A note about where we are.
The Hawk AI Productivity Lab is a new service. What we do have is 30+ years of operational experience across 50+ mergers and acquisitions, three public companies, and decades of founder-led business building. The methodology is proven. The AI application layer is new. This page will grow as we complete engagements and publish real, named results.
Who is behind this
Michael Dinkins
Former CFO and board member across three publicly traded companies. 30+ years of corporate leadership, 50+ mergers and acquisitions, and a track record of building businesses that actually work at the operational level.
The AI Productivity Lab applies that same operational rigor to founder-led businesses — using modern AI and automation tools to solve the workflow problems that Michael has spent decades diagnosing in boardrooms.
30+
Years experience
50+
M&A deals
3
Public companies
The Methodology
What a Typical Audit Uncovers
Every founder-led business has bottlenecks hiding in plain sight. These are the four categories we audit first — because they are where the most time and money leak out.
Client Onboarding
Common bottlenecks we find
- Manual intake forms that require re-entry into 2–3 systems
- Follow-up sequences that depend on the founder remembering
- No automated welcome flow after payment
Proposal & Follow-Up
Common bottlenecks we find
- Proposals built from scratch every time instead of templated
- No system for tracking which leads need follow-up and when
- Quoting process that takes days instead of minutes
Scheduling & Dispatch
Common bottlenecks we find
- Manual calendar coordination across team members
- No automated reminders for upcoming appointments
- Dispatch decisions made from memory instead of data
Reporting & Visibility
Common bottlenecks we find
- Revenue numbers that require manual spreadsheet assembly
- No dashboard showing pipeline, capacity, or utilization
- Decisions made on gut feeling because data is too hard to pull
How We Prove It
What We Measure
Every audit produces a scorecard with these four metrics — measured before and after. No vague promises. Numbers you can verify.
Hours saved per week
Time reclaimed from manual, repetitive tasks that can be automated or eliminated
Cost per workflow step
What each manual step actually costs in labor, tools, and opportunity cost
Error and rework rate
How often manual processes produce mistakes that require correction
Time to completion
How long a workflow takes from trigger to finished — before and after optimization
When we publish case studies, each one will include:
We will only publish results from real engagements with permission from the client.
Client type and industry
The bottleneck we identified
What we recommended
What we built (if sprint)
Measurable result (time saved, cost reduced)
Timeline from audit to outcome
Be one of our first case studies.
Early clients get the full audit methodology at launch pricing. You get a real operational fix. We get a real case study. Fair trade.
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