There is no universal best vending product list, and physical machine capacity is not the same thing as the amount of stock you should deliberately carry.

A useful starting rule is:

Enough of the right product to last until the next appropriate service visit.

That requires product evidence and service planning to work together.

Treat the first fill as a hypothesis

Start with purchase occasions before individual brands.

At a workplace, buying occasions may include the start of a shift, morning break, lunch, afternoon break, or a night shift with limited alternatives.

Build a controlled range of categories around those needs. For snacks, that might include salty, sweet, bars, cookies, and lighter choices. For drinks, it may include water, soda, energy, sports or hydration, and other relevant categories.

The first fill needs enough variety to reveal demand without creating excessive stock exposure.

Do not give half the machine to personal favorites merely because they sell somewhere else.

Separate capacity from par

Capacity is what a selection can physically hold.

Par is the amount you deliberately want available after service.

If a selection holds 24 units but normally sells six between visits, loading 24 every time can tie up inventory without improving customer availability.

If a selection repeatedly empties, the opposite problem appears.

Understand what a stockout tells you

Suppose a selection starts with 10 units and is empty when you return.

You know at least 10 sold. You do not know whether true demand was 10, 15, or 30.

The stockout has censored the demand signal.

Increase availability before deciding that 10 units represents the true sales level. That may mean a higher par, more facings or capacity, or a different service interval.

Record remaining stock, not just refills

A repeatable service record can capture:

  • starting par;
  • quantity remaining;
  • depletion;
  • stockout;
  • waste;
  • vend reliability;
  • customer requests;
  • the next par or product test.

That converts “this seems popular” into an evidence trail.

A buffer above recent depletion can be sensible when normal variation would otherwise create repeated stockouts. The purpose is resilience, not filling every slot to the top.

Use a four-way product decision

For each selection, choose among:

  • KEEP — the product is earning its space under the current plan.
  • EXPAND — repeated evidence supports more availability.
  • TEST — the result is promising or uncertain and needs another comparable cycle.
  • REPLACE — repeated evidence shows the product is consuming space without enough useful demand.

Consider more than units sold. Contribution per unit, space, waste, stockouts, vend reliability, and customer need all matter.

Change one thing when practical

If a product is weak, diagnose before replacing it.

The problem may be:

  • weak customer demand;
  • price;
  • stock availability;
  • insufficient capacity;
  • package-vend reliability;
  • the product itself.

Changing product, price, position, and par at the same time makes the result harder to interpret.

When practical, change one material variable and define what you will review next.

Compare several genuinely similar cycles

One unusual week can reflect holidays, weather, shift changes, a temporary event, or a service interval that was not comparable with the previous period.

Unless a product is clearly unsuitable, compare several cycles before making a permanent decision.

The reverse error also matters: a “test” product can become permanent simply because nobody set a review date.

Connect par to the route

Par levels and service frequency should be designed together.

A remote machine may justify more safe inventory if that reduces unnecessary travel. A machine in a dense cluster can sometimes run with lower quantities because a nearby top-up is inexpensive.

Do not solve every stockout by driving to the machine more often. Ask whether capacity, par, product allocation, or service timing is the real constraint.

The companion guide on planning a vending machine service route shows how stock decisions and route geography interact.