Workflow Economics
Turn manual workflows into measurable capacity in 90 days.
We identify 2-3 high-cost manual workflows, quantify what staying manual really costs, and replace them with AI-enabled processes that pay for themselves in months -- not years.
The Problem
“Staying manual” is now a P&L problem.
Across mid-sized companies, employees spend 3-4 hours per day on repetitive tasks that could be automated. In a 100-person firm, that can exceed 77,000 hours of low-value work each year.
Studies show that targeted automation can reclaim 20-40% of that time while lowering error rates and improving consistency, especially in rules-based processes. For most mid-market applications, the actual AI automation spend is often in the tens or low hundreds of dollars per month per workflow -- not seven-figure transformation budgets.
The real cost is not AI adoption. It is re-buying the same manual hours every quarter while competitors hardwire AI into how they sell, serve, and operate.
Who This Is For
Mid-market operators who are done with AI experiments.
This program is designed for functional leaders who see manual work everywhere and want fewer, deeper, P&L-tied workflows instead of scattered experiments.
Program Structure
Three 30-day sprints.
Baseline, Redesign, and Implement & Scale. Each sprint produces concrete deliverables you can act on independently.
Baseline
Days 1-30Quantify the cost of manual
We start by selecting 2-3 high-impact workflows -- L1 ticket triage, quote-to-cash, RFQ processing, or change order handling. For each, we map the actual steps, handoffs, and systems involved, then measure how much time your team spends today, where errors occur, and how often work bounces between people. We translate that into an annualized cost of staying manual: fully loaded labor, rework, delay, and the opportunity cost of skilled people doing low-value tasks.
Deliverables by Day 30
Redesign
Days 31-60Build AI-enabled workflows on paper
We redesign each target workflow around AI agents and automation primitives in your existing tools. That can include agents that read inbound tickets or emails, classify intent, pull context from CRM or ticketing, draft responses, update systems of record, and hand off to humans for exceptions or approvals. Every step aligns with your security and governance model for M365 and Copilot, so access, DLP, and approvals are built in from the start.
Deliverables by Day 60
Implement & Scale
Days 61-90Ship and measure
We implement the redesigned workflows, starting with controlled pilots and expanding once we see stable performance. We integrate into your current environment -- Teams, Outlook, CRM, ticketing, line-of-business systems -- and set up measurement: how many items the new workflows handle, how much time they save, how often humans intervene, and what the new cost per item looks like.
Deliverables by Day 90
Investment & Payback
Fixed scope. Clear economics.
$75,000 - $150,000 for the full 90 days
This is a fixed 90-day program focused on 2-3 high-impact workflows. Total investment depends on workflow complexity and integration depth across your Microsoft environment.
Low ongoing run-costs
Ongoing costs for the AI-enabled workflows we deploy are usually in the tens or low hundreds of dollars per month per workflow -- not seven-figure transformation budgets.
6-12 month payback
Most clients see the program pay for itself within 6-12 months through reclaimed capacity, reduced cycle times, and lower manual error rates in the first 2-3 workflows alone.
Example Workflows
High-volume. Repeatable. Painful.
We pick workflows that are eating the most hours and have the clearest path to automation. Here are representative patterns.
L1 Ticket Triage & Support
Today (manual)
Agents manually read, classify, route, and respond to common tickets in ITSM tools.
After 90 days
AI agents classify, answer common issues, and route rich payloads for edge cases.
20-40% ticket deflection, faster first response, stabilized backlog.
Quote-to-Cash (B2B)
Today (manual)
Reps chase info, rekey data into CRM, and manually assemble quotes and follow-ups.
After 90 days
Workflows that assemble drafts, update CRM, and schedule follow-ups automatically.
Shorter cycle times, more opportunity coverage, lower admin hours per deal.
Change Orders / Jobs
Today (manual)
Field, ops, and finance pass PDFs and emails around; updates hit systems late.
After 90 days
Agents extract key data, update systems, and push structured approvals through Teams.
Fewer errors, faster billing, better visibility for operators.
Outcomes are indicative of published benchmarks and case studies. We model expected ranges for your environment during Sprint 1.
Day 90
What you leave with.
Quantified economics
A clear view of what manual work is costing you in 2-3 core workflows, expressed in dollars and capacity -- not assumptions.
Deployed AI workflows
Production AI-enabled workflows that reduce cycle times, lower manual touches, and reclaim meaningful team capacity inside your existing stack.
Expansion roadmap
A practical plan to extend AI to additional workflows, backed by proven security and governance patterns in Microsoft 365.
Security Built In
Every workflow sits on your security layer.
Everything we implement in this program respects your existing DLP policies, sensitivity labels, and identity boundaries in Microsoft 365. When needed, we help tighten them so new workflows do not introduce new risk.
We apply Microsoft's recommended patterns for environment zoning, approval workflows, and monitoring for Copilot Studio agents and related automations. The result is AI-enabled workflows that produce real economic gains without loosening your security posture or creating ungoverned shadow agents.
FAQ
Common questions.
What kind of workflows do you target?
High-volume, repeatable processes where skilled people are doing low-value work: ticket triage, quote assembly, change order handling, RFQ processing, CRM updates, invoicing, and similar rules-based handoffs. We pick the ones with the highest cost-of-manual and the clearest path to automation.
Do we need M365 Copilot deployed already?
No. We work with your existing Microsoft stack and can design workflows that use Copilot, Copilot Studio, Power Automate, or other tools depending on what fits. If you are planning a Copilot rollout, the Baseline sprint is a good way to identify where it will have the most impact.
What if we already have some automation in place?
Good. We audit what exists, measure whether it is actually saving time, and build on top of it. Most organizations have pockets of automation that were never extended or measured. We connect those to a broader workflow strategy.
How do you measure ROI?
We measure before-and-after economics for each workflow: cycle time, cost per transaction, deflection or automation rate, manual touches, and FTE capacity reclaimed. The Baseline sprint establishes the numbers so the comparison is concrete, not theoretical.
How does this relate to AI Security & Governance?
Everything we implement sits on top of your AI security layer. We respect existing DLP policies, sensitivity labels, and identity boundaries, and when needed, we help tighten them so new workflows do not introduce new risk. If you have not done a security assessment yet, we can run that in parallel.
What happens after 90 days?
You have production workflows, measured economics, and a 6-12 month expansion roadmap. You can extend with us, hand off to your internal team, or bring in another partner. There is no lock-in -- the workflows run in your environment on your tools.
Can we start with just the Baseline sprint?
Yes. The Baseline stands on its own as a deliverable: a quantified view of your manual costs and a prioritized list of automation opportunities. Most organizations move to Redesign once they see the numbers, but there is no obligation.
A self-funding foundation -- not another slide deck.
Book a call and we will walk through what 90 days of workflow economics looks like for your operation.