Approach

I fix the discipline first, then build only what the discipline needs.

Most planning failures are discipline failures wearing a technology costume. The cadence, the definitions and the decision rights come first — because a system installed on top of an unresolved process just automates the argument. Then I build the part the process can't run without, in your ERP, on your data.

What I do

Nine lines, all of them hands-on.

I don't hand over a deck and leave. Every engagement ends with something running in production and a team that can operate it without me.

01 — SIOP design & facilitation

A cadence that survives contact with the P&L

Demand review, supply review, reconciliation, executive sign-off — designed around how your business actually decides, not a textbook calendar. One owner per call, one place the override is written down and later checked against what happened, and metrics defined tightly enough that the number means the same thing in every room. I chair it myself until the leads can, then hand it over. I've designed, implemented and run this three times now, in three different operating models — the third one goes in faster than the first.

02 — Planning & replenishment

The system produces the number

Reorder and production logic that reflects how the business actually sells — segmented safety stock instead of a hardcoded weeks-of-supply, real lead times, real minimum runs, shelf life where it binds — so the supply signal, whether that's a PO or a co-man run, is generated rather than negotiated. Planners get a workbench showing the exceptions, not a spreadsheet to rebuild every Monday.

03 — Network balancing & freight

Where it sits, not just how much

Half the inventory problem is placement. The same units in the wrong building are a stockout in one region and a markdown in another, and the correction ships at LTL rates. I model deployment across the network: what to transfer instead of buy or make, which node should own which item, how full the truck is when it moves, how much life is left on the pallet when it lands, and what a line actually costs to serve from each site. With freight where it is, the placement decision is often worth more than the buying decision. Where the question is large enough to need a solver rather than a rule, it becomes line 06.

04 — Decision rights & data governance

Fewer cooks, on the record

Outside the monthly cadence, the same discipline applied to the daily calls: who may change a forecast, who may override a buy, what gets logged and what gets audited. Fill rate and service defined once, published from one source, so the standing argument about whose number is right simply ends.

05 — Data & automation

Every input on the same clock

One governed data model over orders, inventory and vendors, joined to the outside signals that actually move your category, whatever the category is. Then self-serve tools and AI agents pointed at the reconciliation, chasing and re-keying that eat the week — the work nobody should still be doing by hand.

06 — Network & optimization modeling

When the answer needs a solver, not a spreadsheet

Some network questions are genuinely too large to reason through by hand: which carrier gets which lane across a freight bid, which supplier or co-manufacturer runs which volume, which sites should exist and serve which customers, what moves between nodes instead of getting bought. These are mixed-integer programs — assignment, facility location and network flow with the constraints that actually bind: capacity, minimum runs, commitments, service, shelf life, truck fill. I formulate and solve them in Gurobi and hand back the model, not a slide. What comes out isn't just a recommendation — it's a proven bound on how much better the answer could be, and shadow prices telling you what each constraint is costing you.

07 — KPI frameworks & reporting platforms

A metric is a contract, not a chart

Grain, scope, source and owner, fixed and written down — then a dimensional model underneath so cross-functional questions are joins instead of projects, then a platform architecture that survives concurrent users and can be rebuilt from a repository rather than from a person. Tableau or Power BI where the licence and the self-serve appetite already exist; Streamlit where what's needed is an application a planner works inside rather than a dashboard they look at. Sequence matters: definitions, model, architecture, tool, owner. Most failed reporting programs started at "tool."

08 — Platform selection & implementation

I've bought the software three times

I've led three out-of-the-box planning implementations end to end — ToolsGroup, Netstock and E2open — across different operating models. So this is a service line, not a competitive position: I'll run the selection if you should buy one, run the implementation if you've bought one, or come in when a live implementation has stalled and nobody wants to say so out loud. Requirements written from how you actually plan rather than from a vendor's feature matrix, an honest read on which gaps are configuration and which are the product's model of the world, and the data and definitional work that has to be right before go-live regardless of whose logo is on it.

