Three Ways Predictive Technology Improves Tail Spend Management

Three Ways Predictive Technology Improves Tail Spend Management

When it comes to procurement, the little things count. Small supplier relationships that tend to sit outside the strategic focus of an organization—the tail spend of procurement—may seem insignificant, but altogether, they can comprise an unwieldy group that outnumbers core vendors and cuts into profit margins. Fortunately, procurement teams can utilize predictive technologies that turn data into actionable insights for sourcing and managing tail-end vendors.

Globally, only 3% of chief procurement officers have fully deployed predictive/advanced analytics, according to a 2018 Deloitte survey. However, 63% are either scaling, piloting or considering adding predictive/advanced analytics. As more organizations add predictive technologies, they can tackle the multi-dimensional challenge of tail spend management in the following ways:

1) Optimize costs
Predictive technologies enable procurement teams to optimize costs across both new and existing suppliers. For example, conducting a spend analysis allows companies to segment their current spend into areas such as category, volume and supplier to benchmark costs and gain full visibility into their spend. Predictive tools can then turn that analysis into recommendations for reducing costs, such as by identifying categories that seem to be growing quicker than usual.

This type of insight can provide an early warning to procurement teams that they might lack sufficient oversight in certain categories, resulting in unnecessary costs. Furthermore, predictive technologies can identify patterns such as potential price increases. This insight allows procurement teams to then get a head start on renegotiating contracts with existing suppliers or sourcing new suppliers at more competitive costs.

2) Gain efficiency
In addition to improving costs, spend analysis can help procurement teams identify issues that lead to new vendor searches. From there, technologies such as machine learning algorithms can help procurement professionals efficiently find the best product or service for their needs.

Rather than having to manually search for suppliers, predictive tools can offer purchasing recommendations to improve sourcing efficiency. Research from consultancy Capgemini also notes how predictive days payable outstanding (DPO) analytics can help accounts payable (AP) teams “better forecast cashflow and to plan working capital requirements accordingly.”

3) Manage risk
Lastly, predictive technologies can provide key risk indicators that help procurement and AP teams get ahead of potential problems. For example, research from consultancy A.T. Kearny notes that AI within predictive monitoring tools can automatically identify issues such as a supplier being involved in a bribery scandal. If so, “the system can automati­cally score the initial risk, monitor it, adjust the risk score as more information comes in, and pull up all contracts and spend associated with that supplier so that the company can make decisions should the scandal grow.”

Overall, predictive technologies help companies gain better insight into their tail spend management, thereby turning a challenging area into one ripe for savings, efficiency and oversight. To learn more about how your business can gain full visibility into tail spend, save costs and reduce risks, schedule a demo with GoProcure today. You can also read more about how our platform improves the full procurement lifecycle.