Published: 07 February 2024
Although many finance organizations want to implement advanced analytics, few have made meaningful progress. This research outlines four key lessons from UCB’s digital finance transformation that will help FP&A leaders overcome barriers to adopting advanced analytics in a short timespan.
Finance teams overestimate advanced analytics’ data requirements; the data they already have is sufficient for value-add machine learning projects.
Using technology use cases to influence advanced analytics adoption is counterproductive, time-consuming and distracting.
“Pure” data scientists are often unnecessary; a citizen data scientist can solve 90% of finance’s business challenges.
Traditional finance communications don’t address business perceptions that algorithms are a black box, reducing adoption of advanced analytics.
To progress advanced analytics in finance, FP&A leaders should:
Embrace the data governance strategy of “sufficient” truth (not “single version” of truth)to use data in its current state to begin advanced analytics projects.
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Analysts:
Financial Services Business Leader Research Team
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