AUTOMATION PREVIEW
Process automation pilot and evaluation
The business case says automation will cut the cycle in half. The board wants proof before it funds a program. The team is nervous because the last quick automation turned into a six-month project that never quite worked. An automation preview answers all three at once. It takes one real, meaningful process and builds a working automation of it in a few weeks, measured against a baseline, so the decision to scale rests on evidence from your own environment rather than a vendor's slide.
- One representative process, run on live cases, not a mock-up
- An agreed baseline and a clear success threshold set upfront
- A scale, adjust, or stop recommendation with the evidence behind it
The purpose is not to build something impressive. It is to retire the biggest uncertainty cheaply.
We pick a process that is representative, not the easiest one.
If it works, the path to scale is credible. If it does not, you learn that in weeks for a small spend rather than in a year for a large one. Every preview starts with an agreed baseline and a clear success threshold, so the outcome is a decision, not an opinion. It sits within automation advisory and consulting and usually follows process optimization and automation strategy, proving the top-ranked opportunity.
A no-go is a real, valuable outcome, reached in weeks, not a lost year.
A working automation and the evidence to decide what happens next.
- A working automation of one real process, run on live cases, not a mock-up.
- A measured result against a documented baseline: cycle time, effort, error rate.
- An exception log showing where the process holds and where it needs handling.
- A cost-to-scale estimate and the platform and architecture implications of going wider.
- A clear recommendation: scale, adjust, or stop, with the evidence behind it.
Deliberately short and fixed in scope, so it never slides into an open-ended build.
Frame
Pick the process, capture the baseline, and define success metrics. Exit on an agreed scope and target.
Build
Configure the automation on the fit-for-purpose platform. Exit on a working automation.
Run
Execute on real cases, measure against baseline, and log exceptions. Exit on measured results.
Decide
Present the outcome, cost-to-scale, and a scale-or-stop recommendation. Exit on a go / no-go decision.
The clock and the boundaries are the discipline. Day bands are illustrative; Softobiz to confirm against the chosen process. A successful preview flows into implementation and managed services to scale, and into automation architecture consulting to design for the wider estate.
The low-risk bridge between a strategy on paper and a program in flight.
A preview fits teams that believe automation will help but cannot yet justify a full program, teams burned by an automation effort that overran, and leaders who need proof from their own processes before funding a roadmap.
Where a preview sits, and where it leads.
Automation Advisory and Consulting
The advisory practice a preview belongs to, from strategy to a proven first build.
Process Optimization and Automation Strategy
Ranks the opportunities so a preview proves the top-ranked one.
Implementation and Managed Services
Where a successful preview flows to be built out and run in production.
Automation Architecture Consulting
Designs the wider estate so a proven process scales cleanly across it.
Intelligent Automation
The parent practice this advisory service belongs to.
What leaders ask us first.
A demo runs the vendor's example on the vendor's data. A preview runs your process on your cases against your baseline. The difference is whether the result transfers.
That is a successful preview. You have spent a few weeks and a small budget to avoid committing a program to a process that would not have paid back. A no-go is a real, valuable outcome.
Often, yes. We build on the platform and patterns the process should scale on, so a successful preview becomes the first increment rather than throwaway work.
Pick one real process, and see what automation does to it, before you commit to a program.
A bounded build, a measured result, and a scale-or-stop decision grounded in your own environment.