1. Integrate data from all key sources
Data integration must underpin your enterprise's financial transformation. After all, you can't maximize the value of analytics if you don't have all of your financial data in one place.
Without integration, you have silos. And silos impede visibility. This is true whether the silos are large-scale—e.g., departments isolating company-relevant financial data from other teams—or small-scale, like teams using independent applications to manage expenses instead of apps integrated with the finance team's tools. The resulting lack of visibility can cause serious problems across the enterprise.
Integrating data is a key first step toward achieving financial visibility. All systems that manage financial data—Salesforce, SAP, and so on—must be integrated seamlessly, connected through application program interfaces (APIs) and overseen by a versatile analytics solution. It’s crucial to choose a platform that can automatically integrate structured, unstructured, and semi-structured data across your entire ecosystem, whether it's on-premises, hybrid cloud, multi-cloud, a data warehouse, or a data lake.
2. Embrace automation wherever possible
Manually wrangling data to be integrated is neither time- nor resource-efficient. Unfortunately, stakeholders who use financial data for analytics typically spend at least 80% of their time on data acquisition. In such situations, it takes hours to locate and verify all of the data needed for periodic reporting.
Although about 34% of finance data tasks are automated, experts believe anywhere from 60% to 80% of those responsibilities could be automated through digital transformation in financial services. Your team should strive to reach that range by adopting data management tools that facilitate automation through leading-edge artificial intelligence (AI) and machine learning (ML) technologies. For example, scalable automated auditing processes can quickly find patterns and anomalies across millions of transactions. This increases efficiency and boosts financial visibility.
3. Establish a holistic view of your organization
Some key performance indicators (KPIs), like debt-to-income ratio, remain important no matter what else is going on with a business. However, the metrics that best gauge a company's financial status can change from moment to moment. For example, real-time insight into working capital and liquidity ratio can be most valuable while working out a merger. The next day, operating cash flow might be much more important.
For these and other critical financial performance metrics, summary-level data management and analytics tools don't provide the level of detail that's necessary to closely and holistically examine them. Your team needs a platform that expands analytics capabilities and provides deeper, more actionable insights into factors contributing directly and indirectly to the organization’s costs and profits.
Financial analytics should cut across different departments, customer demographics and segmentations, and product and channel categories. Ideally, your team will get granular enough to examine the profitability of proposed initiatives based not only on the potential impact for major target audiences, but also individual customers. Establishing this holistic, multi-dimensional view also ensures every stakeholder's bigger picture of the business is consistently accurate.
4. Adopt and leverage predictive analytics and prescriptive analytics
Financial data alone can't tell your team and other stakeholders everything they need to know to solve business problems. And while diagnostic and descriptive analytics aren't valueless, they're referred to as "backwards reporting" for a reason.
Implementing predictive and prescriptive analytics—and realizing their full potential—is one of the most important benefits of financial transformation.
The data management solutions your team uses must be capable of analyzing historical data and projecting potential outcomes of fiscal decisions—accelerated or delayed product launches, major investments, budget cuts, and so on. According to Deloitte, using predictive analytics for the finance function allows analysts to narrow or expand their focus as needed, while reducing the risk of human error and bias.
Prescriptive analytics that can recommend potential courses of action are just as important to help stakeholders across the organization confidently make more informed decisions. This enables comprehensive scenario planning to help reduce the likelihood of risks.
5. Leverage financial data strategically
Finance teams shouldn't see themselves strictly as overseers of cost. You and your colleagues can—and should—play a significant role in shaping the strategic direction of the company.
By efficiently integrating, processing, analyzing, and visualizing critical financial data through a lens of long-term strategy, your team can establish itself as a trusted advisor to business units ranging from product development to marketing. This strategic perspective will be essential for keeping an eye on ultimate goals as competition intensifies, new channels emerge, and customer priorities continually shift.
Teradata empowers financial visibility
Vantage, Teradata's connected multi-cloud platform for enterprise analytics, is the ideal foundation for establishing financial visibility. The solution's versatility, integration capabilities, and powerful analytics engines allow for comprehensive diagnostic, predictive, and prescriptive analysis, uncovering insights that have major value to the bottom line.
To learn more, take a look at our financial visibility case studies, which include successes in the banking, retail, and consumer packaged goods industries.
See more financial visibility case studies
