• Written by Sonali Subhadarsini, Product Manager

On a typical Monday morning, a finance manager in a manufacturing organisation is likely to be waiting for a report from the accounting team, detailing the previous week's expenses, revenue, and production costs, in order to assess the company's financial performance and make informed decisions about budget allocations and resource utilisation.

The finance questions that currently wait on a report

The finance team in a manufacturing organisation often relies on periodic reports to answer critical questions about the company's financial health, such as what the current cash flow situation is, what the total cost of production was for the previous quarter, and how the actual expenses compare to the budgeted amounts, which can be a time-consuming and laborious process, particularly when the reports are not automated or are based on manual data entry.

These questions are not just relevant to the finance team, but also to other stakeholders, such as the production manager, who needs to know if there are sufficient funds to purchase raw materials, or the sales team, who need to understand the pricing strategy and its impact on revenue, and the ability to quickly and easily access this information can have a significant impact on the organisation's ability to respond to changing market conditions and make timely decisions.

The shift supervisor, for example, may need to know the current inventory levels and the value of goods in progress, in order to plan the production schedule and allocate resources effectively, and the category manager may need to compare the prices of different suppliers and assess the total cost of ownership, in order to make informed purchasing decisions.

The data behind them: general ledger, budget, open commitments and purchase orders, receivables and terms

The data that underlies these finance questions is typically stored in a combination of systems, including the general ledger, budgeting software, and enterprise resource planning (ERP) systems, which can make it difficult to access and analyse, particularly for non-financial stakeholders, and the ability to integrate this data and provide a unified view can be a significant challenge.

The general ledger, for example, contains the detailed financial transactions, such as invoices, payments, and journal entries, while the budgeting software provides the planned financial performance, and the ERP system contains information about production schedules, inventory levels, and supply chain activities, and the ability to link these systems and provide a comprehensive view of the organisation's financial performance can be a key factor in improving decision-making and reducing costs.

Sector constraints: changeover losses and multi-plant comparability

Manufacturing organisations face unique challenges, such as changeover losses, which occur when production is halted to switch from one product to another, and multi-plant comparability, which can be difficult due to differences in production processes, equipment, and local market conditions, and the ability to understand and manage these constraints can be critical to improving financial performance.

The category manager, for example, may need to compare the production costs of different plants, in order to identify opportunities for cost reduction and process improvement, and the shift supervisor may need to understand the impact of changeover losses on production schedules and resource allocation, in order to optimise the production process and minimise downtime.

What improvement looks like: variance to budget, commitment coverage, days sales outstanding

Improving financial performance in a manufacturing organisation can involve reducing variance to budget, increasing commitment coverage, and minimising days sales outstanding, which can be achieved by providing stakeholders with timely and accurate information about financial performance, and enabling them to make data-driven decisions, and the ability to access this information quickly and easily can be a key factor in driving improvement.

For example, the finance manager can use financial analytics to identify areas where actual expenses are exceeding budgeted amounts, and work with the production manager to implement cost-saving measures, such as reducing energy consumption or improving production efficiency, and the category manager can use data about supplier performance and pricing to negotiate better deals and improve commitment coverage.

What this does not do, or when it is the wrong choice

While AI for finance in manufacturing can provide significant benefits, such as improved decision-making and reduced costs, it is not a replacement for human judgement and expertise, and it is not suitable for all organisations or situations, particularly those with complex or unique financial requirements, and the ability to understand the limitations and potential pitfalls of this technology can be critical to ensuring its effective use.

Organisations that are considering implementing AI for finance in manufacturing should carefully evaluate their needs and requirements, and consider factors such as data quality, system integration, and stakeholder engagement, in order to ensure that the technology is used effectively and provides the expected benefits, and for more information about how to get started, please contact us.