How Manufacturers Can Leverage Time To Identify Profitable Products

Posted on March 01, 2018


As we discussed in Blog 1 of our Series on the Theory of Constraints, TOC allows companies to determine product profitability through time-based calculations. To fully understand the benefits of using a TOC approach, we first need to take a detour through a traditional cost accounting approach. Any operation’s cash generation is directly tied to how efficiently the most profitable products move through the primary bottleneck resource. While many companies use cost accounting as a tool for identifying which products are most profitable, it can’t do the job as effectively as TOC.

Compare the two methods, and TOC clearly speaks for itself. The below figure shows the profitability of two products through traditional cost accounting versus TOC.


Product Y sells for $100 more than Product X, and they both appear to have the same variable cost per unit. Standard costing would suggest that Product Y is more profitable on a per unit basis, with a $300 margin over Product X’s $200 margin. 

Rather than look at the cash margin per unit, TOC looks at units of time as the core metric for driving decisions. Under TOC, Product Y requires twice as much processing time in the company’s facilities as Product X (Y can only process 3 units per hour compared to X’s 6). Although Product Y generates a higher cash margin per unit, Product X generates a higher return from the assets when expressed as cash per machine hour ($1,200 compared to Product Y’s $900).  Let’s discuss the implications.

Looking at Figure below we can see the significance in the two approaches. According to TOC, over a week which has 168 hours of available capacity on our machine, Product X would generate 1,008 units with an overall profit margin of $201,600. Product Y would only generate 504 units at an overall profit margin of $151,200.


With the cost accounting view of margin per unit as the focus, the emphasis would be selling product “Y” but it would require expending 33% more machine time – which may require capital investment to increase the overall throughput – to make the same money in a week. This is taking us in the wrong direction!


New Call-to-action