1. Don't start with data. Identify high-impact areas and relevant use cases first
Dealing with disparate sources of data in varying formats and structures is challenging. And yet surprisingly, companies are often tempted to start with data analysis without thinking through why they're analyzing the data or identifying potential issues.
As a CFO, begin by pinpointing the areas that will generate more revenue, accelerate cash flow, or improve compliance. Then use this prioritized set of use cases to understand the shortcomings in your company's overall data infrastructure across important dimensions: data sources, quality, storage, availability, and standardization.
One of the world's leading snack-food manufacturers prioritized improving the quality of its sell-side data (customer, product, and price) as the starting point for an analytics initiative. As a result, it improved the overall retailer experience, which increased market share and growth.
CFO advantage: You and your team are in the best position to understand the organization's goals and objectives in-depth. This should prioritize the data scope and the initiatives and investments to make.
2. Maintain high data quality with process discipline
Most successful companies have enterprise-wide MDM structures with robust processes for capturing, maintaining, sharing, and reporting data from across silos. This might sound simple, but it's still startling to see how much value organizations lose when processes aren't aligned or don't have the right controls.
For example, a lack of integrity in basic information can have major consequences. Take supplier payment terms. Discrepancies in payment terms result in suppliers getting paid earlier than contracted, which negatively impacts working capital. And if payments are delayed, that creates a poor experience for suppliers. Also not ideal.
Leading businesses have established advanced organizational structures for data management. For example, a world-leading alcoholic beverages company standardized its data-management processes and created a center of excellence across its regions and business lines, lowering costs by more than one-third.
Securing process discipline through shared service centers (SSCs) or a global business services (GBS) model – together with advanced technologies – also improves cycle time and accuracy and leads to more confident decision-making.
CFO advantage: As a CFO, your team has the advantage of being at the intersection of most enterprise processes. And finance is typically well versed in the use of advanced organizational models with SSC and GBS setups. With this experience in hand and your central role in the business, finance can drive end-to-end process alignment and influence how data should be managed.
3. Implement advanced digital technologies
Better technologies alone cannot drive more effective data management. But the right technologies will unlock smarter processes. Cloud-enabled, off-the-shelf solutions provide critical features, such as interfaces that support data stewardship, built-in workflows, and higher data quality. These technologies also integrate external data – from social media, for example – to gain a complete picture of your customers or suppliers.
The next step is to combine these platforms with technologies such as robotic-process automation (RPA), machine learning (ML), and artificial intelligence (AI). Dynamic workflows will capture business requests and make sure they're processed accurately. Natural language processing will tackle unstructured data – such as emails or audio – and machine learning will handle exceptions, reducing them over time.
CFO advantage: Your finance teams have likely been the biggest adopters of technologies such as RPA, ML, and AI. They can help accelerate the use of digital solutions for data management within finance and beyond by applying their lessons learned and perspectives.
4. Design and build a reliable data lake
Data lakes are key to gaining a real-time, integrated view of your company's data. For example, one of the world's leading healthcare distribution companies is implementing enhanced enterprise reporting, ML-driven forecasting, and scenario modeling, all enabled through its data-engagement platform – or data lake.
The next step is to complement internal data with external data to enhance prediction accuracy in specific use cases, such as identifying payment patterns to improve collections. Expect to make this a regular activity.
CFO advantage: You and your finance team are among the biggest beneficiaries of a data-engagement platform. By reducing dark data in your organization – the data your company generates but fails to use – and adding external data, your finance function will examine scenarios exhaustively, improve planning and forecast accuracy, and enable the business to make better decisions faster.
5. Establish a data-governance board
Data governance delivers data integrity and quality. But not all organizations recognize the role it plays. A data-governance board promotes the value of data at all levels of the enterprise, improving efficiency, lowering business risks, defining rules, and resolving issues from non-compliance.
The board's governance structure often includes an executive steering committee, data governance council, and data stewardship committee. As you create a board, set these objectives:
- Identify stakeholders, establish decision rights, and clarify accountabilities
- Be the formal decision-making body for data standardization
- Define, approve, and monitor policies, standards, and procedures for each data domain, such as customer, supplier, or product
- Follow data standardization and quality best practices
- Formalize processes for creating and promoting data consistency, standardization, reuse, and data exchange
- Provide a centralized mechanism for effectively communicating data-related initiatives
- Act as the liaison between technical and business groups
- Drive the organizational and behavior changes needed for how the business creates and uses data
- Define service-level agreements to guide how the business collects, stores, shares, and reports data accurately
CFO advantage: Alongside CDOs and chief information officers, CFOs are a critical part of the executive steering committee because you have visibility of performance data across the enterprise. You also understand the challenges caused by specific data attributes and the impact they can have on, for example, working capital, which will help the business prioritize where it focuses its investment and action.
Underlying each of these practices is the need to develop digital and data skills to help finance become a better business partner. Identify the skills you and your teams need to adopt and hire. They may include data modelers, data scientists, or visualization experts. A mix of training approaches will also allow you to upskill employees while building a data-driven culture.