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Decision Making with Throughput Economics

Updated: Nov 28, 2022

What is this thing called Throughput Economics, and how to apply it to make better decisions-PART 1

Among the various tasks of management - stimulating, guiding, coordinating, directing - one of the most important (if not the most important) is decision-making since it is necessary for all the other functions performed. Good decisions, possibly.

We will briefly analyze the decision-making process and compare the techniques of traditional Management Accounting as a tool to support evaluation with a new model called Throughput Economics.


Introduction to decision-making

Decision-making usually arises from the need to solve a problem.

Some problems are so repetitive and automatic that it might seem that no particular process is run behind the scene: I am hungry (the problem) - I grab something to eat (the decision).

The process becomes less linear when the decision to be made impacts the decision-maker and other spheres of influence. This is what usually happens with business decisions.

Whether the decision is repetitive or automatic, the process is the same.

  • The first step is to recognize that we have a problem.

  • The second step is to agree that it is worth analyzing its ramifications.

  • The third step is to define the details of the problem: starting from the symptoms, try to get to the cause of the problem itself, collect data to analyze it, and make it less subjective.

Hopefully, we have reached a detailed description of the problem in the first three steps. Still, since it touches multiple spheres of interest, its representation is not a sufficient condition for deciding to solve it. The following steps are:

  • Achieve consensus to move the process forward: the problem exists and is worthy of resolution.

  • When all the above is agreed upon, it is possible to move ahead to identify how to solve it. It is possible to leverage all the deliverables already produced in steps 2 and 3, plus any additional information gathered in the consensus phase.

  • When more options are likely to have different impacts, develop scenarios to evaluate each.

  • For each option, estimate the costs and benefits of different possible solutions.

  • Arrange a short list of possible solutions to be implemented, eliminating the least beneficial options.

For complex decisions, several consensus meetings are necessary to discuss the different solutions and options before reaching an agreement. For problems of a certain complexity, developing solutions for decision-making requires teamwork and an interactive process.

  • When consensus is reached within the work group, the team shall present the solution to management entitled to make the final decision.

  • Then after the decision is made, the process enters the implementation and execution phase.

The process illustrated so far also applies to more repetitive business decisions, which sometimes may even be delegated to the information system software. Take, for example, the Material Requirements Planning (MRP) process, which generates planned supply orders, leaving the material planner with the task of confirming the decisions (the planned orders issued by the system).

  • The MRP identifies a problem: the need to replenish a material that has reached the reorder point.

  • To qualify the problem, it collects data in the system to define the due date for restoring the stock before going into stock-out.

  • The consensus that the problem exists is implicit in the system logic: a policy written in the system defines the reorder point that triggers the replenishment process.

  • Solving the problem means placing a replenishment order and deciding how much, when, and to whom: again, the decision parameters are already defined in the system with supply quotas, lot size, lead times, and so forth.

  • In MRPs, capacity is infinite. It means that they are not designed to build scenarios. For simulating and evaluating different options, it is necessary to use Advanced Planning & Scheduling software (APS) that considers capacity constraints.

  • With few exceptions, the process ends with the generation of planned orders approved by the material planner and released as actual orders for the implementation (supply chain execution). The managerial approval process results in the need for exception management.

Other decisions cannot be fully delegated to information systems, as they may require managerial judgment, and the sphere of management intuition also assumes greater importance. To name a few:

  • Make-or-buy decisions.

  • Investment decisions.

  • Pricing decisions.

  • Production mix decisions.

Whatever the decision to be made, whether it can be automated or not, making a good decision requires an effective deductive model and metrics system to transform data into information and actions.

Evaluation & Metrics

Within the decision-making process, the deductive (evaluation) process and metrics are cornerstones for several purposes because they set the paradigms that we will use to:

  • make the questions to identify and qualify the problem;

  • decide how to measure the problem;

  • evaluate the outcomes of different possible solutions.

The deduction process is the aspect that, starting from the observation of reality and data, translates them into information from which actions (or non-actions) flow: detecting or not detecting that a problem exists, the criteria for judging the most suitable option, and so forth.

Suppose we instruct the inventory management system to reorder only when the stock reaches the reorder point. In that case, the system will produce the planned orders only when such a level is reached, doing nothing before the reorder point is hit. A different policy could be to instruct the system to issue daily replenishment orders based on quantities consumed to get completely different behavior.

Metrics are the factors to measure, compare, and rank different decision options. They are necessary for the evaluation and consensus stages.

The metrics must be broadly shared to limit subjectivity in judgment as much as possible.


Which variables should be considered?

What requirements the deduction process and metrics system shall meet when applied to decision-making?

They must make it possible to identify, among several alternatives, the most productive one, that is, the option that brings the company closer to its goal. How to decide whether or not a metric is effective for this purpose?

A business metric is effective for making business decisions only if it satisfies causality requirements between the decision itself and the target. If the Goal of the organization is to make profits now and in the future, then the metrics used should have the dollar sign attached to assess the financial impact of the decision and shall take care that maximizing profits today will not jeopardize the profits of tomorrow.

Throughput Economics or Management Accounting?

Throughput Economics is the methodology suggested by the Theory of Constraints for financial analysis of business decisions and performance management.

It relies on Throughput Accounting data and transforms them into information by providing the framework (metrics and deduction process) for decision-making, planning, and performance measurement processes.

Drawing a parallel, Throughput Economics stands for Throughput Accounting, and Management Accounting stands for Cost Accounting.

We will delve into the details of the two methodologies in the second part of the article. For now, we will provide two pieces of information:

  1. Throughput identifies the rate at which the system generates money through selling products and services.

  2. Throughput Accounting does not make fixed cost allocations to products; therefore, all expenses, including transformation, are considered period costs.


Implications and advantages of using Throughput Economics

We now list the benefits of Throughput Economics over traditional Management Accounting in decision-making, planning, and control processes. We will analyze the details of the two methodologies and go into the different advantages in the second part of the article.

Throughput Economics & Management Accounting
Throughput Economics & Management Accounting


We explained how the deductive process and metrics influence the decision-making process.

We explained that since the goal of companies is to make profits now and in the future, the metrics and valuation model must be financial and consistent with that goal.

Finally, we introduced Throughput Economics, arguing its superiority from all points of view over traditional Management and Cost Accounting models.

In the second part of the article, we will explain how Throughput Economics provides better information, analyzing different areas of evaluation.

For now, we want to offer some food for thought, which we invite the curious reader to try to answer.

  1. Can we still afford to base assessments on a system that does not distinguish the criticality of different resources and ignores constraints?

  2. Pursuing flow efficiency or resource efficiency: what is the priority?

  3. Is an hour lost to a constraint comparable to an hour lost to another non-constraint resource?

  4. Can we continue to neglect such a significant effect as variability in management accounting?

  5. Do we lose information capacity if we do not calculate the total cost of products and stop allocating costs for managerial purposes?

  6. What are the negative branches of a metrics system that promotes local optimum instead o global optima?

  7. Is management accounting effective in explaining phenomena and getting management's attention?

Contact us

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We have helped leading companies in various industries successfully implement articulated, cross-organizational transformation programs--Sales, Operations, Supply Chain, and Finance--achieving double-digit increases in profitability and substantially improving ROI on invested capital.

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