Services · Workflow Automation
Work enters in one system, gets re-keyed into a second, waits for an email approval, and someone chases its status in a meeting. Multiply that by every process in the company — that's the efficiency your competitors are about to find. Splendor's workflow automation consulting engineers the flow itself: connected systems, automated handoffs, and AI assistance where it measurably pays.
The Problem
An order, a claim, or a hire touches five systems — and a person re-keys it into each one.
"Where does this stand?" is answered by emails and meetings, never by a system.
Approvals wait in inboxes for days while customers wait on the other end.
Month-end means overtime, spreadsheets, and reconciliation nobody trusts.
The RPA bots from two years ago break every time an application updates.
Sound familiar?
What We Do
Automating a broken workflow just produces broken results faster. We map how work actually moves across your systems and teams, remove the waits and re-keying by engineering the flow, then automate the handoffs — so status becomes a property of the work, cycle time becomes a metric, and improvement becomes measurable.
Read: Workflow engineering — why the flow matters more than the tool →
How It Works
Workflow automation follows the Splendor Transformation Framework — baseline first, pilot with measurement, scale what the numbers support.
Workflow mapping and baselines — where work waits, where data is re-keyed, what each manual touch costs.
The re-engineered flow, the integrations it needs, and success metrics agreed before anything is built.
Pilot in production against the baseline; compare, tune, then roll the proven pattern across departments.
Outcomes
Cycle times cut from days to hours as waits, re-keying, and status-chasing disappear from the flow.
Every item has a current state systems can report — queue depth, aging, and throughput on a dashboard, not in someone's memory.
Data entered once and validated at the source — customers and employees stop paying for internal handoffs.
Planning AI-assisted workflows? Check your AI readiness first →
FAQ
Mapping the end-to-end flow of work across systems and teams, finding where it waits and where data is re-keyed, re-engineering the flow, and automating the handoffs — with integration, orchestration, and AI assistance applied where each pays. The outcome is measured in cycle time and error rates, not bots deployed.
RPA imitates a person clicking through broken workflows — useful sometimes, brittle often. Workflow engineering fixes the flow itself: connected systems, engineered handoffs, and status as a property of the work. Automation on a fixed flow is durable; bots on a broken flow are maintenance debt.
High-volume, rule-heavy flows with painful handoffs — order-to-cash, employee onboarding, claims and approvals, customer service intake. We baseline cycle time and error cost first, so the first automation produces a measured win that funds the next.
At the judgment steps that rules can't handle — drafting, summarizing, classifying, extracting. We deploy AI assistance inside engineered workflows with baselines and measurement, so you can see whether time-to-completion and quality actually improved.
Done right, it removes the parts of their job they complain about — re-keying, status-chasing, waiting. We design new flows with the teams who run them, pilot with a baseline, and scale only what the measurements support. Adoption is engineered, not assumed.
Intelligent automation delivery lives in our AI & Intelligent Automation practice.
Ready to move?
Pick the workflow that hurts the most — the one with the re-keying, the inbox approvals, the month-end overtime. We'll walk through what an engineered version would look like and what it would save.