#DigitalTransformation – Next stop…the future

Procurement organizations are on the brink of change – and the future is bright. In the coming years, they will automate most transactional activities, freeing up resources to focus on strategic efforts that drive value to the business. As a result, the cost to run the function will decrease, while the actual value derived from it will grow.

This change will enable procurement to rethink activities, resource allocation, and skill sets and operate in more efficient, collaborative and data-driven ways. A solid 84% of procurement organizations believe that digital transformation will fundamentally change the way their services are delivered over the next three to five years. Procurement professionals will more closely align with business teams, and their work will draw heavily on analytical insights empowered by rich data across the internal and external landscape. Moreover, traditional procurement skills will give way to newer skills in data science and analytics, risk management, and collaboration.

Going Digital

According to a recent survey of over 600 companies, 52 percent of the average procurement organization’s time is spent on transactional activities such as managing purchasing orders (POs), sourcing events and contracts, reconciling invoices and tracking payments.

In digitizing such tasks and infusing them with robust machine learning algorithms, the entire source-to-settle process can be redefined. Organizations can perform transactional activities at much greater speed, lower cost, and higher accuracy. More importantly, they can make smarter, more informed decisions that beyond savings and efficiencies, deliver broad business value.

SAP Ariba and IBM are uniquely positioned to deliver these intelligent technologies and help companies accelerate their procurement transformations.

Getting Smarter

In pairing SAP Ariba and SAP Leonardo with IBM’s cognitive capabilities, Procurement Services and Global Business Services, companies can begin their journey with an advantageous fast start. What does the journey look like?

Every company begins at a different point, and the steps and timing vary. But all start with a focus on process automation, transformation and strategic sourcing underpinned by data enrichment and advanced cognitive spend analysis to drive early value. 

This first step drives about 10 percent to 15 percent savings on average. Next up? Bring in intelligent technologies that enable companies to dissect the data and make more informed decisions and potentially drive another five percent to 15 percent of spend savings.

A digital assistant combined with machine learning, for instance, can be used to run better sourcing events by providing assistance in defining the right Request for Proposal type, identifying the right suppliers to participate based on commodity category, region or industry and delivering intelligence on market signals and/or pricing pressures to optimize results.

Or to create smarter, more comprehensive contracts by identifying relevant terms and conditions matched to legal library and taxonomy, unearthing similar contract terms for a specific commodity by industry and/or region based on benchmarking data and suggesting optimal prices to target based on expected volume and contractual discounts.

Add in the efficiency and effectiveness that digitization brings to the process along with control and compliance, and companies can ensure these savings are realized downstream.

Cognitive isn’t just a buzz word. In embracing these emerging technologies and choosing the right partners to deliver them, procurement can fuel a more efficient, intelligent way of operating that truly changes the game.  

Marcell Vollmer is chief digital officer of SAP Ariba and the former chief procurement officer of SAP.

SAP is the market leader in business applications; and SAP Ariba is the world’s largest business network, linking together buyers and suppliers from more than 3 million companies in 190 countries.

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#DigitalTransformation #future #Procurement #digital #technology #automation #ArtificialIntelligence #AI #MachineLearning #ML