DIGI’TAIL’ SPEND MANAGEMENT – A COGNITIVE SOLUTION TO AN OLD CONUNDRUM

By – Aravind Ns

(Product Specialist – ignio Cognitive Procurement | Digitate)

The new normal has brought a paradigm shift in business priorities, the biggest one being to reduce cost. Enterprises are paying a premium to find a reliable and continuous supply of goods or services, thus putting more pressure on margins. While battling these pressures and risks, procurement personnel can put money back on the table by addressing the tail spend.

Why Digital in Tail Spend?

Tail spend or long tail spend is typically 20% of the spend value that accounts for 80% of the purchases and supplier base. At an organization level, the tail spend could run high (in millions) and have a combination of the following characteristics (or) issues:

  • Unmanaged spend, not strategically managed by the organization
  • Irregular way of dealing with suppliers (as opposed to contracts, catalogs, P-cards or RFX)
  • One-time high price purchases (or) recurring low-value purchases
  • Maverick spend or spot buys (non-preferred vendors and buying channels)
  • Unclassified or misclassified
  • Improper KPIs to track their quality and performance
  • Compliance, legal and financial risks

While most enterprises are familiar with the listed issues within their businesses, addressing the tail spend is laborious and time-consuming. As organizations are grappling to manage tail spend, identifying saving potential could be daunting, especially when there are thousands of transactions that make even the scroll bar in the spreadsheets look tiny. Conventionally, the focus is on strategic direct spend and very little attention is given to the tail spend due to the poor reward ratio to the quantum of work. However, with the advent of digital technologies, it can deliver measurable value in tail spend through better visibility, prices and control of compliance risks.

According to BCG, firms that use digital solutions to manage tail spend can cut their annual expenditures by 5% to 10% on an average—a significant amount, especially for global companies with total expenditures in billions.

Frontier of Spend Visibility

The Achilles heel to bringing tail spend visibility is having proper data classification. Any procurement personnel would know that tail spend data lacks classification and harmonization. While a majority of the organizations have the top 80% of the spend classified, it is time to take over the herculean task of classifying the rest. Erstwhile the classification is unwieldy and manual. With Artificial Intelligence (AI) and Machine Learning (ML), spend can be auto classified based on the UNSPSC (United Nations Standard Products and Services Code) or custom standards with minimal human effort. Minimal human effort is required during the initial cleansing and classification to aid the learning of AI/ML, which also improves the accuracy/errors over time. AI/ML can detect similar or minor variations in material descriptions making it easy to remove or consolidate duplicate items, giving better spend transparency. After the initial classification of existing tail spend data, the new addition of data will be incremental and an instant activity.

Cost Savings to Cost Avoidance

With tail spend classified, bringing visibility is a matter of finding the right analytical tools that can show the distribution of suppliers and spend across items and categories. However, the buck doesn’t stop there. What you do with the visibility determines the potential of savings you can bring. Traditionally, this is an uphill climb given the thousands of low-value transactions that must be analyzed across multiple source systems. The power of AI/ML can open opportunities highlighting value saving avenues in terms of:

  • Flagging cases of higher price purchases
  • Alternatives for existing suppliers
  • Supplier base consolidation to get better price points
  • Scope for making high-value tail item purchases a catalog or contract buy

Cost avoidance in simple terms means ‘A penny saved is a penny earned’. The procurement department has created a cost-conscious culture to not just cash in on opportunities to save money but also avoid unnecessary spend as well. Using AI/ML you can find unusual patterns that cause process inefficiencies, non-compliance and fraud. These patterns if not addressed, impacts productivity and hence consumes more effort and time which further translates as a cost to the department. In extreme cases, this could also pose a financial and business risk.

Reactive to Proactive

In retrospective, humans and machines are equally wise to point out what went wrong. So, why invest in an AI/ML or advanced analytics product? The answer is, you can proactively prevent it from happening. All tail spend purchase transactions could be monitored 24×7 in real-time to proactively avoid purchases at higher prices, flag out unusual transactions and avoid any delays within the P2P cycle. Organizations have slowly started looking at tail spend as a huge area of opportunity to invest in digital technologies. According to Research and markets, the spend analytics software market is expected to grow at 18.2% CAGR between 2021 to 2026. Thus, it’s a no brainer that organizations are very keen at reducing undesired spending, making AI/ML a must-have capability in all organizations

Digi’tail’ Spend Management with ignio

At Digitate, we have developed ignio Cognitive Procurement, an AI-based continuous spend monitoring solution that screens purchase transactions in real-time to proactively avoid spend leakages and mines behavioral patterns driving process inefficiencies and noncompliance. ignio customers have realized millions in savings in their tail spends. To know how they did it and how you can to, reach out to us.

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