Hyper-automation: A Game Changer that is Here to Stay
Hyperautomation is no longer a trend or a business aspiration. In a fast evolving and increasingly integrated digital world, hyperautomation is inevitable.
Market pressures to improve efficiencies, agility and to orchestrate disparate systems intelligently are pushing organizations to adopt hyperautomation.
The technology has been termed “the next frontier for organizations globally” by Deloitte. Moore’s law explained how the complexity of electronic circuits had doubled in a given period of time, and automation technologies will also grow exponentially.
What is Hyperautomation?
Hyperautomation (also known as “extreme automation (EA)” or “Intelligent Process Automation” (IPA)) is a fundamental re-imagination of how a company works across the entire enterprise in a digital world.
Gartner defines hyperautomation as a
“business driven, disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible.”
Deloitte breaks the definition into its components:
Hyperautomation refers to a combination of complementary sets of tools that can integrate functional and process silos to automate and augment business processes. EA brings together several components of process automation, integrating tools and technologies that amplify the overall ability to automate business processes.
The difference between automation and hyperautomation is the tools used to deliver. Robotic Process Automation (RPA) is typically deployed to automate simpler and linear processes. The automation of complex operations with higher variability (e.g. customer interactions) poses challenges for most RPA software.
When RPA is combined with AI, and in some cases NLP, complex processes can be integrated and scaled allowing the RPA to unlock more efficiencies and improvements.
The trend however is still nascent. Pioneering companies will need to stay focused and consistent. Companies which have already embarked on automation will need to continue to invest to augment the level of automation already achieved.
The Investment Rational
The worldwide market for technology that enables extreme automation will reach $596.6 billion in 2022, according to Gartner. This is up from $481.6 billion in 2020 and a projected $532.4 billion this year.
Most non-IT verticals have seen increased adoption of hyperautomation solutions. A survey by Bain found that more than 50% increase in automation is expected in healthcare, life sciences and manufacturing verticals.
Security is the top automation funding priority for 36% of IT decision makers according to Red Hat’s Annual Global Tech Outlook.
Geographically, the Asia Pacific region is expected to have the highest growth (22.8% CAGR 2022–28) due to its growing technology adoption across multiple verticals and particularly manufacturing. China ($2,438 million market value by 2028), Japan (22% CAGR for forecast period) and India (23.5% CAGR for forecast period) are among the major countries driving hyperautomation growth.
Competition, cost pressure, ramping cyber security threats and the increased complexity from fragmented systems are factors that will drive demand from medium and large enterprises for many years to come.
Large Scale Use Cases Across Industries
1. Manufacturing: When Machines Talk
Industrial automation has been around for many years and continues to be in the main agenda for manufacturers.
Hyperautomation can be deployed to pull together disparate streams of automation creating an overarching structure that connects all the tools and processes and that can integrate AI/ML for further gains and improvements.
A digital twin can be created to inform EA improvements. A digital twin is a recreation of a part of or the entire manufacturing operation. By using real-world data it can be used to inform decision making, scheduling and improvement opportunities.
2. Hypercool Retail Purchases
With hyperautomation retailers can collect customer data across all channels to examine shifts and preferences and apply automated AI rules to personalize reminders, emails and ads.
The integrated data can also be analyzed with custom AI/ML/NLP for demand forecasting, coping with supply chain disruptions and improving inventory management.
Combining RPA and AI to analyze real time purchases by product, channel, competitor pricing, social media sentiment and geographical trends can provide real advantages to dynamic pricing.
The same data can be used to modify existing products, create new products, modify distribution channels and optimize marketing spend.
Hyperautomation can also be deployed to mechanize and improve payments, order management, transportation, warehousing, procurement, supply chain design, supplier risk and inventory management.
3. AI-powered Virtual Construction
The safety controls of construction sites demand tight controls, regular monitoring, spot safety checks and reporting to decrease the costly insurance premiums associated with the industry.
Camera systems powered with AI-systems can detect safety violations, or risks before they become accidents.
The same technology can be used to track progress, timelines, inventory management and adherence to architecture plans.
