Will Machine Learning Save Procurement Millions a Year?

Posted: 06/01/2018 - 03:36

When it comes to automating processes, procurement organizations are no slouches. Long ago, chief procurement officers automated administration, payroll processing, material-resource needs calculation, invoice generation and material flow tracking. The function has, for the most part, eliminated redundant work to dedicate more time toward more strategic activity and transitioned the collaboration to business networks.

Yet, exception handling seems to be at an all-time high as companies try to get a better handle on their suppliers and partners to gain a competitive edge. And procurement professionals are now stretched to their limit, bombarded with a steady stream of requests – each one requiring analysis of massive volumes of documents. 

Organizations, on average, waste between 3 and 4 percent of overall external spend on unnecessary transaction costs, excessive inefficiency and regulatory noncompliance. For an organization with an annual procurement spend of $2 billion, cutting off such leakages can add $70 million a year back to the bottom line. But there’s good news. “Thinking” algorithms – known as machine learning – can speed up the process of exception handling with significant payback. And they literally do all the thinking – and work – for you.

Machine learning: Overcoming common barriers to full automation

Unlike Robotic Process Automation (RPA) and preliminary use cases for Artificial Intelligence (AI)Machine Learning (ML) handles activities that call for complex rules and pattern recognition. By demonstrating a basic level of human judgment, machine learning can, for example, assign transactions to formal spend categories and subcategories. This critical first step in uncovering sourcing opportunities can transition from a traditionally time-consuming, manual task to a real-time, automatic response.

And easier categorization is just the beginning. Machine learning can further automate procurement and enhance its strategic reputation across five major aspects of the function:

  • Supplier management. Procurement organizations want to make sure that their suppliers are financially viable and stable. Procurement can apply machine learning to determine the most competitive rate to negotiate, and also discover the best contract terms that will help the partnership become more successful through as-promised delivery and on-time payment. 
  • Capabilities matching. All buyers want their suppliers to fully meet current and expected needs and deliver exceptional serviceBut it can be tough to separate marketing hype from reality. By scanning the industry for new competencies and aligning them with business requirements through machine learning, procurement can develop processes to continuously test the ability of new and existing partnerships.
  • Efficiency monitoring. Machine learning can efficiently track and monitor the efficiency of every entity of the supply chain and rate suppliers based on their performance, enabling procurement to hold vendors accountable while helping to ensure that operations run at peak standards.
  • Compliance enforcement. Machine learning can pick out hidden patterns that indicate whether a supplier is not meeting business and regulatory requirements and can do so faster and more efficiently than any human. With the data on hand, the procurement function can engage in difficult discussions with greater ease and in a manner that is both productive and decisive. 
  • Value creation. Every area of the company demands quality and maximum value to the bottom line. Using machine learning, the procurement function can deliver it, automating balanced scorecarding to track the efficiency of the supplier relationship and the effectiveness of a purchased good or service on all transactions. Plus, machine learning can empower the team to develop rules that permit flexibility and responsiveness while controlling risk. 

While technology will undoubtedly continue to evolve, and deliver more value and opportunity, it's impossible to ignore machine learning as a transformational stepping stone toward providing quick value that benefits the entire company and its customers. And procurement leaders that adopt and embed this next-generation form of artificial intelligence in their processes can lead the way and position the function as a powerhouse of strategic influence on business success.

 

 

 

Region: 

About The Author

Marcell Vollmer's picture

Marcell Vollmer is Chief Digital Officer for SAP Ariba and is responsible for defining and driving Digital Transformation for customers of SAP Ariba globally. A thought leader in procurement, supply chain, finance and shared services, Marcell’s expertise lies in defining digital transformation strategy and to make Run Simple a reality for global customers and consumers by delivering high cost and additionalprocurement savings. Previously, he was Chief Operating Officer for SAP Ariba where he successfully developed and led global business development, procurement, go to market, sales operations, and enablement. And prior to that Marcell was Chief Procurement Officer of SAP and was responsible for the reorganization and process optimization for and end-to-end source-to-settle organization. Since joining SAP in 2005 he has held various leadership roles involving restructuring, improving project efficiency and execution of global programs in finance, procurement, sales, human resources and post-merger integrations.