HYPER-AUTOMATION describes a step change in productivity and output achieved by applying modern digital technologies to supercharge business processes. The term has found favor in 2020 to describe enterprise initiatives to harness the best available methods and tools to automate by harvesting all the capabilities of modern digital technologies. But does it make sense for your enterprise?

What’s different about hyper-automation? While hyper-automation as a term focuses on the OUTCOME of technology interventions, from a practical perspective, the biggest change in how organizations go about harnessing technology comes down to a couple of factors:

LOW-CODE and NOCODE applications development and deployment ecosystems—provided by enterprise vendors like Salesforce.com, Appian, Encanvas, Mendix, ServiceNow and OutSystems—offer a route to accessing hyper-automation digital technologies in a holistic and affordable way. These are cloud deployed platforms that equip organizations with tooling to create and manage federated data structures upon which they can architect their applications on-demand. Deployment typically takes a few clicks which means the complexities of back-office IT are removed from the ideation process.

It’s best to imagine these new platforms as a new layer of interoperability and applications engineering that sits across existing enterprise Systems of Record and repositories. As the terms LOW-CODE and NO-CODE suggest, these platforms dramatically reduce or remove the need to code or script when authoring, integrating and deploying applications. That said, these are still enterprise platforms and therefore satisfy the necessary data security, scalability and extensibility aspirations of large organizations.

At one time, any IT systems requirement automatically got forwarded to the IT team or data processing department. In the last decade, it’s been popular to introduce a two-speed IT approach by having Development Operations (‘DevOps’) teams serve up digital transformations through SCRUM-based agile development initiatives. Often, these teams are divorced from the mainstream IT department charged with keeping the lights on.

In 2020, we’re just beginning a new major change in the way applications developments and process changes are handled in organizations with the introduction of FUSION TEAMS armed with the new LOW-CODE and NO-CODE applications development ecosystems.

FUSION TEAMS are a connecting team made up of Business Stakeholders (such as Line-of-Business project managers, users, etc.) and Business Analysts equipped with the skills to employ hyper-automation technologies served through a unifying LOW-CODE or NO-CODE applications development and deployment ecosystem.

According to Gartner, ‘Multidisciplinary digital business teams — or “fusion teams” — are critical to success in digital transformation. Progressive CIOs foster rather than fight the rise of the distributed digital delivery model and maximize value by focusing on the human aspects of managing digital business risk.’

While enterprise technology analysts, practitioners and experts struggle to agree on anything, the general consensus that the major building blocks found in the hyper-automation box are:

Business Process Modelling (BPM) Software

Robotic Process Automation

Machine Learning and Artificial Intelligence

Chatbots (also embracing Natural Language Processing and Neuro Linguistic Programming)

Data Integration, Mashups and ETL Tooling

Micro-Automation Technologies

Sensor Networks and Smart Devices (IoT)

3D Modelling, Configuration and Printing Technologies

Virtual, Mixed, Blended and Hybrid Reality

Big Data

Cloud Computing

Intelligence Document Automation

Case Management and Knowledge Systems

Outsourcing

Whilst there is a great deal of hype and media attention on the ‘sex and sizzle’ digital tech tools like Businesses have spent millions of dollars on their large back-office Systems of Record that manage business-critical process flows. Examples include offerings from SAP, Microsoft, and Oracle. These systems offer a trade-off between the rewards of adopting best practice (woven into the forms, data structures and workflows these providers have adopted) and the disadvantages of slow speed of change. That said, sometimes, investing in costly and slow enhancements to existing systems can remain favourable to alternative process automation choices.

It would be wrong to accuse hyper-automation as being a new term with nothing new inside to show for it. Not that the core digital technologies themselves are anything new. What’s essentially different about hyper-automation is the underpinning philosophy surrounding how businesses harness digital technology in their business thanks to new interoperability and design tooling, and a new organizational design to serve up innovation in the form of FUSION TEAMS.

To compete in a digital era, companies need to offer an excellent and differentiating customer service experience and products and services tailored to discerning customer requests. For these and other cost cutting reasons, companies should be considering a hyper-automation strategy if they’re not already doing so. With so many ways to get a job done these days, adopting a triage approach that considers all available solution options dispassionately to produce the best outcomes is a sensible approach.

Unfortunately, the age old issues of data quality and management prevail for project teams appointed with a hyper-automation responsibility. The fact is, few organizations actually hold all of their data in a digital format. Much of the content remains trapped in hard-copy documents, siloed data repositories and desktop formats like MS Excel and MS Word. Harnessing data and re-using it remains one of the bigger challenges for change teams.

Another constraint on hyper-automation programs is the silo culture of large enterprise structures. Some organizations continue to operate organizational designs crafted in the Victorian era. Expecting all of the departmental managers to offer up their data and resources to create holistic cross-organizational data processing systems is an unlikely prospect.