Hyperautomation: definition and context
Why the Term Matters
The term shifts the view from the single automation to the portfolio. Not every flow deserves effort, and without prioritisation you automate the random. Hyperautomation first asks where the biggest lever sits, then picks the fitting technique per case. Placing the term, you see it is less about a new tool and more about a method to tackle many opportunities in order.
When It Is Relevant
- There are many automation candidates but no clear order.
- Different techniques are needed because the cases differ.
- An organisation wants automation strategically rather than piecemeal.
- An overview is missing of which processes bring the most value.
When Not
For a single clearly bounded problem, hyperautomation is oversized, then a targeted build is enough. Without a data basis and without willingness to clarify processes, the approach stays theory. And whoever wants to test one technique first should start small rather than with a big programme that promises much and delivers little.
Industries That Use It
- Wholesale and distribution: automate many recurring flows across purchasing, warehouse and sales in an orderly way.
- Insurance groups: prioritise a portfolio of application, claims and service processes by lever.
- Energy and utilities: tackle numerous customer and billing processes with mixed techniques.
- Public sector: systematically assess many application processes and automate them step by step.
Typical Use Cases
- A stocktake of which processes suit automation.
- A prioritisation by value, effort and risk.
- The build of several flows, each with the fitting technique.
- The combination of RPA, AI and integration in one programme.
- A repeatable method that keeps taking in new candidates.
Decision Guide
| Signal | Hyperautomation fits | Alternative |
|---|---|---|
| Many candidates without order | prioritise the portfolio | build a single flow |
| Different techniques needed | mixed approach per case | one technique for a simple case |
| Only one clear problem | rather not | a targeted build is enough |
| No data basis | create clarity first | start small with a pilot |
Example
A wholesaler sees dozens of flows running manually but does not know where to start. In the workshop a list of candidates with value and effort is built first, then an order. The first prioritised case is built and tested as a prototype in a few days before the next follows. So the programme grows step by step rather than in one big leap. This describes the method, not an asserted total saving.
Service Connection
The usual entry is the AI workshop for prioritisation, then AI automation per case and AI implementation for operation.
Sources
This framing describes common practice of a portfolio-oriented automation approach. Scope and order depend on the organisation's processes and data and should be worked out there.