Gartner introduced the concept of Hyperautomation in 2019 as the key trend for 2020. What is it? Well, it’s simply the combination of different technologies to carry out the end-to-end automation of an organization’s processes by integrating technologies such as robotic process automation (RPA), intelligent business process management (IBPM), machine learning, and artificial intelligence (AI).
At first glance, it makes a great deal of sense. Many organizations have incurred massive amounts of technical debt over the years as IT responded to the needs of individual departments instead of automating value creating workflows. Then, departments would hoard data thereby creating data silos. These difficult to bridge data stovepipes have created additional obstacles. No wonder that digital transformation remains challenging for many companies as such large programs are prone to failure and businesses struggle to achieve planned outcomes.
While the integration of digital tools is attractive in theory, there’s some skepticism. Is this just more techie double speak or marketing spin? After all, the key analyst firms can’t even decide what to call it. Gartner calls the integrated deployment of digital tools hyperautomation. Forrester calls it digital process automation (DPA). IDC calls the very same thing – intelligent process automation (IPA). Quite a few vendors have hopped on the hyperautomation band wagon. Appian – a leading low-code BPM vendor, promotes hyperautomation as a “more muscular version of automation.” UiPath – a leading robotic process automation (RPA) vendor, claims that hyperautomation starts with RPA – which some vendors of intelligent business process management suites (iBPMS) and process mining might disagree with.
Digital transformation is far more complex than simple incremental improvement. For example, if a company claims to be doing hyperautomation but it is still modeling small business processes within departmental boundaries – then that’s ballyhoo. If a company claims to be doing hyperautomation, but is still tinkering with small proof of concept RPA projects – then that’s ballyhoo or hoopla. Success with digital is more difficult and costly than advertised. Take RPA for example. It has been reported that only around 13% of RPA projects actually advance beyond the pilot stage, and the majority of companies deploying RPA have fewer than 10 bots in production. In spite of the rhetoric around “hyperautomation” and “digital process automation (DPA)” – unfortunately many RPA vendors fail to integrate their offerings with process mining vendors and machine learning vendors. That’s just more ballyhoo.
So, what’s best practice when it comes to leveraging hyperautomation for digital transformation? It starts with mindset. The automation of a company’s work needs to be viewed from an end-to-end process focus. This calls for a big picture approach to tackling large processes such as “order to delivery,” “idea to launch,” “record to report,” and “request to receipt.” That can best be accomplished by using tools such as an iBPMS or process mining to create the end to end context needed to identify the best places to apply tools such as RPA. Then, groups of people from the departments touched by the process can work together to identify the best ways to deploy the set of digital technologies. Engaging front line workers and managers is critical. Remember, “Processes don’t do work – people do!”
It’s equally important to recall that a successful digital initiative has to start with the customer – and hence the need to merge the voice of the customer research with customer journey mapping. That’s sometimes easier said than done – as the teams responsible for customer experience deploy a different methodology than process improvement professionals and typically sit elsewhere in the organization. So, the effective deployment of hyperautomation doesn’t just call for collaboration by vendors – it also requires collaboration across the practice areas of process management, customer experience and IT professionals.
Hyperautomation is a genuine “best practice” in digital transformation when a company can claim the following:
- Leadership has defined and articulated a clear and concise strategy for digital transformation.
- A big picture approach underlies efforts to understanding the current state of the company’s large, end to end business processes.
- There is a conscious effort to boost collaboration across departments, regions, vendors, and teams.
- Modeling small business processes within departmental boundaries and the deployment of individual digital tools within departmental boundaries is actively discouraged.
- Data sharing across multiple apps is actively encouraged.
- The overall ambition for digital transformation includes stretch goals for both customer experience and employee experience.
- Plans for streamlining activities and improving productivity are front and center and include the ability to scale the deployment of digital tools.
Launching hyperautomation for success with digital transformation calls for an unprecedented level of collaboration between IT professionals, IT vendors, and process practitioners. Process professionals have the methods and skills to model end to end business processes and along with an “outside-in” focus this can form the foundation for reimagining the business and connecting with customers and employees in new ways. Process professionals have learned the importance of cross functional collaboration and they have first-hand experience dealing with employees’ fears around job losses. These insights can form the much needed foundation for collaboration with customer experience teams, the IT group, and technology vendors.
Otherwise, call it what you will – hyperautomation, DPA or IPA – it’s probably just ballyhoo.
EDITORS NOTE: We have created an organization level assessment to assist our member companies in their digital transformation efforts. We hope that you will find this assessment helpful.
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