what is an example of a company?s main cost drivers and how would they be able to lower their cost driver if needed?

June 28, 2026

A simple way to see this is to zoom in on one company, pick its main cost driver , then show what levers it has to reduce that driver.

Example company and its main cost driver

Imagine a mid‑sized manufacturing company that produces metal parts for the auto industry. One of its main cost drivers is machine hours used in production. Machine hours drive many large cost buckets:

Depreciation of equipment (more hours → more wear and tear).
Maintenance and repairs.
Energy usage (electricity, cooling).
Labor tied directly to operating and supervising the machines.
Setup and changeover time between product batches.

In activity‑based costing, this company might use “machine hours” as the driver to allocate a big overhead cost pool (maintenance, utilities, supervision) to each product. The more machine hours a product consumes, the more cost it “pulls” onto itself.

Why machine hours drive cost

Machine hours become a dominant cost driver when:

The business is capital‑intensive (lots of expensive equipment).
Overhead is high (maintenance, quality checks, engineering support).
Products differ a lot in complexity, so some need much more machine time than others.

If the company can reduce machine hours per unit (without hurting quality or sales), it reduces:

The total overhead it needs (fewer maintenance hours, less energy, fewer operators at a given volume).
The overhead allocated to each unit, making unit costs lower and margins higher.

How the company could lower this cost driver

Using the same example, here are practical ways the company could lower “machine hours” as a cost driver.

1. Process and technology improvements

Invest in more efficient machines. Newer equipment might produce more units per hour or need less setup time per batch.
Automate repetitive tasks. Robots or automated handling can speed up loading/unloading, reduce idle time, and smooth flow.
Improve preventive maintenance. Better maintenance planning reduces unplanned downtime, so the same capacity is achieved with fewer total hours.

Story angle:
Think of an old factory whose machines frequently break down. Every breakdown adds hours of “non‑productive” machine time and overtime labor just to make up lost output. By upgrading one key machine and adding sensors for predictive maintenance, the plant cuts downtime by 30%. Those “saved” hours mean less overtime, lower maintenance cost, and fewer overhead dollars allocated per part.

2. Lean manufacturing and setup reduction

Reduce setup/changeover time (e.g., using SMED‑style methods like standardizing tools, doing more prep externally, using quick‑release fixtures).
Increase batch sizing smartly when possible, so there are fewer changeovers per week.
Smooth production scheduling to avoid constant switching between small orders.

Effect on the cost driver:

Fewer changeovers = fewer “non‑productive” machine hours.
More of the total machine time is actually producing saleable units, so machine hours per unit fall.

3. Product and design changes

Design parts that are easier to machine. Simplify features, tolerances, and materials so they require fewer passes or fewer complex operations.
Standardize components. Using common designs across products can reduce unique operations and custom setups.

Example:
If a component currently needs three separate machining operations on different machines, redesigning it so two operations can be combined on one machine might cut required machine hours per unit by 20–30%.

4. Better planning, capacity use, and staffing

Optimize production sequencing. Group similar jobs so settings don’t need to be changed as often.
Balance lines and remove bottlenecks. If one machine is a bottleneck, adding a parallel line or shifting work can reduce total hours spent in queues and rework.
Cross‑train workers. Operators who can run multiple machines can keep more equipment running with fewer idle hours.

Result:

Less idle or partially utilized machine time.
Lower effective machine hours per unit at the same volume.

5. Shifting or redefining the cost driver

Sometimes the best move is to question whether machine hours should be the main cost driver at all.

If setup time is the real cost killer (short runs, many variants), then “number of setups” could be a better main driver.
If quality checks and rework are exploding, “number of inspections” or “defect rate” might better explain costs.
If logistics dominate, drivers like “number of deliveries,” “distance per delivery,” or “returns rate” may be more relevant.

Then, the company can target those specific drivers:

Reduce number of setups by standardizing products.
Reduce defect rate with better training and process control.
Redesign delivery routes or policies to reduce trips and returns.

Quick HTML table: example driver and actions

Below is a simple HTML table summarizing the example.

html

<table>
  <thead>
    <tr>
      <th>Aspect</th>
      <th>Example for manufacturing company</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Main cost driver</td>
      <td>Machine hours used in production</td>
    </tr>
    <tr>
      <td>Costs influenced</td>
      <td>Maintenance, energy, machine depreciation, operator labor, setups/changeovers</td>
    </tr>
    <tr>
      <td>Why it matters</td>
      <td>Higher machine hours per unit increase overhead assigned to each product, lowering margins</td>
    </tr>
    <tr>
      <td>Ways to reduce it</td>
      <td>Newer equipment, automation, shorter setups, lean scheduling, better maintenance, simpler product designs</td>
    </tr>
    <tr>
      <td>Alternative drivers</td>
      <td>Number of setups, defect rate, number of deliveries, distance driven, returns rate</td>
    </tr>
  </tbody>
</table>

How this ties back to your question

So, to directly answer:

Example of a main cost driver: For a manufacturing firm, “machine hours” (or “number of setups,” or “units produced”) is a main driver that explains a large share of its costs.
How they lower it: They can improve processes (lean, automation), upgrade technology, redesign products, optimize schedules, and sometimes shift to a more accurate driver (like setups or defect rates) and then attack that root cause.

This same logic applies in other businesses too:

In a call center , minutes of call time or number of calls drive labor and telecom costs.
In logistics , kilometers driven, number of stops, or weight/volume shipped drive fuel, driver, and fleet costs.
In software/SaaS , main cost drivers might be users, API calls, or data storage, leading to actions like code optimization, better infrastructure scaling, or usage‑based pricing.