Psychometric profile
This is an unedited, AI-generated summary of Jack's actual psychometric testing results.
Jack leads with authority and directness. A natural decision-maker who moves toward challenge rather than away from it, and who takes seriously his responsibility to deliver results for the people and organizations he works with. His strong Investigator tendency means he doesn't just act, he understands first, building the analytical foundation that makes his decisions defensible and his systems durable. The Achiever dimension adds a results orientation and an instinct for what success actually looks like in practice, not just in theory. Combined with 85% Openness on the Big Five, this is someone who brings genuine intellectual curiosity to complex problems, comfortable in ambiguity, drawn to novel approaches, and unlikely to reach for the obvious solution when a better one exists. Low Neuroticism suggests someone who operates with consistent emotional stability under pressure. This is not a profile that needs perfect conditions to perform.
DISC D
Big Five Openness 85 · Neuroticism 25
Enneagram 8 · 5 · 3
How I work
The chaos that comes with growth is predictable. So is the fix. It is not a playbook or a silver bullet technology. It is a set of interlocking foundations that give teams the clarity to move fast in a way that adds value and avoids the kind of fragmentation that slows companies down. Built on Lean, Operational Excellence, and Systems Thinking and refined across every stage of growth from bootstrapped startups to pre-IPO rocket ships, these six pillars reinforce each other and hold up under scale.
Customer Focus
Understand what your customer values and put them at the center of every decision and every measure of success.
Clear Roles and Responsibilities
Every person on every team should understand what they are accountable for, how it adds value to the customer, and how to measure their own success.
Plan Do Check Act
Effective planning routines ladder enterprise goals down to the right level of relevancy and accountability. Review routines measure at the level of execution and ladder up to reflect holistic performance.
Reliable Processes and Transactional Integrity
Reliable processes deliver consistent customer value. Transactional integrity produces clean data. Together they create the bedrock on which AI development can actually succeed.
Data
Data should be accurate and accessible to everyone. Outcome metrics should be meaningful to the customer. Input metrics should help individuals manage their piece of the value chain.
Grassroots Continuous Improvement
Standard work does not mean static work. Data and blameless accountability give individuals the agency to improve intentionally, with benefits that are clearly defined and visible.
Case studies
Case Study 01
Aligning Order to Cash Operations with Synchronized Flow for the Perfect Order
Context
FBN's order-to-cash operations had become highly fragmented. Service-level agreements were siloed by function and disconnected from customer outcomes. Teams lacked visibility into downstream timing dependencies, making it difficult to prioritize work in a way that protected the customer delivery promise. As a result, speed to customer was inconsistent and promise-to-delivery performance had fallen below 80%.
Problem
Order execution was governed by generic, time-based SLAs that failed to reflect the actual sequencing flow required to deliver on customer commitments. Teams optimized locally, reacted late, and relied on recovery heroics to protect customer outcomes. This fostered a blame culture with finger pointing and defensiveness getting in the way of root cause and continuous improvement.
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Case Study 02
Restoring Inventory Discipline and Freeing Unproductive Working Capital
Context
During a period of rapid growth, FBN had accumulated significant inventory through opportunistic buying and an expanding SKU portfolio. Over time, a large portion of working capital became tied up in inventory that was no longer productive. The long tail of slow-moving inventory remained poorly understood and largely unmanaged.
Problem
There were no formal routines, governance, or shared framework to identify non-productive inventory, challenge forecast assumptions, and drive consistent cross-functional action. As a result, inventory decisions were reactive, inconsistent, and ineffective at reducing structural working capital exposure.
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Case Study 03
Restructuring a Customer Experience and Support Organization
Context
At FBN, the Customer Experience and Support teams had formed organically. From sales support to order entry to ongoing customer care, they had become a catch-all for tasks and responsibilities that either did not fit elsewhere or no one else wanted, producing an everybody-does-everything model with no thought given to prioritization.
Problem
Customers complained about long waits on urgent cases. SLAs were tied to broad categories rather than the urgency or complexity of the actual issue, producing KPIs that were meaningless to the people doing the work. The team itself was disengaged. Without clarity on what they were there to do, purpose was hard to find.
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Interview highlights
These excerpts were taken from actual interview transcripts.
What shaped how you think about operating at scale?
It opened my eyes to how to operate at scale — from a kind of former operator cowboy, get-shit-done guy. How to do it with rigor, how culture can play into that. It changed my whole perspective on being an operator.
On Amazon and the power of culture
How would you describe what you do really well?
What I do really, really well is I connect dots. Whether you're talking about tactical problems to strategic things, or connecting people to what their role is and why it's important and how to do it well.
On connecting the dots
Tell me about a time you didn't perform as well as you would have liked.
I thought, like a lot of Amazon people do, that the culture was plug-and-play. I was being hired to do something I knew very well, but I honestly didn't know how to sell it. I didn't know how to communicate it. I didn't know how to influence the forces that were at work in that company. I think part of my growth path, even post-Amazon, has been in that respect. I think part of what I learned at Target was managing a large group, a wide group of stakeholders — an organization that isn't adverse to change, but isn't about change for change's sake.
On growth at Wayfair after leaving Amazon
