5 Ways a CPO Can Create Organizational Value with AI
The current worldwide lockdown is presenting new organizational pressures and challenges to business continuity in the face of uncertain global supply chain impact across logistics, materials, labor, sourcing, and other core areas of procurement.
CPOs must address unprecedented disruption, future-ready their procurement strategy and generate business resiliency. Leveraging Ai is a powerful way to create organizational-wide value and promote an agile, efficient and responsive supply chain that’s fully operational—regardless of circumstance.
- Resolve unmanaged tail spend
- Enhance post-contract compliance and analysis
- Technology partner who delivers strategic value
- Mitigate economic, environmental and trade risk
- Category management
Unmanaged small and infrequent purchases, about 20% of annual spend, yet comprises up to 80% of completed business transactions, have resulted in an untapped source of potential incremental saving opportunities. Yet many organizations let “the tail,” a fragmented and complex mixture of suppliers, transactions and product categories, slip through the analysis and management cracks, simply accepting it as an inevitable monetary loss. This has gone on for to long.
Ai-led procurement provides new solutions to address the untapped cost savings and mitigate transactional and operational risks hidden within tail spend. This area of spend is ripe for concealed fraud and misclassified purchasing, and can benefit from intelligent automation to provide the control and data visibility organizations need to drastically reduce or eliminate tail expenditures, creating robust spend awareness, purchasing and decision making.
Critical to ensuring success with such an endeavor are high-degrees of classification, for example with ElectrifAi’s ProcurementAi which can classify 97% or higher using Ai, and the automatic generation of insights around tail spend. ProcurementAi includes over 50 different insights on cost savings and risk reduction which automatically help organizations address their problems with spend in the tail.
Procurement contracts, characterized by complex, inaccessible contract language and clauses and differing renegotiation terms and renewal dates, are nearly impossible to interpret, monitor, review and act upon with manual or traditional solutions, creating a compliance and regulatory gray zone of potential hidden risk and liability. More so, contract insights go unconnected to the larger scope of enterprise information and decision making.
Disparate contract data is ideal for the pattern recognition capabilities of ML, which extracts, classifies and clarifies contract information to improve contract performance through greater visibility, accuracy and responsiveness, resulting in proactive contract risk management and stronger compliance. A critical nuance is making sure contract data is actually connected to spend data so organizations can quickly understand the big picture.
A significant percentage of organizations who have implemented enterprise-level digital technologies to address procurement transformation across contract management, spend analysis and supply chain risk and compliance have been unsatisfied with the outcome.
CPOs who embrace digital procurement transformation should assess what an Ai technology partner can offer to improve the procurement model, unravel procurement complexity and deliver strategic value. Evaluating buy-side specifications, including budget and current infrastructure, as well as sell-side specifications like solution design and framework and required organizational skills, is key to solving procurement pain points and driving positive change.
A great KPI to look at when evaluating Ai technologies is “First Pass Accuracy” - essentially a measurement of how well the Ai performs the first time it looks at your spend and contract data. As a reference, at ElectrifAi we generally see 73% to 78% first-pass accuracy (industry leading).
When inefficiently managed, environmental, economic, sourcing and trade risks can create a pandora’s box of potential consequences and repercussions that run the gamut of everything from negative perception of the organization to major supply chain disruption.
The best offense is a good defense, and in procurement, transitioning from a reactive to proactive approach to procurement risk through the right Ai procurement tools can help organizations understand key risk drivers, mitigate risk and account for changing supply chain dynamics. Logistics scenarios, probability simulations and deep-dive data exploration that brings insights to the surface and produces detailed visibility are critical to aggressive Ai-fueled risk mitigation.
There is a powerful list of 3rd party data integrations that we often recommend to clients engaging on a better understanding of these risks. At ElectrifAi, we connect this data right to the consolidated supplier list – insights and recommendations are generated from a global, single point-of-view on each company and all of its subsidiaries.
Category management is a top priority for today’s procurement leaders, and an area where Ai has proven to be a catalyst in deepening supplier relationships and value and achieving greater security and visibility.
As more categories come into play, CPOs need the big picture view of central procurement function and bring challenging spend categories beneath a single umbrella with Ai tools that seamlessly drill down into spend data to identify granular opportunities within the supply chain.
Accelerate the Ai procurement journey
Procurement leadership is changing. CPOs must wield the strategic advantage of Ai generated insights to embrace the new value-driven procurement culture and optimize their procurement strategy amidst disruption, uncertainty and beyond.
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