A data-driven approach to improving net working capital

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For many companies across industries, the COVID-19 pandemic has created a sudden need for cash and has highlighted the significant value that can be gained by optimizing operations for cash generation. As outlined in a previous article, one of the largest opportunities to generate cash is to focus on net working capital. Besides building resilience, managing cash properly allows organizations to finance growth (both organic and inorganic), pay for holistic transformation efforts, and improve capital-return ratios.

While the potential value from improving net working capital is significant, sustainable change is hard. Performance is the product of people across the business who make thousands of individual decisions on a daily basis: the purchaser who agrees to nonstandard terms, the inventory manager who decides to place a larger order than required to avoid stockouts, or the account manager who is asked by the finance team to follow up on an overdue invoice but delays outreach to avoid damaging a long-standing relationship.

To truly improve net working capital, organizations must provide direction to all individuals to embed the right mindsets and decision-making processes. A simple top-down policy will not do the trick, as it does not enable the much-needed cross-functional collaboration or address mindsets and behaviors. In addition, such a policy doesn’t account for the granular complexity of individual payments, customers, stock-keeping units (SKUs), and suppliers that ultimately determine the company’s net working capital. Taking a bottom-up, data-driven approach is a prerequisite to fully unlock the potential, define specific steps that can improve performance, and create an insight-focused cash culture.

Three elements of a data-driven approach

An important step toward improving the performance of net working capital is to use data analytics. To lay the foundation for this capability, organizations should focus on three areas:

Set up your data infrastructure

Most organizations have one or more enterprise-resource-planning (ERP) systems deployed to store the details of orders, invoices, payments, and SKU volumes, among other information. Often, however, multiple independent systems have been set up throughout the company, primarily to track past transactions for a specific part of the business or function. As a starting point to the analytics journey, data must be consolidated manually. This endeavor can be painful: it’s a slow, labor-intensive, one-off effort that is prone to human error. Because of differences in data quality and coverage, the analyses resulting from this effort are usually outdated and rarely paint the full picture.

Companies that take analytics seriously set up their data infrastructure—and the organization around it—in a way that allows them to easily consolidate the information. A globally advanced industrial player, for example, made the ability to easily consolidate its data infrastructure a priority. This decision was, among others, triggered by the insights that arose from a time-consuming, painful, and manual consolidation exercise. For example, executives learned the company was regularly granting a wide range of commercial terms for the same product to the same customer across different countries. Breaking down those historical data silos is hard but critical to managing net working capital properly and sustainably.

Prioritize the indicators that matter and have them at your fingertips

Providing employees with access to data is a prerequisite, but it’s only the first step. Companies must define clear, granular, and measurable key performance indicators (KPIs) and analyses that governance functions (such as the cash office) monitor regularly to inform their actions. For example, a real-time inventory control tower could highlight potential bottlenecks in the supply chain that could prevent an organization from delivering the promised service to its customers. This function could include the creation and evaluation of different scenarios to help remedy such issues. Identifying measurable and relevant KPIs, such as inventory availability, back orders, and inventory on the SKU level could help organizations identify bottlenecks before they happen.

Move from retrospective reporting to a forward-looking mindset

The true power of data is unlocked when organizations move their thinking beyond score-keeping and toward a forward-looking mindset. Data and analytics can be used to identify potential issues up front and decide on concrete actions. An energy retailer, for example, had poor credit-risk management that resulted in late payments and bad debt. By harnessing the available rich data, executives defined KPIs during the customer journey that enabled them to identify high-risk customers at every step, from acquisition to those that might make late payments. With this customer segmentation, they are now able to take corrective action, such as offering cash-back bonuses or installment-payment schemes, to lower the risk of late (or no) payments.

Key success factors

A data-driven, fact-based approach can help organizations achieve excellence in managing net working capital. To be successful, companies should focus on five factors:

  • Transparency is important for understanding which steps, entities, and individuals can maximize the impact of digital initiatives on net working capital. Since the efficient management of net working capital requires granular and detailed measures, adopting a data-driven, bottom-up perspective is critical.
  • Companies must adopt a long-term perspective. Manually consolidating data is a cumbersome, inefficient, and imprecise effort. Setting up the data infrastructure in a way that allows for easy, real-time, and consolidated access is a critical step.
  • To sustain the change, it’s necessary to distinguish between signal and noise by setting up granular, measurable KPIs that are closely tracked and acted upon swiftly.
  • Carefully analyzing historical data can offer powerful insights on how to manage net working capital by preemptively addressing emerging issues.
  • Data and facts are meaningless without initiatives to promote cross-functional collaboration, create greater awareness of cash, and change the mindsets of individuals who ultimately drive the performance.

With these capabilities and mindsets in place, organizations can quickly implement a transparent, well-coordinated effort to improve net working capital.

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