Conversational Data Intelligence, RPA, digitisation and automated process discovery tools are playing an increasingly important role in intelligent automation. Shared services transformation leaders should explore how they can be used to drive process understanding and straight-through processing.
Key business functions and shared service centres are under increasing pressure. Not only do they have to hit their service targets while finding new cost-out opportunities, they have to do all this under an unprecedented and ever-growing volume of digital communications - emails, service requests and support tickets. To date, many intelligent automation initiatives have failed to make a real impact, with agents trapped in a cycle of falling response times, client frustration and operational slowdown.
When shared services aren’t running efficiently, the whole business suffers. Thankfully there’s an answer, or rather four, that you need to be aware of as you seek to enhance shared service capability through intelligent automation and hyperautomation.
While talk of self-healing bots, autonomous everything and the automated enterprise is everywhere, there are four crucial technologies that are already technically feasible and deployed in live settings. This is important to note for any enterprise making near-term plans. Moon shots are undoubtedly risky and will likely fail to meet expectations. But how do you know which emerging capabilities are worth the investment?
These key technologies will supercharge your automation ROI in 2022 and beyond:
Conversational Data Intelligence
One of the largest challenges facing shared services - on top of ever-growing request volumes and the shift to hybrid working - is the lack of insight into the forces driving these shifts. To plan and resource effectively, it’s vital that shared services and transformation leaders understand which requests are creating the most work, and what the problems are that slow business-critical processes. It’s critical they understand not only how work is getting done, but why workflows are being triggered in the first place. This helps them resolve issues at the source rather than just treating the symptoms periodically.
However, much of this insight is hidden in unstructured communications data - primarily within emails - that can’t be analysed or automated by most traditional intelligent automation tools. Being able to process and understand all this unstructured data at the scale and speed required demands strong natural language processing (NLP) and analytical capabilities, which thankfully can be found in Conversational Data Intelligence tools like Re:infer.
Conversational Data Intelligence platforms combine NLP and machine learning to rapidly train models that can accurately and reliably convert freeform natural language into structured data that’s ready for analysis and automation. Shared services and transformation leaders then have the insight and data they need to scale automation effectively and drive improvements that deliver real ROI. That’s why 67% of intelligent automation leaders say data extraction from email using NLP is a key investment priority.
67% of intelligent automation leaders say data extraction from email using NLP is a key investment priority.
Process Mining & Task Mining
A suite of automated process discovery tools are starting to make waves by helping organisations understand processes at an unprecedented level of detail. Though not purely focused on automation opportunities alone, these technologies will provide insight into process efficiency that’s hard to match.
Process Mining and Task Mining are technology platforms that can enhance process discovery and improvement initiatives. Automated process discovery is like lean on steroids. Using system, click, and user behaviour data, these tools show the reality of processes rather than a picture distorted by the opinions of subject matter experts. This gives you a baseline to understand the work your service agents are completing, while also revealing a pathway for future process improvements and automations.
OCR & IDP
Optical character recognition (OCR) and intelligent document process (IDP) have seen a huge boost in usage thanks to the growing focus of intelligent automation on RPA. Adding document understanding to your shared service capability provides a whole new area of work to be structured, digitised and therefore automated by RPA. If semi-structured documents, such as invoices and application forms are now fair game thanks to OCR and IDP technologies, organisations gain easy access to masses of new structured data sources.
RPA
Intelligent automation makes use of many complementary technologies, one of the most popular and widespread being RPA. Although the core capability of RPA is to mimic human workers and replicate their keystroke activity, it’s far reaching application - from delivering a sales order into your CRM, to processing a customer account amendment or onboarding a new employee - make RPA one of the most useful software technologies available. Pairing RPA with the prior three technologies can supercharge your automation value creation initiatives.
Summary
The technology stack for intelligent automation is evolving rapidly, and it can be difficult to know what emerging technologies to pin your hopes on. These four automation capabilities will help you build the proper foundation to make sure your processes help rather than hinder future business planning. These technologies are already becoming a reality in some leading organisations and will become the norm by 2025. Getting onboard early will accelerate your existing automation efforts and pave the way for a future autonomous enterprise.
