This column by Mark Sue, the lead instructor of our increasingly popular FATE Tech Certification course, borrows from Module 2, Data Analytics and Insights.
Are you getting the most out of your approach to financial analytics? Finance has aimed to elevate its reporting for years, but without modern tools, it’s had one hand tied behind its back. Now, however, the tools have caught up to the science, especially with AI capabilities infiltrating data visualization solutions. Is your organization keeping pace? Here are some questions you should be asking:
Analytics Categories
- Are your analytics descriptive enough? In which areas might your organization be reporting what happened but failing to deliver additional context or actionable insight?
- Are your analytics diagnostic? They might be spotting trends or anomalies, but are you digging into why those trends are occurring?
- Are they predictive? Are you still making significant decisions, such as resource allocation or capital budgeting, using data that is backward-looking?
- Are they prescriptive? Where could your analytics recommend financial actions, like pricing or customer targeting, based on internal trends and external indicators?
Example: A mature manufacturing operation wants to investigate why a cost control or operational efficiency number appears to be off. With diagnostic analytics, it can conduct a root cause analysis of declining gross margins, investigate machine downtime linked to maintenance scheduling and trace labor cost spikes back to sources such as excessive overtime or low productivity.
Designing Dashboards
- Are your dashboards clear and usable? One way to tell is to notice which of your dashboards are routinely misunderstood, ignored or misinterpreted. Look for signs of low end-user engagement or repeated clarification requests from the audience.
- Are you targeting specific audiences? The FP&A team has different expectations and needs from the executive team. FP&A personnel expect deep drill-downs and variance drivers, while executives look for KPI summaries, risk indicators and strategic levers.
Choosing Tools
Modern analytics tools—ranging from BI platforms to AI-enhanced plugins—can reduce manual effort, accelerate planning cycles and elevate the quality of financial decision-making. How do you know when you need to upgrade?
- Are there workflows that feel overly manual, repetitive or spreadsheet-dependent? They are ripe for automation. Those activities could include creating board packets, iterating budgets, modeling cash flow or scenario planning. Exploring the newer AI tools for plugins is a must. Finance does not want to rely on legacy workflows that have high opportunity costs.
- Have you put your new or existing analytics tool through its paces? Here’s a boiled-down version of one way to do it.
Example: Select a high-impact workflow, preferably one that is time-intensive and information-poor, such as the weekly cash flow statement. Then, select the product that best fits the use case. For example, if you want interactive dashboards with advanced drill-down capabilities and real-time analytics, Tableau, Power BI or Qlik might be the optimal choice. To build a simple ROI case, track before-and-after metrics, such as hours saved per month or time reduced by performing manual reconciliation.
Success Indicators
- Is your upgraded approach to analytics making a difference? Look for tangible evidence. Are new analytics insights cited in planning sessions, QBRs or board meetings? The level of cross-functional engagement, such as tool adoption by other departments or requests to enhance dashboards, is another barometer of success.
For a much deeper dive into all of this, see module 2 of the FATE Tech Certification course.
