Improving Spend Visibility with AI-Driven Classification of Commodities

Data is a consistent source of new opportunities and insights. The key to making data actionable is ensuring that businesses have the means to earn a sense of the flood of data at the enterprise level. There are multiple ways to approach this, but one approach many companies are adopting is artificial intelligence (AI) driven commodity classification. It is mainly because it can help improve business spend visibility and management. By enabling you to categorise your raw materials based on their real-world usage and extract actionable insights, AI-driven commodity classification becomes a helpful approach in the procurement system.

Business Spend Visibility and Its Importance

Spend visibility refers to understanding your spending and where it’s going. It allows you to make informed decisions about how much money you should be spending on each project and what type of projects are most valuable for your business. Without spend visibility, companies can’t achieve high levels of success in their day-to-day operations or even long-term goals like growth strategies or acquisitions.

When a company lacks spending visibility, they often don’t know how much money has been spent on specific projects or what those costs were until after the fact—which can lead them to make bad decisions about how best to allocate resources (and waste time).

Role of AI-driven Commodity Classification in Spend Visibility

* Better Supplier Management

AI commodity classification demonstrates your company’s purchase trends, finds possible cost reductions, and aids in compliance. The research gives you the visibility you need to be strategic and have meaningful conversations with your suppliers. Renegotiated contracts with volume discounts and better payment conditions may result from this. In addition, the spend visibility might point out areas for process improvement, such as using favourite providers less frequently or limiting the number of vendors for each category. The 2019 Global Chief Procurement Officer (CPO) Survey reports that 51% of participants currently employ advanced analytics, and 25% have or are testing an AI/cognitive solution to increase visibility.

* Demand-Driven Product Sourcing

An AI-driven commodity classification system helps you to find the best suppliers for your business. It starts with a list of products you want to procure and ends with actionable insights about their cost. Moreover, it reduces waste and risk by helping companies understand which suppliers are truly capable of meeting their needs before they commit large sums of money. By eliminating unqualified prospects from consideration, this approach prevents costly mistakes from happening over time—which means less wasted resources at every stage.

* Reduce Time & Cost

AI-driven commodity classification can help organisations reduce costs and improve supply chain efficiency by reducing the number of errors in purchasing decisions. It also helps companies enhance compliance with their internal policies and customer service experience by reducing time spent on documentation and paperwork. AI-powered classification engines accelerate the procurement process and automatically categorise 60–70% of the first pass data.

* Improve The Accuracy Of Internal Cost Allocations

AI-driven commodity classification enables organisations to gain valuable spend visibility in minutes. This can be done by creating custom rules using the AI engine, which helps you classify your products and services based on their operational characteristics. AI-driven commodity classification also improves internal cost allocations by providing accurate estimates of an item’s depreciation pattern over its lifetime. It enables you to determine how much it costs to operate each piece of equipment or software solution based on its age. It is critical for accurate budgeting because it allows companies to allocate resources more efficiently across their business units or departments to operate optimally.

* Improved Risk Management

Risk management is one of the most critical aspects of business spend visibility. It’s about anticipating and avoiding problems so you can deliver your products on time and within budget. Risk management also ensures that the product is successful, which will lead to improved cash flow for your company as a whole. That is why AI-enabled commodity classification tools analyse different product success rates and companies’ classification. It looks for ways to improve spending visibility across all areas of operations.

To organise commodities, companies use AI technology that accelerates computation and boosts classification precision. NLP recognises all the things and variations of a supplier’s name during normalisation, and combining data from many sources is simpler.

Machine Learning (ML) enables a model to “train” on one data collection and then apply what it has learned to another data set. These trained algorithms are substantially faster at processing and classifying data. By gathering data in real-time and fully understanding it, ML enables businesses to increase their expenditure visibility by up to 95%.

Using machine learning to power spend visibility will also help organisations assign costs more accurately, leading to a more accurate allocation of discretionary expense accounts and better financial reporting.

__Procurement Software For Commodity Classification __

Businesses may use commodity categorisation software with AI capabilities to make more special purchases while lowering the risks associated with doing so. Additionally, commodity categorisation software may be connected with other tools in a business’s spend management arsenal, enhancing automation and visibility across all divisions.

Commodity classification is an essential aspect of procurement solutions. It offers the best approach to help you assess commodity possibilities in terms of quality and price. A good AI-powered procurement software analyses your product information and segregates it into specific categories for customers’ interests.

The Takeaway

Artificial Intelligence can help drive better commodity classifications and improve business spend visibility. AI-driven commodity classification uses NLP to identify the meaning and context of words used to describe the goods. Commodity classification helps with financial record-keeping, high-value material identification, and production planning by providing data on supply chain partners and net present value. In addition, it is based on real-world data that offers powerful insight into commodity movements, quality, and supply chain performance.

Procol is a procurement software that easily adjusts to meet your organisation’s requirements for commodity classification. Schedule a demo to see how this procurement solution can help.