Transforming Treasury with the First Principles Thinking 

Why is treasury transformation required?

The ultimate goal of the treasury department is to ensure that there is enough liquidity for managing its day-to-day operations by creating cash forecasts, managing cash flows, managing bank relationships and risks. During turbulent times, their priorities shift towards managing working capital, but most businesses still perform treasury functions the same way. Moreover, the role of treasury is becoming increasingly complex, but the treasury resources are not increasing. Thus they need to transform their existing processes and systems to ensure better liquidity management.

The drivers of treasury transformation are:

• Rapid analysis: It is considered necessary to make timely decisions. But the manual processes and limited resources make it challenging.
• Reporting and regulation: They are crucial for treasury, but the lack of regulatory requirements make treasury prone to loopholes and errors.
• Cyber risks: Data thefts and payment frauds are now prevailing more than ever due to the work-from-home situation. But the lack of visibility into the systems and processes makes it difficult to track and mitigate fraudulent activities.
• Global expansion: The growth of companies leads to bank relationships becoming more complex. The lack of scalable systems makes it challenging to handle multiple banks and transactions.

Cash forecasting helps transform treasury by performing rapid analysis, monitoring regulations, ensuring real-time reporting, proactively managing cyber risks, and handling multiple banks seamlessly.

Use-cases of cash forecasting

Cash forecasting helps treasury in:

• Making confident debt or investment decisions.
• Steering cash to meet quarter-end targets.
• Having accurate cash visibility for the future helps deploy cash more efficiently.

Bottlenecks in cash forecasting

These are the bottlenecks in the four cash forecasting levers that prevent treasurers from meeting their business objectives:

• Approach: The approach leads to a forecast that does not provide granular visibility on cash movements.
• Data Gathering: Manual data gathering from different teams and/or systems is cumbersome and error-prone.
• Modeling: Treasury professionals often lack the required technical expertise to build the best-fit models.
• Variance Analysis: Deviation between forecast and actuals is infrequently or inaccurately calculated. This leads to low confidence in decision-making.

Transforming cash forecasting using the first principles thinking

First Principles Thinking is a basic assumption that cannot be broken down further. It involves deconstruction (breaking down complicated problems into basic elements) and reconstruction (reassembling them to make better decisions, processes, and systems).

Deconstruction in Approach

The problem with the approach is that the forecast does not accurately predict real-time cash movements. The problem can further be broken down into its basic elements such as:

•  Top-down vs. bottom-up
•  Too much data
•  Indirect vs. direct

Reconstructing in Approach

The basic elements of the approach solution are then gathered to identify the current approach to make improvements. The solution is to focus on cash moving through bank accounts at the lowest level.

Deconstruction in Data Gathering

When we deconstruct data gathering, the problem is that the manual data gathering from various teams and/or systems is cumbersome and error-prone. The problem can further be broken down into its elements:

• Not timely
• Inaccurate
• Subjective

Reconstruction in Data Gathering

The basic elements of the problems can be reassembled to generate the solution, which is to obtain the data directly from the source, rather than manually gathering data from multiple teams.

Deconstruction in Modeling

Oftentimes, the treasury department lacks the technical expertise to build the right model for different cash flow categories. The problem can be further divided into basic elements such as:

• Expertise
• Tools
• Bandwidth

Reconstruction in Modeling

The solution for improving modeling is to use AI models to create accurate forecasts for complex cash flow categories such as A/R and A/P and use heuristic models for static categories such as taxes and payroll.

Deconstruction in Variance analysis

Variance analysis is difficult to perform for each entity level over multiple durations for multiple cash flow categories. The basic elements of the problem are:

• Entities
• Duration
• Category

Reconstruction in Variance analysis

The problem in variance analysis can be addressed using automated tools that capture multiple forecast iterations at a granular level.

Skills required for treasury transformation

37% of treasury professionals stated that they lack time to perform their day-to-day responsibilities, 35% of them feel that treasury is understaffed, and 63% feel that their top operational challenges are manual processes and lack of investment or technology in treasury operations. Treasury professionals need to shift their roles from performing administrative tasks to performing value-added tasks. Treasurers need a creative mindset nowadays instead of a transaction-oriented traditional mindset to stay on top of the curve.

Ways to transform

• Identifying the core purpose of the treasury department and how it aligns with business goals.
• Identifying the core issues by applying the first principle thinking.
• Learning about emerging technologies and how they might solve these problems.
• Developing new skill sets to drive transformation.