Make insights visible
A CFO who kept strategic dashboards 'in his head' lost credibility—executive projects must be explicit, documented and shared across stakeholders. Separately, research shows 73% of CFOs struggle not with forecasts but with getting leaders to act on data, so visibility matters more than perfect models. ( )
Alisa Cohn described an X post recounting a senior finance leader whose key strategic metrics existed only in his personal mind, and the episode ended with that leader losing influence when colleagues couldn’t validate or act on his numbers ( ). A follow-up X post tied that failure to a wider problem: many finance chiefs say the barrier is not model math but getting other leaders to move when data is presented, a point echoed in the thread shared by another finance executive on X. (x.com). Recent surveys quantify the execution gap: a Coupa report found 73% of finance leaders name data quality and AI readiness as a primary barrier to extracting business value from analytics, while Pigment’s Office of the CFO research reported that 89% of CFOs admit to making decisions monthly using inaccurate or incomplete data. ( ). Visibility failures sit behind those numbers: Gartner’s finance research shows CFOs are increasingly accountable for enterprise metrics and analytics, and EY’s DNA of the CFO research found roughly 44% of finance leaders struggle with data visibility inside their organisations. ( ). Practical anti-fragility steps described in vendor and practitioner write-ups include formal data governance, published data dictionaries, and a RACI for metric ownership so that executive KPIs are repeatable and auditable rather than tacit knowledge, with revenue-governance case studies showing restored trust after standardising definitions and sync processes. (durity.com). Implementation examples show dashboards that were previously ignored became decision tools after one-page executive summaries, clear recommended actions and drill-paths were added, and modern “decision intelligence” platforms that combine narrative context with causal signals accelerated adoption in several mid-market finance teams. ( ). FP&A playbook items aligned to these findings include building compact driver-based models that tie revenue, margin and working-capital KPIs to 3–7 operational levers (sales volume, price mix, days-payable/receivable), pairing each variance with a decomposition tree or P/V/M split for root cause, and delivering a one-slide “so‑what/now‑do” with recommended executive actions and owner and deadline. ( ).