09 — Sponsor-side work

Where the working capital went

For sponsors and boards: what the inventory is really worth, how much of it will never sell at any price, and how many people are employed to compensate for a system that doesn't work. Opportunity sizing that holds up in a board room, and a plan the operating team will actually run.

Why not just buy a platform

Sometimes you should. Here's when you shouldn't.

Relex, Blue Yonder, Kinaxis and o9 are good products. If you have the scale, the budget and eighteen months, buy one — and I'll run the selection with you. Most mid-market companies have none of those three, and the failure mode isn't the software.

I know that because I've been on the other side of it. Three out-of-the-box planning implementations, led end to end — ToolsGroup, Netstock and E2open — in three different operating models. When I say the constraint usually isn't the product, that isn't a consultant's talking point. It's what I watched happen from inside the project, three times.

Licensed platformWorking with me
What you're buyingA product, configured to youA process, and systems built to your business
Year one costLicence + implementation partner, often seven figuresFixed-fee diagnostic, then a scoped build
Time to first value9–18 months to go-liveSized opportunity in 2–3 weeks, running system in 8–16
Who does the process workYou, or a separate consulting engagementMe — that's the core of it, not an add-on
Fit to how you operateYou adapt to the model the product assumesBuilt to your ERP, segmentation, cadence and definitions
When it endsAnnual licence, foreverCode and documentation hand over — you own it

The honest version: a platform gives you software and leaves the discipline to you. Every one of those three implementations went live, and the ones that changed how the company decided were the ones where somebody did the definitional and process work alongside the configuration. That work isn't in anyone's statement of work by default. I fix the discipline first, then build only what the discipline needs — and if the readout says you should license something and run a proper selection, that's what it will say, and I'll help you do it.

How to start

Three shapes.

Most clients start with the first one. It's built so that if the opportunity isn't there, you find out in three weeks for a fixed fee.

2–3 weeks
Fixed fee

Diagnostic

I sit with your planners and read your ERP data directly. Where decisions actually get made, how many versions of the truth are in circulation, how the week is really spent, and what it's costing in labor and working capital.

→ Sized opportunity
→ Sequenced roadmap
→ Board-ready readout
8–16 weeks
Project

Build

The system gets built to your business and put into production: replenishment logic, the planning workbench, the data model, the automated feeds, the reporting. Built on your ERP and your definitions, not configured around someone else's product. Your team is in it from week one, and code and documentation hand over at the end — you own it outright.

→ Running system
→ Trained users
→ Full handover
Ongoing
Retainer

Fractional

Executive-level planning leadership a few days a month — chairing demand and supply review, arbitrating between sales and planning, coaching the leads toward running it themselves, and standing behind the numbers with the board. This is the piece that makes the rest stick.

→ Cadence held
→ Leads developed
→ Sponsor reporting

Inside the first engagement

What three weeks actually buys you.

No discovery theater. Week one is data and observation, week two is quantification, week three is the argument you take to your board.

Week 1

Read the data, watch the week

Direct extracts from your ERP — order lines, stock status, open POs, vendor masters. In parallel I sit with buyers and planners and watch the actual week happen: what gets rebuilt by hand, what gets chased, which report everyone quietly distrusts. The gap between what the system says and what people do is where the money is.

→ Data model stood up
→ Decision map drafted
Week 2

Quantify it

Service measured properly at the level it happens — item by location, not netted to a company average that hides everything. Inventory split into what's working, what's dead and what will never sell at any price. Planning labor costed against what the work would take if the system produced the answer. Every number traced back to a query you can re-run.

→ Working capital sizing
→ Labor sizing
→ Service baseline
Week 3

Sequence and defend it

A roadmap ordered by payback rather than by what's easiest to build, with a defensible number attached to each piece and an honest note on which ones I'd skip. Delivered as a readout your CFO and your sponsor can interrogate — including the case for doing nothing, if that's what the data says.

→ Sequenced roadmap
→ Board-ready readout
→ Scoped build proposal

Next step

Tell me who decides what to buy.

If that answer takes more than one sentence, there's an engagement here. An hour on a call is usually enough to know whether it's worth paying for.