From Augmented Procurement to Autonomous Procurement
From augmented procurement to autonomous procurement, in this article, we’ll take a brief journey of the evolution of procurement.
Autonomous Procurement: The Beginning
In the history of Artificial Intelligence (AI), the year 2014 has been a turning point. That year in May, Google revealed a new prototype of the driverless car. In June, a chatbot named Eugene Goostman beat the “Turing Test” heralding a new era for using human-like bots for automation.
Incidentally, 2014 was also a key year for Zycus. Having launched our Procure-to-Pay platform in 2012, we were at the threshold of realizing the immense potential A.I will have for procurement. Looking back, it was one of the first steps that took us to where we are now, and towards Merlin. But first, let’s go back in time…
Tactical vs. Strategic
For the past 15 years, procurement has always been juggling between quality and quantity. On the one hand, they had to deliver strategic inputs involving time, analytics, and intelligent negotiation. On the other, the requirement was to review and process thousands of transactions and records like a machine.
The Fine Balance
To strike that fine balance, the demand for a digital transformation grew stronger. Companies started moving away from ERPs to dedicated source-to-pay solution suites. Few of these solutions, or rather the best of them, also came with inbuilt A.I capabilities.
First-generation AI-based procurement solutions
The first generation AI-based procurement solutions used essential machine learning technologies and used probabilistic models to aid spend classification and contract or supplier analytics. Such technologies require the right data sources to learn from and be effective. Hence, it is natural that only established procurement solution providers can provide meaningful AI solutions to their customers.
For instance, Zycus was the pioneer in AI-based spend analytics using Auto-Class, a patented AI automation platform. Auto-Class can work on a massive volume of unstructured spend data (PO/invoices) and automatically classify and assign the correct category codes to each line item using the knowledge gathered from over a trillion dollars’ worth of processed documents.
Second-generation AI-based procurement solutions
The second-generation AI-based procurement solutions evolved more recently as more and more companies started automating their core processes providing a more developed ‘base’ framework for AI to grow. The focus of AI also shifted partially from a back-end computation platform to ‘smart insights’ helping users with actionable insights. This provided what we called Augmented Procurement experience by leveraging technology to increase procurement control.
This stage also saw AI use cases expanding across the entire gamut of source-to-pay processes. Some instances of 2nd generation AI solutions at Zycus focused on improving turn-around times.
Automated three-way matching of PO–Invoice–GR, converting supplier pdf invoices to eInvoices, and tagging Non-PO invoices to existing contracts were some examples that stood out in terms of their extensive adoption.
Other instances of 2nd generation AI solutions at Zycus were more strategic
For example, Guided Buying routed users to preferred buying channels (favorite suppliers, contracts, catalogs, etc.), even for free text searches. Spend monitoring and mining looked to provide detailed insights on savings opportunities hidden within detailed spend data based on experience. Smart Assist in contract and supplier management helped in adhering to compliance and timelines with timely insights to the right stakeholders.
This was also the time when Natural Language Processing (NLP) became a part of procurement applications with conversation platforms like Zycus Ask-Anything encouraging human-like conversation with machines. The synergy between solutions and their users were changing and changing fast.
Today, we are in the first quarter of 2019
The topics for most procurement conferences held in 2018 focused on AI, Intelligent Augmentation (IA), etc., as the path forward for procurement. But as per Gartner, “Within the market for procurement, the current penetration of the addressable market for AI is estimated to be within the range of 1% to 5%.”*
Why is there such a massive gap between expectations and reality for procurement ambitions?
There are two reasons which we at Zycus identified, and the insight is the driving force behind the third-generation AI-based procurement solutions designed by Zycus that will result in transformational change.
First of all, AI/RPA (Robotic Process Automation) based processes are being created in bits and pieces. They provide a partial advantage but not the power of an integrated AI/RPA process across the solution suite. Also, the development does not cater to the needs of individual organizations despite customer-specific learnings.
Secondly, AI solutions are still used as a computational advantage. As a result, they are dependent on the end user’s readiness to leverage them. They are not ‘autonomous,’ i.e., not able to take actions on their own.
Zycus Merlin A.I. StudioTM aims to address the above challenges by providing a comprehensive bot platform where customers can create, train, and launch numerous bots across the source-to-pay suite.
The bot platform comes pre-configured with numerous intelligent functions (think of them as botlets) which can be used to configure any bot specific to customer’s needs resulting in a one-of-its-kind configurable AI platform.
Each bot leverages cutting-edge technologies like AI, ML (Machine Learning), RPA, etc. as per the requirement for its particular task. With appropriate training, the bots can be launched to perform basic, routine functions without human intervention, thereby paving the way for autonomous procurement.
Finally, we at Zycus have taken the first step towards a new era of AI-powered autonomous procurement processes.
To know more about our journey, click here.
* Source: The Impact of Artificial Intelligence on Procurement Software Applications, Gartner, 2018