In today’s volatile economy, companies must keep on developing new offerings, optimizing processes and investing in employees. To achieve these objectives, cash is king. Yet, proactive cash flow management can be a struggle. Could new technology help?

The versatile nature of cash flow

The challenge of effective cash flow management is faced by organizations of different maturity and in different performance contexts – both in turbulent times and in periods of financial well-being. This is driven by multiple factors, amongst which:

  • It is not always obvious where ultimate responsibility lies. Many components contribute to cash flow, and they often fall in different functional domains, which in turn increases the complexity of responsibility and ownership. Thus, Sales and Receivables terms are managed by Sales teams, Payment terms are managed by Procurement, Inventory levels are managed by Supply Chain teams – while the overall cash flow outcomes are often perceived as a Finance and Treasury issue.
  • Overall cash flow numbers are typically pulled together by Finance teams who often have a lack of visibility on the operational drivers behind the cash flow outcomes, and hence are not well positioned to act upon the results.
  • A lack of integrated data flow that would provide visibility on the end-to-end cash conversion cycle.
  • A lack of clear guidelines and incentives policies across the organization on making decisions with the right cash flow impact in mind.

All of the above make it difficult enough to get a transparent picture of working capital performance and cash flow bottlenecks. The challenge is amplified by the fact that the expectations of Finance teams are constantly growing. In its role as Value Architect, Finance is now expected to not only provide full visibility on past performance, but also steer more strategic data-driven decisions about the future. It is therefore crucial that Finance can create a sufficiently accurate view on future cash flows.

In its role as Value Architect, it is crucial that Finance can create a sufficiently accurate view on future cash flows.

Where does cash flow forecasting start? 

Let’s first take a look at different activities that lead to the creation of a cash flow forecast. They can be grouped into three blocks: 

1. Gathering input data for the cash flow forecasting process 

Input data are generated as part of different business processes – like open customer orders with expected delivery dates coming from Sales or expected payments to suppliers coming from Sourcing and Procurement. These data are typically reported on a periodic basis in the form of predefined Key Performance Indicators (KPIs) and used by Finance teams in the next steps. Unsurprisingly, the quality and timeliness of these data are dependent on the complexity and efficiency of the underlying business processes, the number of organizational units involved and the alignment of data definitions across them, and the maturity of information systems used for capturing and reporting on these KPIs.

2. Interpreting the inputs and preparing an integrated cash flow forecast

Aggregating and consolidating incoming data is not the most difficult task, as long as data definitions are aligned, standardized process and output templates are used, and the technology is in place to channel data towards an integrated outcome. 

3. Optimizing the forecast and triggering actions to close the gaps

This is the most important step and the ultimate reason why companies strive for accurate cash flow projection: to identify in advance where possible gaps may arise and actions that will improve the outlook. Yet not every organization manages to get this right. All too often, there is not enough time left for this step because the previous two took too long. As a result, remedial actions are initiated too late to have a real impact on business performance. 

Many companies face a number of common pitfalls throughout this process: disparate, non-standardized data; a lack of supporting technology resulting in time-consuming data crunching and reconciliations; no link made between financial outcomes and the operational drivers behind them, making it impossible to conclude what needs to change in order to optimize the outcomes; and finally, the absence of a cash-oriented mindset. Does this sound familiar? 

Now imagine if: 

  • The forecast is prepared based on available operational drivers (e.g. logged customer orders), agreed contractual terms of payments, known probability of late payments by specific customers, known percentage of revenue leakage due to cancelled or non-fulfilled orders, forecasted stock levels based on planned deliveries, etc.
  • The consolidated picture of the cash flow forecast is created automatically by combining all data inputs and refreshed real time once the changes in the underlying data occur, providing full transparency to decision-makers.
  • The risks and opportunities within the cash flow forecast are automatically flagged, triggering management attention to anomalies and proposing actions that target cash flow optimization.

Some companies are already putting these practices in place. Clearly the change will not happen overnight, and companies still need to work on all aspects of the process to ensure it yields tangible improvements. It starts with establishing the necessary fundamentals: 

  • Harmonized Data: A harmonized definition and interpretation of KPIs across business divisions and information systems is key.
  • Governance: Clear policies, guidelines, and processes to address exceptions help to steer the process in a way that is aligned with cash flow management objectives.
  • Discipline: Monitoring policy adherence and nurturing data-driven decision-making at all levels of the organization.
  • Cash-oriented mindset: Aligned with strategic objectives, the culture of cash-oriented decision-making should be embedded in all relevant processes, from target setting and business reviews, to workforce training and personnel incentives schemes.

The optimization path paved by analytics

Leveraging advanced analytics techniques, companies can go much further and unlock powerful levers to optimize cash performance. Examples of working capital optimization enabled by analytics include:

  • Cash collections: By analyzing the cash conversion cycle at a granular level, companies are optimizing their revenue cycle and cash collection policies and establishing a more customized approach towards specific groups of customers. Furthermore, analysis reveals the bottlenecks in the process – such as activities that take the longest lead time or generate the most errors/biggest volume of re-work – and as a result, highlights process automation opportunities to reduce time from invoicing to cash.
  • Cash disbursements: Clustering vendors to apply optimized payment terms, as well as trade-offs between payment terms and early payment discounts to enable optimization of the net cash impact.
  • Inventory management: By analyzing required inventory levels (raw materials, work in progress, finished goods), and by modelling stock-keeping unit (SKU) level parameters (e.g. lead times, safety stocks, minimum order quantities, replenishment rates, etc.) companies can optimize processes and avoid unnecessary up stocking.

Discover how a leading pediatric hospital improved its accounts receivable and cash management processes, and read more about how the latest technologies are helping to drive cash flow impact

More than just cash flow 

Besides optimizing free cash flow and freeing up low-cost cash for future investment opportunities, companies investing in their working capital management process typically benefit from additional outcomes: 

  • Reduced revenue leakage, thus increased sales
  • Reduced obsolete inventory levels
  • Increased payment terms compliance
  • Healthier balance sheet (optimized liquidity)
  • Increased visibility on profitability at a granular level
  • Improved monitoring and real-time decision making

What can your organization already do to start moving towards better working capital management?
Feel free to get in touch to discuss. 

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