Spend Analytics

How is AI expanding the capabilities of spend analytics?

Consider these questions –

• Which suppliers is your company spending the most on?
• What are your product and supplier categories?
• Can you measure the performance of your suppliers based on specific KPIs?

These are just some of the issues business leaders struggle with. While they may have a broad picture of the company’s spend, a process-driven mechanism is missing. As a result, companies fail to control maverick spend, lose potential business opportunities, and rely too much on a few suppliers raising their risk exposure.

To deal with such issues, business owners invest in spend analytics with an AI-based approach. As a result, the spend analytics market is set to reach a CAGR of 17.9% by 2027.

This article will explain how you can use AI in spend analytics to tighten the strings around maverick spending, identify cost-saving opportunities, simplify budgeting and negotiations, and manage suppliers better.

Spend analytics with AI gives you the edge

A bad spend analysis can do more harm than good for your business. To make spend analytics truly a part of the strategic function, businesses need to augment it with AI. Compiling and cleaning the existing spend data for insights is a resource-intensive job.

Investing in software is not enough

The software will do no good if the underlying data is low quality. Sub-standard data is incomplete, inaccurate, inconsistent, duplicate, and even invalid.

Data categorisation and quality tend to deplete over time if you do not have a system to regularly check and update them. Incorrect categorisation and generic taxonomies in the existing spend analytics systems impede new business opportunities.

A customised approach to AI-based spend analytics

There is no one-size-fits-all approach to AI-based spend analytics, and off-the-shelf products often do not deliver the maximum value. Each business has different KPIs depending on the procurement maturity and required granularity of the data.

The best choice is to invest in a solution that leverages and customises an existing AI-based spend analytics solution for your business.

How does AI deliver more value in spend analytics?

AI-based spend analytics uses machine learning and text matching to manage each step of the journey. These steps include data collection, cleansing, and categorisation. Custom data sets based on the business’s maturity stage feed and train the algorithm for error-free categorisation.

Opportunity assessment tools deliver high-quality reports that help you identify cost-saving opportunities at the subcategory level. Using this information, you can re-negotiate and re-structure contracts, consolidate the suppliers and the spending, and even cut ties, if necessary, with non-productive suppliers.

AI-based spend analytics for better risk management

Expand the scope of your AI-based spend analytics solution to assess the risk. Traditional spend analytics platforms offer cleansed and accurate procurement and supplier information. AI can enhance the value of this data by integrating it with financial risk scores, corporate social responsibility, sustainability, and other key identifiers.

Using this information, your business can proactively assess risks associated with your suppliers, such as –

• Environmentally harmful production processes that could bring legal penalties
• Supplier based in a politically unstable country
• Impending supplier bankruptcy that could disrupt your business

Machine learning and artificial intelligence can detect these patterns and warning signals early on, leading to lower risk. Using predictive analytics, you can also better manage the price and margin with your suppliers.

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How can Infosys BPM help overcome the spend analytics challenges?

ProcureEdge, an AI-powered spend intelligence platform by Infosys BPM, gives a business enhanced visibility across business units, categories, and products. Rather than replacing your existing procurement and spend analytics management system, you can enhance AI-enabled data management, opportunity identification, and spend classification capabilities.

Read more about how you can use AI-based spend analysis services in your business.