In our previous blogs
(here
and
here)
we discussed how enterprises struggle with obtaining financial insights from ERP systems and how a solid data foundation can enable scalable insights and automation. In this blog, we will explore how visualization can help finance teams become better storytellers and provide clearer insights into business performance.
CFOs are encouraged to become better “storytellers,” by communicating important messages about company performance, strategy, and opportunities in ways that everyone can understand. Finance departments are working to become true partners to the business by providing critical metrics, KPIs, and forecasts to guide decision-making.
With ever-increasing data volumes, financial analysis can be overwhelming, but data visualization simplifies reporting, making it more engaging and actionable, especially from a CFO’s perspective.
As businesses face rapid market changes, traditional ERP systems often lack the agility to provide real-time insights needed for agile decision-making. Companies are adopting cloud-based solutions and advanced analytics, enabling CFOs to consolidate data from multiple sources, gain real-time visibility, and make informed decisions. Data visualization aids Finance teams by making information more accessible, highlighting key trends, and improving decision-making. However, poorly generated data visuals can lead to misinterpretation and, ultimately, poor business results.
So, how can finance professionals make the most of the latest data visualization technology to tell compelling stories and encourage sound, data-driven business decisions?
Know Your Audience and What Matters to Them
The first rule of data visualization is to identify the purpose—what to visualize and who the audience is. It is important to understand:
What kind of business questions do they care about? What decisions are at stake? What metrics distinguish high performance from mediocre results? Which factors most dramatically impact revenue, expenses, and cash flow? What does the executive management team care about, and how can you provide a view of the data that is most meaningful to them?
Some insights may require inclusion of external factors such as competition, inventory levels, or even weather patterns. The goal is to pinpoint audience interest areas and create visualizations that answer their questions in a compelling and simple way.
While building data visualizations, consider the following objectives for each visual:
- Distribution – Show how items are divided. Example: Enterprise profit by business unit.
- Composition – Display data components. Example: Accounts receivables by different regions.
- Relationship – Highlight connections between data points. Example: Cost reduction tied to business value.
- Trend – Show data over a time period. Example: How predictive models help achieve goals.
- Comparison – Compare datasets while avoiding overcomplicating visuals with too many categories.
Selecting the Right Visualization Tools
The right visualization brings data to life, while the wrong one causes confusion. Rather than choosing based on visual appeal, focus on clarity and simplicity. Select charts that present information intuitively and limit the number of visuals to what is necessary.
Choose visuals based on data type:
- Nominal data – Example: Customer name
- Ordinal data – Example: Payment terms
- Numeric data – Example: Sales amount
For example, in our astRai platform, while designing templates for SG&A Analytics dashboards, we applied structured logic to determine which visuals best represented the underlying data and business objective.