Manager, Supply Planning

Sesh is a modern nicotine platform company and the #1 independent pouch brand in the US. Our mission is to accelerate the end of smoking. We operate a Canadian and a US operating company, we make our product through a partner manufacturer, and we sell through distributors and retail. We are growing fast and the finance function is being built as we go.
You are not starting from zero. There is a demand plan, a contract manufacturer, an ERP, and a team that has kept products on shelf through a lot of growth. What is missing is the layer in between: the supply plan gets rebuilt more often than it gets trusted, and inventory health is the residual of everything else rather than something we set on purpose. And underneath it, the sales curve ahead of us requires our contract manufacturer to add capacity faster than they ever have. The investment decisions sit with leadership, but the plan that says when capacity binds, and the week-to-week work of holding the CM to the ramp, sit here.
What you'll own

Capacity ramp at our contract manufacturer

Maintain the capacity picture against the growth plan: how much capacity we need and by when, worked backwards from equipment and qualification lead times, so the investment call gets made while there is still time to act on it.
Model the constraint stack - filling lines, blending, packaging, labor and shifts, warehousing, lab and release - and know which one binds next. It is rarely the one everyone is watching.
Track the ramp with the CM against dates and owners rather than a standing agenda item: line additions and qualification, equipment lead times, staffing, and throughput improvement. Chase the milestones and surface the slips early.
Give the CM the forward visibility they need to staff and invest ahead of the curve, and give us an honest read on whether their commitments are real. Escalate with options attached - build-ahead, added shifts, resequencing.
The supply plan and inventory health

Own the constrained supply plan across the full horizon: a rough-cut view out 12 to 18 months to feed capacity decisions, a 13-week operating window, and a firm near-term commit.
Build and defend finished goods inventory targets by SKU and location, from measured demand variability, supply variability, and our service target - not a flat rule of thumb applied to everything.
Size the buffer to absorb real forecast error and production variability. Measure both, segment SKUs by volume and volatility, and revisit targets on a cadence as the ramp changes them.
Balance service, cash, and shelf life, and own the supply side of launches and transitions - build-ahead, phase-in and phase-out, and no stranded components when a format changes.
S&OP and weekly execution

Lead the supply and capacity review in our monthly S&OP. Bring a plan rather than a data dump: where demand and capacity diverge, how far out, what the options are, and what you recommend.
Run the weekly sales and operations execution meeting. What changed, what it does to the plan, what we are doing about it, who owns it, and by when. Standing agenda, decisions made in the room.
Publish the plan of record, and keep the line clear between what gets settled weekly and what goes to monthly S&OP, so decisions reach leadership with time to act.
Production planning and materials

Translate the supply plan into a feasible build schedule with the CM: line assignment, campaign and changeover sequencing, minimum runs, and lead times that reflect how the plant actually runs.
Hold the rolling production commit - a firm window with defined change rules - and hold both sides to it, including us. Track schedule adherence, yield, and scrap against plan, with root cause and corrective actions on the misses.
Secure the materials behind the plan. Nicotine, pouch material, cans and lids, film, labels, and cartons have to be at the CM in the right quantity at the right time, whether we buy them or the CM does.
Own material requirements planning off the production plan - BOM accuracy, lead times, MOQs, coverage - so a shortage is visible weeks out instead of the morning of, along with material aging and obsolescence exposure when artwork or specification changes.
Systems, data, and AI enablement

Own the planning master data - lead times, BOMs, yields, MOQs, calendars, planning parameters. Bad parameters produce a confident, wrong plan, and everyone believes it until it fails.
Design AI-enabled workflows for scenario modeling, exception surfacing, and the weekly metric set - forecast accuracy and bias, plan attainment, inventory versus target, material coverage, capacity runway - so planning scales without headcount scaling with it.
What success looks like in year one

The capacity picture is current and trusted, and the next constraint is visible early enough for leadership to act on it rather than react to it.
The supply plan is the plan of record, and sales, operations, and finance argue about the decision rather than about whose numbers are right.
Weekly execution closes decisions on a standing cadence, and the monthly review is a decision forum rather than a status update.
Finished goods inventory sits inside target range by SKU, with service protected and cash not parked in the wrong items.
Schedule adherence at the CM is measured and improving, and no run is lost to a material shortage we could have seen coming.
What we're looking for

5-8 years in supply planning, production planning, or materials planning within CPG or similar consumer products, including time planning through a contract manufacturer or co-packer.
You have planned through a capacity ramp or a step-change in volume and know which assumptions break first, because you have watched them break.
You have owned a supply plan end to end, not just fed one, and have presented the supply view in an S&OP or IBP process with senior leaders in the room.
Working knowledge of inventory strategy: safety stock modeling, SKU segmentation, and the ability to defend a target with the math behind it.
Working fluency with an ERP and planning tools (Cin7, NetSuite, SAP, Oracle, or similar) and genuine strength in Excel - modeling, not formatting. Regulated categories a plus.
You're likely a fit if you treat forecast error as a design input rather than an excuse, plan for the volume that is coming instead of the volume in front of you, are willing to be the person who says the plan does not work and here is what would work instead, and already use AI to do the work rather than just to write about it.
Why Sesh

High ownership, direct access to leadership, and real exposure to how the decisions get made.
A function to build rather than inherit, a lean Austin team, no ego, and fast decisions.
Competitive compensation and benefits, and room to grow with the function you build.

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