Selected work

Results, not reports.

One consulting practice since the early 2000s, first as EBS, then PennyDrop Strategies, now ARYS, working with associations, nonprofits, manufacturers, distributors, transportation companies and e-commerce businesses. Client and employer names, and any identifying details, are withheld. The patterns and the decisions are real, and they’re what transfer.

~500
Engagements since
the early 2000s
30+
AI readiness
roadmaps delivered
20+
Transportation
analytics clients
$125M
Largest program
led end to end
Manufacturing & Distribution · Program leadership

$125M enterprise technology program for a national industrial manufacturer and distributor

The challenge

A national industrial manufacturer and distributor with a national distribution footprint had built its technology stack through two decades of acquisitions. Six mission-critical systems operated in near-total isolation: a decades-old WMS running batch processing with no real-time inventory visibility, a homegrown OMS with brittle EDI integrations to hundreds of trading partners, a monolithic ERP that could not consolidate financials across multiple acquired business units, and field service technicians dispatched by phone and tracked on whiteboards. There was no unified customer record across sales, service, and order history. Month-end close required weeks of manual reconciliation.

What I did

I led a $125M, three-year enterprise transformation spanning six interconnected platforms: a modern WMS, an OMS with EDI modernization, a consolidated ERP, a CRM, an ITSM platform, and a field service management system. My team served as the program management and integration architecture backbone across 12 vendors, 300+ stakeholders, and eight parallel workstreams. I sequenced delivery to protect operational continuity: ERP and WMS first to stabilize the operational core, OMS and CRM next to unify the customer layer, then field service and ITSM to close the loop on service operations.

Program outcomes
$125MDelivered on schedule, 36 months
6Enterprise platforms implemented
99.4%Inventory accuracy (from 83%)
65%Reduction in order cycle time
Platforms delivered
  • WMS: wave/batch/zone picking, RF-directed operations, slotting, labor management
  • OMS: EDI modernization (850/856/810), ATP, drop-ship orchestration, backorder mgmt
  • ERP: multi-entity financials, procurement automation, standard costing, close acceleration
  • CRM: customer 360, quote-to-order, dealer portal, opportunity, sales forecasting
  • Field Service: mobile work orders, route optimization, van inventory, SLA, warranty
  • ITSM: incident/change/problem, CMDB, self-service portal, SLA enforcement
Strategy

Technology vision and roadmaps: the core of the practice

The challenge

Most organizations that call me have a stack that grew one decision at a time, and a list of problems nobody has ranked. Leadership can feel that something is off, but not what to fix first, or what the next five years should look like.

What I did

I look at the current stack and the problems people actually live with, then build two things together: the low-hanging fruit that pays off in weeks, and a long-term technology vision tied to what the organization needs and wants. In many cases I stay on to help implement it.

Outcomes
Now + nextQuick wins and a long-term plan, in one
OftenCarried through to implementation
Strategy & AI

AI readiness roadmaps for 30+ organizations

The challenge

Manufacturers, distributors, e-commerce businesses, associations, nonprofits and founders, all asking the same question: where should AI actually go first, and what has to be true before it works?

What I did

Assessed each organization’s data maturity, governance gaps and real opportunities, then delivered a prioritized roadmap grounded in its own context rather than a generic framework.

Outcomes
30+AI readiness roadmaps delivered
6Kinds of organization, from founders to associations
Strategy

Tech stack check-ups: a short, honest read

The challenge

Not every organization needs a full assessment to start. Some just need someone experienced to look at the stack and say plainly where they stand.

What I did

A focused working session, typically four to six hours, on the stack and its problems, followed by a clear read on what’s working, what isn’t, and what to look at next. Many clients go on to a larger engagement; others I point to the right vendor or implementer for the job.

Outcomes
4–6 hrsTypical working session
ClearRead on where you stand
Associations

Technology vision for professional and trade associations

The challenge

Several associations, including a medical professional association, had tech stacks that had grown piece by piece around the AMS, and no shared picture of where to go next.

What I did

Worked through each organization’s stack with its team and delivered a technology vision: what to fix now, what to plan for, and how the pieces should fit together over the next several years.

Outcomes
StackReviewed end to end
VisionNear-term fixes and a multi-year direction
Associations

AMS selection and migration for two associations

The challenge

Two associations, in the late 2010s, had outgrown their AMS and needed an independent view of which platform to move to, and how to get their data there cleanly.

What I did

Ran the vendor evaluation, built the data migration strategy, and helped negotiate the contract, so each association chose on its own requirements rather than on the best demo.

Outcomes
2Associations moved to a new AMS
IndependentEvaluation, migration plan, contract
Associations · Data

Data ecosystem overhaul for a national financial association

The challenge

A national financial association had accumulated 15 disconnected data sources across their AMS, accounting platform, event management, regulatory reporting, and a tangle of spreadsheet workflows that had grown over a decade. Staff spent days each month reconciling figures that never quite agreed, and leadership had no reliable real-time view of organizational performance.

What I did

Audited all 15 sources, designed a centralized cloud-based data architecture, and built automated pipelines to consolidate everything into a single source of truth. A continuous-monitoring data quality framework replaced manual reconciliation. A self-service analytics layer then put trusted, governed data directly in the hands of staff and leadership.

Outcomes
15→1Data sources unified
70%Reduction in manual reconciliation
Self-serveData access for all staff
Transportation · Data

Cost and fuel-surcharge analytics for 20+ transportation companies

The challenge

Small carriers run on thin margins, and without good analytics it is hard to see what the operation really costs, or how fuel surcharges are landing against actual fuel spend.

What I did

Built analytics on operating costs and fuel surcharges from the systems each company already ran, so owners and dispatchers could see the numbers without waiting on anyone. For some, I also built driver scheduling systems.

Outcomes
20+Transportation clients
Costs + fuelVisible in one place
Data & AI

Demand forecasting for a retailer

The challenge

A retail group was planning inventory for more than 200,000 SKUs in spreadsheets. Overstock was tying up cash, and stockouts were costing sales and customer goodwill.

What I did

Built and deployed machine-learning forecasting models integrated directly into their ERP and merchandising systems, with monitoring and retraining so the forecasts stayed accurate after go-live.

Outcomes
200K+SKUs forecast
~$75KReduction in overstock
MLForecasts inside the ERP, with retraining built in

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