There’s been a fair amount of talk of Hyperautomation recently. I thought I’d pen my thoughts on this topic, and how it relates to ERP and the Finance Back office in the first of these blog articles.
Now, Automation has been around for decades; people have been trying to gain efficiencies and cost savings by automating the mundane, repetitive tasks and processes through innovative and effective tools and techniques.
As we moved into this decade, there is a new dimension to where automation can take us. Leveraging artificial intelligence (AI) and machine learning (ML), automation can now be enhanced to take on processes that require contextual decision making and augment the human interface.
This is the advent of what is known as Hyperautomation.
The research firm Gartner says, “As no single tool can replace humans, hyperautomation today involves a combination of tools, including robotic process automation (RPA), intelligent business management software (iBPMS) and AI, with a goal of increasingly AI-driven decision making.”
The net result is a significantly more sophisticated automation framework, one that involves discovery and analysis, language-centric process construction, and ongoing measurement, monitoring, and refinement of the business processes.
In fact,Hyperautomation and its potential impact in companies is so profound that Gartner identified it as the #1 Top Trend to watch for in 2020. Take a look at this short video clip to see what David W. Cearley, Distinguished Analyst at Gartner says about Hyperautomation as he introduces the top trends for 2020.
In ERP, the opportunity to drive more efficiencies using Automation has been actively driven by CFOs and Finance executives for several years. However, the dawn of Hyperautomation opens up some very interesting perspectives on how to approach Automation in the back office.
Let’s take an example of a typical AR/Collections process. Normally, you’d have Receivables clerks or Collections agents that would leverage existing tools, software, and telephone-based communications. The goal is to automate the process of outreach to clients (or their Payables teams) and remind them of upcoming payment obligations. As the situation necessitates, we remind them of delays and late as part of the collections process.
With Hyperautomation technologies, the Collections process can be dramatically improved. Here are some specific examples:
- Before even a single outreach is made, AI proactively informs the Collections agent or AR Clerk of which customers are likely to be late in making payments, or likely to request payment extensions.
- Next, with Recommendation Analytics and Machine Learning, the Collections agent is provided a set of incentives, in order to encourage the customer make payments on time. The best recommendation analytics can also predict which customers are likely to accept these incentives.
- The dramatic improvements in Natural Language Processing (NLP) can also streamline the Collections process. This includes initiating outreach, intercepting requests from the client (such as payment extensions or late fee waivers), and providing contextual decisions (such as approvals for fee waivers or split payments).
As you can see, with advances in AI, ML, and NLP, Hyperautomation is quickly becoming a reality. Here at Auditoria, we are helping companies every day to re-imagine the back office and every business process—AP, AR, Audit, Tax, and Treasury—can benefit from intelligently digitizing these functions.
Reach out to us, and let us share some ideas on how we can help you with your Hyperautomation and digital transformation initiatives in your back office.