4. Powering an Efficient Healthcare System
The healthcare industry in the US is overcoming years of operating with legacy systems and manual processes. Recent research found that between26% and 39% of healthcare workers are entering data manually. Further, 32% to 40% believe this is partly due to challenges in locating the data they need, when they need it.
Smart patient services can be created combining AI and process automation bots that can manage patient service tasks, demand cycles and staff. Hyperautomation can be used to interact with patients assisting humans, enable self-service, schedule appointments, manage prescriptions and collect data to manage demand and improve the patient experience.
NLP and ML can also address the large inefficiencies and costs of claims processing and payments between providers and insurers. The technology can be used to detect and prevent code errors associated with procedures, integrate claims into a single EOB, minimize human errors from claims processing and integrate payments with claims receivables.
Compliance with regulations such as HIPPA can be improved using RPA bots and AI models to analyze system logs, test processes and controls and prevent incidents before they happen through alerts.
Hyperautomation can also accelerate drug discovery through deep algorithms to select and evaluate the performance of clinical trials and improve selection of drug candidates for specific diseases.
5. Hyperadoption in Financial Services
RPA is already prevalent among most financial institutions. According to a study by AI Multiple, banking will be one of the top industries spending on artificial intelligence by 2024.
Banks are already embracing automation across payments processing, back office processing, AP/AR automation, credit scoring and risk management among other processes.
However, systems remain fragmented across business units and functions. The ability to bring together process-related data into one place where intelligent automation technologies can be applied is the key to unlocking the next wave of efficiencies for banks.
Combining RPA with ML across critical processes like Know Your Compliance (KYC) and Anti-money Laundering (AML) and onboarding workflows can minimize errors, human intervention and paperwork allowing teams to focus on mission critical tasks.
RBS, HSBC, Wells Fargo and CBA are banks using Real Time Decisioning for customer interactions informing the next best action based on the latest customer interaction. Pega has developed a customer service application with all available connections (IVRs, chats, messaging, emails, etc.) that allows customers to be served from a few microjourneys that are either prefabricated or customized for each client.
Lending processes continue to be slow due to multiple credit checks, compliance, risk and back office processing. RPA combined with AI could compare and validate data from multiple sources reducing timelines. Real time data and historical data can be used to inform and expedite credit decisions.
Deep Dive: Discovery saves 800k Hours through Extreme Automation
Discovery, a leading US digital bank and payments company, focused on a mission to ensure manual processes were understood, optimized, automated or eliminated. Its primary aim was to extend automation to every possible process within the business.
“We used to do things in silos; now we’re pushing Extreme Automation as a whole and driving towards the same mission.” Joe Mills, Discovery Financial Services
According to Red Hat, Discovery ‘s EA program spanned across 3 pillars:
DevOps
Process automation
Automation community of practice — a guild of experts to diagnose and address automation problems
Discovery utilized the Red Hat Ansible Automation Platform, an enterprise framework for building and operating IT automation at scale, from hybrid cloud to the edge. Edge computing moves processing closer to data sources allowing organizations to deploy latency-sensitive applications, gather data from IoT devices, and create resilient sites that can operate even when a connection to the datacenter or cloud is lost.
Benefits
800,000 annualized hours given back through EA
Increased use case ROI by applying repeatable solutions across the organisation
Enabled staff to focus on higher value work
6. Cybersecurity: hyperautomation through SOAR
The introduction of multiple SaaS solutions, a push towards remote work, IoT and multi-cloud architectures has dramatically improved the productivity of most businesses. However it has also introduced major cyber security concerns.
Security Orchestration Automation and Response (SOAR) is the cornerstone of hyperautomation. It relieves the burden on security departments by automating repetitive tasks and behaviors and it has become a proven way for enterprises to improve business and operational metrics.
According to RedHat, network security is the highest priority for automation funding at 38%. Vulnerability management funding has increased in importance with funding at 27%.
Conclusion
Hyperautomation is a game changer that will become a factor of strategic survival for enterprises.
The execution can be costly and the time to realise the benefits can be lengthy. Solution providers that design solutions that are easy to implement, SOAR ready, replicable and scalable are positioned to benefit from enormous growth particularly if targeting the APAC market.
“It’s not the strongest of the species that survives nor the most intelligent that survives it’s the one that is most adaptable to change”.