For many years, the “Single Model of Reality” has been the gold customary for finance and accounting professionals in search of to reconcile knowledge throughout the enterprise. The intuition is comprehensible: a superbly balanced ledger and a single, agreed-upon dataset are foundational to monetary integrity. However as know-how and enterprise wants evolve — significantly with the rise of AI and knowledge science — the pursuit of a single, excellent dataset is not simply unrealistic; it could possibly hinder progress.
At this time’s finance leaders face mounting strain to ship quicker and extra actionable insights. Knowledge and analytics are CFOs’ prime precedence, but many organizations stall main know-how initiatives, from ERP upgrades to AI pilots, as a result of they’re ready for his or her knowledge to be “excellent” earlier than taking the subsequent step. This can be a expensive mistake.
The truth is that, in a contemporary enterprise, a real Single Model of Reality is sort of unattainable to attain. Knowledge is distributed throughout numerous programs, every with its personal definitions and enterprise logic. Even in case you may power each stakeholder onto a single dataset, the method can be costly, gradual and fraught with politics. Worse, by the point you are carried out, a lot of the information will already be outdated or irrelevant for decision-making.
As an alternative, forward-thinking finance leaders are embracing the idea of “Adequate Reality.” This method pursues knowledgeable trade-offs between the price of unhealthy knowledge and the price of extra governance. It is about making certain knowledge is “match for goal”— clear and ruled sufficient to help compliance, reporting and analytics, however not so inflexible that it stifles innovation or responsiveness.
Knowledge material, knowledge mesh and the phantasm of unity
Rising applied sciences like knowledge material and knowledge mesh are altering the panorama. These federated or virtualized platforms current customers with a seamless expertise, hiding the complexity of a number of underlying knowledge sources. To the tip person, it seems to be like a single unified supply — although knowledge may very well reside in lots of silos.
This can be a game-changer for finance and AI. With an information material, entry to data is enabled to a level by no means seen earlier than. Nevertheless, it’s vital to acknowledge that the “single” view is a product of know-how, not a assure of excellent, immutable knowledge. Knowledge safety, entry controls and governance are extra necessary than ever, significantly when delicate monetary or HR knowledge is concerned.
The fit-for-purpose method: centralized the place it issues, versatile the place it counts
Adequate Reality will not be about abandoning requirements. Knowledge ought to embrace a wide range of supply programs and knowledge repositories which can be clear sufficient to help compliance and core reporting, however not so rigidly ruled that it stifles innovation.
Gartner (August 2025)
Sure knowledge, particularly grasp knowledge like clients, distributors or workers, have to be tightly ruled and constant throughout the enterprise. That is very true for monetary reporting, the place immutability and auditability are nonnegotiable. Controllers and CFOs should be sure that the information underlying the P&L, stability sheet and money move statements is dependable and defendable.
However not all knowledge requires this degree of rigor. Many knowledge components, corresponding to addresses utilized by totally different departments, or quickly altering operational metrics, profit from a extra versatile, federated governance mannequin. Adequate Reality means centralizing governance the place ambiguity is unacceptable and pushing it out to regional or native groups the place higher flexibility is required. The result’s an information setting that’s healthier for goal, relatively than match to a singular, inflexible customary.
AI and Adequate Reality: progress with out perfection
A typical fable is that AI and superior analytics require excellent knowledge. AI can truly perform and even thrive with knowledge of various high quality and completeness. AI fashions can fill gaps, normalize inconsistent inputs, and even generate artificial knowledge to deal with lacking data. The hot button is to anchor your knowledge governance and grasp knowledge administration to enterprise wants and outcomes, to not an unattainable ultimate of perfection.
Contemplate the instance of an oil and gasoline firm that used AI to optimize rig efficiency. Their knowledge was at first messy and inconsistent, however by specializing in the information that issues most for his or her resolution fashions, they’re extra apt to attain vital operational enhancements and thousands and thousands in financial savings — with out ready for excellent knowledge.
The Adequate Reality method is about incremental progress. Outline your use case, govern your knowledge to the extent obligatory for that goal, deploy your analytics or AI, after which transfer on to the subsequent enterprise consequence. This cycle permits finance groups to keep away from the “boil the ocean” lure and ship worth rapidly, whilst knowledge high quality continues to enhance over time.
The longer term is Adequate Reality
The period of the Single Model of Reality as the one acceptable customary is over. Finance should undertake a toolkit of approaches that stability accuracy, pace, flexibility, and enterprise relevance. Adequate Reality makes good, risk-based choices about the place to spend money on knowledge high quality and governance, and the place to just accept “adequate” to maintain the enterprise transferring ahead.
Cease ready for excellent knowledge. Begin constructing an information technique that’s ample to your wants, strong the place it counts, and versatile sufficient to allow the subsequent wave of finance innovation — together with AI.
Grant Faulkner Nelson is a vice chairman, workforce supervisor and key initiative chief at
Since becoming a member of the corporate in 2019, he has turn into well-known for his potential to professionally problem each specialists’ and shoppers’ D&A predispositions with constructive options. His 22 years of practitioner expertise main D&A technique, D&A governance and MDM, superior analytics, COEs, FP&A, administration reporting and dashboarding) allows him to comfortably flex with shoppers’ wants. Moreover, his down-to-earth method has made him extremely wanted by many inside each the finance and analytics capabilities. He earned his MBA from Georgia State College’s Robinson Faculty of Enterprise and his B.S. from the College of Colorado, Boulder in Worldwide Affairs. As a household man and former rugby participant, he enjoys staying lively and, after hours, is commonly discovered teaching his daughters’ sports activities groups.
