Transitioning from Spend Analysis to Spend Monitoring

laptop showing an spend analysis dashboard

Organizations have traditionally relied on Spend Analysis to discover cases of spend leakage or non-compliance in procurement processes. However, research shows even best-in-class companies lose 6.2% of their annual revenue on average due to contract value leakage. The risk of lost revenue is even greater for non-leading companies, for which the average loss is 12.4%. And that is just one cause for spend leakage. Traditional Spend Analysis is largely a massive offline exercise that is resource-costly and fails to catch things like price variances, discount opportunities, process delays, non-compliant transactions in time to prevent leakages. Given the fact that buyers are mushrooming across an enterprise and not all expenses flow through a single system, the problems are bound to increase. Therefore, it is prudent to think beyond Spend Analysis and move into the realm of Spend Monitoring across systems so that the procurement function can act as a purchasing advisor and intervene only on a need basis. Here’s more on transitioning from spend analysis to spend monitoring.

Below are three main challenges in procurement Spend Analysis today, and how organizations can overcome them by extending it to intelligent Spend Monitoring.

Spend Analysis – Three challenges: Quality, Frequency, and Scope

Quality – Enterprises find many ways to optimize spending, but they keep running into the same problems of leakage and non-compliance again and again. The reason is that the prevalent style of analysis reveals helpful insights, but they ultimately stop short, failing to offer any suggestions about how to prevent sub-optimal spending in the future. The analysis restricts itself to scrutinizing performance but stops short of scrutinizing behavior or causality. As a result, enterprises can often identify opportunities for savings but have no way of operationalizing them at scale, rendering their strategies moot.

For example, fulfilment delays that hurt production are inevitable. But it can be difficult to pinpoint exactly why those fulfilment delays occurred because there are so many factors that could contribute to a delay. Manual analysis of the entire spectrum of production data across various influential factors is simply too much for most enterprises to handle, merely based on analysis volume and time needed to identify specific causes of overspending.

To compound the issue of spend analysis quality, enterprises are realizing the need to increase the frequency of spend analysis as well. Today, all spend analysis is performed periodically: either once a month, once a quarter, or in some cases once a year. The responsibility and strategy of spend analysis within an organization varies on the enterprise’s structure – some have analytics teams that analyze all transactions, while some do internal quality assurance checks on a select sample of transactions. Regardless of how organizations go about spend analysis, it is a massive undertaking that eats up resources, including time and money.

In addition, periodic spend analysis is retrospective, and while it can be used to tweak spend policies for future exchanges nothing can be done to reverse the overspending that has already occurred. Enterprises must adopt a continuous spend analysis strategy that comprehensively screens 100% of the company’s transactions in near real-time, without necessitating a significant increase in time and monetary expenses. This became especially critical when the pandemic caused massive supply chain delays and many businesses had to find new suppliers that could meet order deadlines. This rapid change in sourcing and procurement has driven enterprises to increase the frequency of spend analysis to ensure they are always getting the most bang for their buck. Unfortunately, this is incredibly challenging to sustain at scale.

Lastly, taking analysis quality and frequency improvements into consideration, enterprises must realize that insights generated from spend analysis are just that … insights. To fully close the loop on spend analysis, enterprises must extend the scope of the solution to include clear recommendations at a transaction level and build the ability to automatically trigger prescriptive actions to remedy the issue.

Spend Monitoring – An extension to Spend Analysis to address these challenges.

Given the advances in technology, it is possible to address all these challenges in interesting ways.

To improve the quality of analysis, organizations should build an ability to explore its procurement behaviour through different lenses. This analysis could be done on purchases done over a 6–12-month duration offline but with the intent of analyzing behavior rather than just performance. For example, one should analyze historical purchases and mine patterns that explain repeated cases of delays in approving, releasing, or fulfilling purchase orders. One should mine patterns that explain repeated cases of non-compliance to procurement policy. These patterns could reveal specific conditions that aggravate these issues. Business analysts could then validate these patterns and earmark specific ones worth monitoring on a continual basis to get an early warning indicator for issues.

To improve the frequency of analysis, organizations should build an ability to monitor live purchases daily using controls. Each control should be a very specific and configurable business check that all transactions are subjected to before they are cleared for further processing. Using controls, organizations can continuously screen purchase orders to detect and flag maverick orders, split orders, duplicate orders, non-compliant orders, purchases with high-risk suppliers, predicted fulfilment delays etc. Likewise, there could be a separate set of controls to continuously screen invoices to detect and flag duplicate invoices, discount opportunities, overdue invoices, predicted payment delays, 3-way mismatches, wrong tagging, non-compliant invoices etc. Controls could be based on rules, models or patterns that have been observed and earmarked for monitoring. These controls should run 24×7 and flag transactions that need human attention due to some impending issue. This would provide a crucial window of opportunity to intercept anomalous transactions to prevent or contain any damage.

To improve the outcome of analysis, organizations should also build an ability to intercept anomalous transactions rapidly. Along with every insight provided, there should be a very clear recommendation on what to do and an ability to trigger a relevant action to correct or prevent the problem. For example, a recommendation for a predicted delay could be to send a proactive recommendation to the supplier with an ability to send out an email or, a recommendation for a suspected duplicate invoice could be to put a hold on payment unless the matter is investigated by a human with an ability to put a block on payment processing.

Final thoughts

Life for procurement professionals is changing every day. The rapid transition to purely digital because of the pandemic has expedited digital transformation timelines and made existing challenges even more complex – especially for stakeholders along the supply chain that needed to quickly expand their supplier network amid global shortages. This has resulted in increased price fluctuations and a more volatile market, creating extensive obstacles for procurement teams and businesses during an already turbulent time.

Organizations that want to stay abreast of supply chain upsets and reap the most value for procurement spending must leverage intelligent analytics and take a continuous spend monitoring route beyond periodic spend analysis if they are to out-perform their competition.


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