailed scenario modeling at the customer and product SKU level, all in service of better board-level decision-making.
What does Chris Scholz say is the most effective way for data engineers to deliver value to finance teams?
Chris recommends that data engineers embed themselves alongside the finance analysts who will actually use the data products, working shoulder to shoulder rather than disappearing into a backroom to code against a spec sheet. The highest-performing projects he has been part of involved engineers developing genuine subject matter expertise in the data they were building pipelines for, understanding what the numbers mean and why they matter to the business. This contextual knowledge allows engineers to catch problems early and avoid costly rework.
Should data leaders allow finance team members to write their own SQL queries or access data platforms directly?
Chris Scholz supports reducing gatekeeping where possible, arguing that cross-pollination between finance and data teams is valuable. However, both Chris and host Ian Allison acknowledge real risks: a finance analyst writing incorrect queries can produce numbers that contradict official data, triggering lengthy validation exercises, or a team may make decisions based on flawed self-service analysis. The consensus is that access should be enabled with proper training, governance guardrails, and clear accountability structures, driven from the top down by data leadership.
What single piece of advice does Chris Scholz give to senior data executives about working with the CFO?
Chris's closing advice is to understand your CFO deeply: know what concerns they carry, understand what they do with the data you produce, and recognize that they must personally vouch for those numbers in front of boards, outside investors, and lenders. He argues that walking a mile in the CFO's shoes is the foundational step from which all other improvements in the finance and data partnership flow, and that it is the highest-leverage action a senior data professional can take.
Why is learning finance more valuable for data professionals than pursuing new technology certifications?
Chris Scholz argues that understanding the business use case and end outcome unlocks genuinely transformative data work, whereas technical skills alone only enable incremental automation of existing processes. Ian Allison references an observation that data professionals are often incentivized to job-hop and collect tool certifications for short-term pay gains, but Chris contends that the long-term strategic play is learning the language of the business, particularly finance, because that understanding allows data teams to anticipate needs, avoid rework, and deliver insight rather than just data.
What is the emerging finance systems manager role and why does it matter for data leaders?
Chris Scholz points to the rise of finance systems manager, director, and VP level roles as evidence of how seriously CFO organizations now take data infrastructure. He notes this role type barely existed five to ten years ago and has emerged specifically to manage the integration of tools like ERPs, CPM platforms, and BI solutions such as Power BI and Tableau. For data leaders, this signals a counterpart on the finance side who speaks both languages and can serve as a key bridge between the two organizations.
About the Guest
Chris Scholz
Chris Scholz is a data and finance consultant with over a decade of experience working across major consulting firms including Deloitte. He specializes in closing the gap between enterprise data teams and the office of the CFO, helping organizations translate raw financial data into actionable business insight. His work spans finance, accounting, and FP&A functions, and he has led large-scale data projects where he embedded technical teams directly within finance organizations to ensure data pipelines and analytics solutions meet real business needs. Chris brings a hybrid perspective that combines deep knowledge of financial operations, data engineering practices, and the organizational dynamics that determine whether data investments deliver lasting value.
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