How to use Throughput Accounting to Drive Results

by | Lean Six Sigma

American entrepreneur Jim Rohn once said, “It is the set of the sails, not the direction of the wind that determines which way we will go.”

Let’s say that you have an exemplary ship with a strong crew and you set your sails utilizing a navigation device. Unfortunately, you are unaware that your navigation tools are not accurate. Will you reach your destination?

I have seen this occur in multiple organizations, and it can be discouraging for the employees and harmful for the business.

I would like to share with you why some commonly accepted accounting and efficiency metrics used in operations are not as useful as we initially thought. I will then share with you a simple but robust model that will work in almost any organization or industry.


One of the most common ways to measure efficiency is to calculate Performance to Plan:

Performance (% to Plan) = Actual Output ÷ Planned Output

Usually, the output is measured by units produced within a specific time-frame, such as a minute, hour, or shift. This formula calculates the rate for an individual or an entire production line.

This is an excellent method for identifying whether or not you achieved the plan, but it encourages over-production as employees are incentivized to out-perform the plan.

In Lean Six Sigma, over-production is the most significant cause of waste because it creates excess inventory, wait time, transportation, handling, expired or damaged goods, and it can hide problems in the system.

Further, how do we know that the planned output is the most cost-effective? What if we are using more labor than needed to hide output problems? This metric alone will not correlate with the profitability of an organization.

When a system relies mostly on machines, it is common to measure the mechanical up-time, or Operational Availability (OA):

OA = Actual Availability ÷ Planned Availability

Much like the Performance formula, OA causes over-production as the metric encourages employees to produce as much as possible, regardless of flow or customer demand.

Another downside to this metric is that it fails to factor in the variable costs of producing each unit. For example, the OA formula will not help us determine if it is more profitable to maintain a 98% OA with three employees or a 95% OA with two employees.

Leaders are then incentivized to add labor hours to maximize OA rather than look for ways to reduce the variable costs.

A more comprehensive form of measuring efficiency is calculating the Overall Equipment Effectiveness (OEE):

OEE = OA × Performance × Quality

OEE is a great tool to identify waste in the system as it separates employee, machine, and quality. While it is a more comprehensive evaluation tool, it still encourages over-production, and it fails to factor in the labor costs used to improve each metric.

This is why I find the metrics used in the Theory of Constraints so valuable.


Dr. Eliyahu Goldratt introduced Throughput Accounting (TA) along with the Theory of Constraints in his book, The Goal. TA differs from Managerial Accounting in the way it calculates inventory and equipment. As highlighted by Dr. Goldratt, using managerial accounting can hide problems that impact overall profitability.

Understanding TA will help drive profitability into your organization, and it will help identify what metrics to measure on an hourly basis.

There are three basic categories in TA as defined by Dr. Goldratt:

Throughput: The rate at which the system generates money through sales, calculated by subtracting the Variable Costs (labor, transportation, WIP, consumables) from Net Sales.

Investment: All the money invested in purchasing things needed by the system to sell its product, such as inventory on hand and the depreciation of capital investments.

Operating Expenses: All of the money the system spends turning inventory into throughput, such as rent, salaries, maintenance, etc.

You can increase the total profit of an organization by improving Throughput, or by reducing Investment and Operational Expenses.

Dr. Goldratt introduces the following formulas to help identify opportunity:

Net Profit = Throughput – Operating Expenses

Return on Investment = Net Profit ÷ Investment

Throughput Accounting Ratio = Throughput ÷ Operating Expenses

Investment Turns = Throughput ÷ Investment

I believe these ratios are helpful, but I suggest simplifying the process by focusing on one main metric:

Throughput Cash Flow = Throughput – Investment – Operating Expenses

Throughput Cash Flow is not a true Theory of Constraints calculation, but it simplifies the need for multiple metrics and is easy to understand.


Measuring the Throughput Cash Flow on a weekly and monthly basis will help your organization focus on improving throughput and reducing costs.

It also calculates the benefit of investing in new technology and operating expenses. For example, below is a simplified scenario showing how to measure the investment of a new machine:

Current metrics

Throughput: $50,000

Investment: $20,000

Operating Expenses: $20,000

Throughput Cash Flow: $10,000

Proposed investment with a new machine

Throughput: $60,000

Investment: $25,000

Operating Expenses: $20,000

Throughput Cash Flow: $15,000

As you can see, the machine benefited cash flow by increasing Throughput without adding variable costs. Even though it increased the Investment category, the overall Net Cash Flow improved.


TA is an effective way to measure profitability for the organization, but what metrics can leaders track on an hourly and daily basis?

To measure the effectiveness of daily operations, we should be working to improve Throughput. This can be done either by improving the rate of production or by reducing variable cost.

Let’s use an example of an Operations Manager with labor being the highest variable costs that she can influence. We calculate the number of units delivered to the customer—as this discourages over-production—by the number of labor hours used to produce the units, or Throughput per labor hour (TPH):

TPH = Units delivered to the customer per hour ÷ labor hours

Now the Operations Manager is incentivized to increase the number of units produced each hour without over-producing customer demand by optimizing the efficiency of labor. Here is an example:

Sara’s team is responsible for producing 30,000 units in 10 hours with 50 employees. If Sara runs a perfect shift, she will have a TPH of 60, (30,000 ÷ 10 ÷ 50 = 60).

Let’s say that customer demand is high enough for her to produce 35,000 given the same condition. She now has a TPH of 70, due to her being able to produce more with the same resources, (35,000 ÷ 10 ÷ 50 = 70).

Another scenario is if Sara is limited to 30,000 units due to customer demand but can finish her shift with 48 employees instead of 50. Her TPH will be 62.5, (30,000 ÷ 10 ÷ 48 = 62.5). This scenario is possible when you have a flexible workforce with policies that allow the manager to reduce labor hours during a shift, such as Voluntary Time Off.

In the unfortunate scenario that Sara’s team is unable to meet Throughput, or utilizes more labor hours to accomplish the goal, the TPH and the TA metrics decline. However, if the operations manager is aware of these target metrics and how they improve the profitability of the organization, their decisions will be driven by that goal, which will help them focus energy on what is most important.


These metrics can be used in the service industry as well. For example, if I owned a pool cleaning business, the pools would be the unit of measurement, and the labor hours would be my main variable cost.

Since it takes more time to clean a pool, it may be best to use a daily metric rather than an hourly metric:

TPH = Pools cleaned per day ÷ labor hours

If a Sales Manager wanted to measure efficiency, they could use the same formula:

TPH = Sales per hour ÷ labor hours


Aligning your organization’s metrics with true profitability through the use of TA and TPH formulas is the same as giving a seasoned sailor a compass.

If you are not currently using TA, I encourage you to compile the last three months of production data to compare the Throughput Cash Flow metric with your current Managerial Accounting metrics. Which one is a better representation of your organization’s profitability?

If you are not currently using TPH to track hourly or daily productivity, I encourage you to compile three weeks of production data to compare the TPH metric with your current practices. Which one gives your leaders the best incentive to improve the organization’s profitability?

Realigning your metrics with your strategy will enable you to make data-driven decisions that improve the overall value of your organization.

Often, we have a ship built for success… we only lack direction.

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