CFO Talk: Data-Driven Decisions: Unlocking the Power of Analytics in FP&A Part 1 of 2

If you thought the wildest thing to happen to a finance department was a spreadsheet with color-coded tabs, think again. On the latest episode of CFO Talk: Data-Driven Decisions: Unlocking the Power of Analytics in FP&A” host Steve Rosvold and guests Brian Lapidus (Director of FP&A Practice at AFP) and Prashanth Southekal (Founder, DBP Institute) embark on a lively expedition into the jungle of digital transformation in finance.

Their mission? To answer the burning question: “Why now?” when it comes to CFOs embracing analytics and data, and chart a course for those of us still hacking through the undergrowth of dashboards, acronyms, and occasionally, actual data.

Let’s break down their conversation into bite-sized, digestible, data-driven lessons.

Lesson 1: The CFO’s Evolving Identity Crisis (And Why Now Means Now)

As Prashanth Southekal puts it, the CFO has ditched the green eyeshades and receipt piles. The CFO’s world has expanded from “compliance and reporting” to “growth, compliance, and operational efficiency.” We’re talking Matrix-style evolution here—except instead of dodging bullets, they’re dodging irrelevance if they don’t embrace data analytics and AI. “If you don’t do it now, you will be left behind or… replaced,” Prashanth warns, speaking the terrifying gospel of today’s finance world.

The data deluge is real: By 2030, company data will have doubled—so if you’re still struggling with five terabytes, buckle up. If you’ve got the tech (which, let’s face it, you probably do), the only thing holding you back is your own hesitation… and maybe your company’s Wi-Fi.

Lesson 2: “Why Now?” Isn’t Just for Millennials

Brian Lapidus, ever the devil’s advocate, argues that it’s always been the time to adopt better analytics (cue sighs from finance veterans everywhere). The exponential growth of data is matched only by the exponential promises of next-gen analytics tools—with each iteration promising salvation. “If I just get it right today, I’ll be all set—no,” Brian laughs. “Tomorrow, you’ll throw it out and do something even better.” It’s not a project; it’s a journey. Get comfortable with change, or get comfortable being obsolete.

Lesson 3: FP&A—From Swiss Army Knife to Super Specialist

Once upon a (not-so-distant) time, the FP&A professional was a singular hero: one spreadsheet, infinite pivot tables, and caffeine. But the field has matured. Now? FP&A jobs are multiplying, specialization is the name of the game, and LinkedIn is humming with FP&A roles (13th fastest growing job, to be precise). The new expectation isn’t just keeping the books balanced—it’s about foresight, insight, and bringing “financial valuation” to boardrooms where the future is being plotted.

There’s no room for generalists on a battlefield of specialized talent and niche certifications. But, as Brian points out, diverse FP&A skill-sets are stamps in your finance passport, making you a stronger contender for the CFO summit itself.

There’s no room for generalists on a battlefield of specialized talent and niche certifications. But, as Brian points out, diverse FP&A skill-sets are stamps in your finance passport, making you a stronger contender for the CFO summit itself.

Lesson 4: Three Buckets and a Dream

Prashanth gives us a tidy framework: everything you do with analytics should fall into one of three buckets:

1. Growth (Top line)

  • Think customer churn, segmentation, and boosting the customer lifecycle. Your data isn’t just for balancing books—it’s for bringing in more business.

2. Operational Efficiency (Costs)

  • Inventory mania, streamlining SG&A, optimizing processes. Here’s where “doing more with less” becomes a statistical reality..

3. Risk Management

  • Fraud detection, compliance metrics, and looking under the company’s risk-rug. “Analytics is asking powerful questions,” Prashanth reminds us. And if your questions—or projects—don’t fit a bucket? Maybe don’t do them.

Lesson 5: Data Quality—The Great Equalizer

The difference between the finance wizards (leading FP&A teams) and, well, everyone else? Data quality, pure and simple. “It’s not a weekend project,” Brian laughs. Years of scrubbing, defining, and democratizing data are the blueprint. The best start with why: “What decisions do we need to make? What do we need to know to make them?” Only then do they dive into the data. No more meetings wasted on reconciling eight versions of the truth—just one, single source everyone can trust (and even swim in, if you don’t mind the metaphor).

Lesson 6: The Battle of Lagging vs Leading Indicators

Lagging indicators tell you what was—like a financial mirror reflecting the past. Leading indicators make you a finance fortune-teller, guiding future decisions. Effective FP&A teams maximize the predictive, scenario-based, and stochastic side of things using options, scenarios, and—yes—some good old forecasting. Don’t ignore your laggers, but leading indicators are where strategy happens.

Lesson 7: Practical Magic—Analytics Use Cases

Brian brings out the real-world stories, notably:

Insurance company retention bonuses. Instead of bribing every customer with the same bonus, analytics pinpointed who was likely to leave. Target those, save the cash, retain more clients, and make the CFO look like a genius in the next earnings call.

The lesson? Start with a hypothesis, test on historical data, experiment in real-time, and scale up. Analytics isn’t about flashy models—it’s about impactful, measurable results.

Lesson 8: Structured vs Unstructured Data—The Untapped Goldmine

Most companies are sitting on a mountain of unstructured data (text, audio, images) and only using 10-20% of it. Prashanth notes that while structured data lives in neat rows and columns, the real magic comes from extracting value from inspection reports, call center logs, even recorded Zoom meetings. Yes, AI can summarize meetings and generate to-do lists—but beware, as Steve jokes, of letting your AI assistant assign you all the action items!

To get the most out of data (and avoid a robot takeover), use AI as an enhancer, not a replacement. HTIL, “Human in the loop”, is the new acronym: AI + experience = finance superpowers.


Parting Thoughts (and a Teaser)

As Steve summarizes, the best-run finance teams aren’t just using analytics—they’re building a data-first culture, obsessing over KPIs, and continually reinventing themselves. The path isn’t linear, the journey never ends, but the destination (better decisions, more strategic value) is worth the effort.

Don’t miss Part 2, where our data dream team shifts from “Why?” to “How?” and reveals actionable tips for making your own finance org data-fluent—without losing your sanity (or your job).

Craving more? Visit CFO.University for more wisdom and resources—and maybe a few more data-inspired jokes.


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