• Written by Azhar Aliyar, Director

A spreadsheet used by the finance team to track costs and identify areas for reduction often reveals a disconnect between the numbers and the reality on the ground, where money actually goes and which reductions survive contact with production.

The unit cost and total cost of an AI workflow

The difference between unit cost and total cost of an AI workflow is crucial in cost optimisation for finance. Unit cost refers to the cost of a single instance of an AI workflow, whereas total cost takes into account the overall cost of the workflow, including the cost of the AI model, data preparation, and deployment. Most people get wrong that unit cost is the only factor to consider, but they are wrong because total cost has a significant impact on the overall financial performance of the organisation.

A finance manager checking the costs of an AI workflow may find that the unit cost is low, but the total cost is high due to the large number of instances run. This is where cost optimisation for finance comes in, helping to identify areas where costs can be reduced without compromising the effectiveness of the AI workflow.

Caching, batching, and model routing as the three real levers

Caching, batching, and model routing are the three real levers that can be used to reduce the cost of an AI workflow. Caching involves storing the results of expensive computations so that they can be reused instead of recalculated. Batching involves grouping multiple instances of an AI workflow together to reduce the overhead of deployment. Model routing involves directing instances of an AI workflow to the most cost-effective model available.

For example, a shift supervisor checks the maintenance log and finds that a particular AI workflow is being run multiple times a day. By implementing caching, the supervisor can reduce the number of times the workflow is run, resulting in significant cost savings. Similarly, batching and model routing can be used to further reduce costs.

Finance data dependence

The finance data that cost optimisation for finance depends on includes general ledger, budget, open commitments, and purchase orders, as well as receivables and terms. This data is used to identify areas where costs can be reduced and to track the effectiveness of cost reduction measures. The general ledger provides a detailed record of all financial transactions, while the budget provides a plan for how funds will be allocated.

Open commitments and purchase orders provide insight into future expenditures, while receivables and terms provide information on the organisation's cash flow. By analysing this data, a finance manager can identify areas where costs can be reduced and implement measures to achieve those reductions.

For more information on how to use this data to inform cost optimisation decisions, visit our finance page.

Changes to variance explanations and budgets

Cost optimisation for finance changes the way variance explanations are done, as it provides a more accurate picture of where costs are going. Variance explanations that arrive after the period are no longer useful, as cost optimisation for finance provides real-time insights into costs. Budgets that look healthy while overcommitted are also a thing of the past, as cost optimisation for finance helps to identify areas where costs can be reduced.

A category manager comparing two suppliers may find that one supplier is more expensive than the other, but that the more expensive supplier offers better terms. By taking into account the terms offered by each supplier, the category manager can make a more informed decision about which supplier to use.

Measurement

Cost optimisation for finance is measured using variance to budget, commitment coverage, and days sales outstanding. Variance to budget measures the difference between actual costs and budgeted costs, while commitment coverage measures the extent to which commitments are covered by available funds. Days sales outstanding measures the average number of days it takes to collect payment from customers.

These metrics provide a comprehensive picture of the organisation's financial performance and help to identify areas where costs can be reduced. By tracking these metrics, a finance manager can see the impact of cost optimisation for finance and make adjustments as needed.

Limitations

Cost optimisation for finance is not a silver bullet, and there are times when it is the wrong choice. It does not replace the need for careful financial planning and management, and it is not a substitute for sound financial decision-making. If you are unsure about whether cost optimisation for finance is right for your organisation, contact us to discuss your options.