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Theory of Constraints, control system, and metrics.

Updated: Nov 28, 2022

How to improve decision-making processes and behaviors in business by measuring what to measure and how to measure it.


In the first article of our Blog - How to improve the S&OP process with the contribution of the Theory of Constraints - we focused on describing the errors that most commonly afflict Sales & Operations Planning processes. In the top 3, we highlighted how the problem of gaps in the metrics system is often among the most impactful.

Now we want to deepen the theme by explaining

  1. The role of metrics

  2. The pitfalls to managing when defining the system of metrics

  3. How the Theory of Constraints can make the system of measures more effective for both decision-making and performance control processes

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1. The role of metrics

“When you can measure what you are talking about, and express it in numbers, you can claim to know something; but if you can't measure it, if you can't express it with numbers, your knowledge will be poor and unsatisfactory: perhaps a beginning of knowledge, but not enough to advance your thinking to the stage of science... [] If you can't measure it, you can't improve it” - Lord William Kelvin

In companies, many metrics are used in various fields and for multiple purposes. These can be the measures to define the specifications that a product must meet or metrics to set the specifications of a process and verify its behavior. Metrics and standards are set to measure customer satisfaction levels and the financial result of the organization or its sub-units in a certain period. And so on.

Abstracting ourselves from the specific context, metrics are used to define a quantifiable specification of a certain goal to be achieved and determine to what extent it has been achieved. By measuring deviations from the index set for the objective, the analysis of variances aims to identify the variability of the processes and identify the common and special causes that led to these variations, in order to remove them and / or control their manifestation and / or mitigate their effects.

In order not to be dispersive, we specify immediately that we will focus on the role of metrics as a tool for coordination and managerial control.

In this context, metrics exert an essential function, being used for a plurality of purposes:

  1. To set objectives for management, with the dual purpose of fulfilling both ex-ante coordination purposes and performance incentive purposes

  2. To check "ex-post" and provide feedback about the work of managers and their business functions and, pushing further and further down in the organizational charts, the result of each person in the organization.

The metrics system exerts a significant power of direction, influencing people's behavior, all the more markedly when the MBO incentive system is linked to them.

For this reason, designing a coherent and harmonious metrics system is extremely delicate.


1.1 Metrics and organizational model

The control system and its metrics are an essential complement to the organizational model. The assumptions underlying organizational models, especially the functional ones, are as follows:

  1. To manage complexity, it is necessary to divide the organization into many subunits that are more easily manageable and controllable

  2. With the proxy system, each sub-unit is assigned a manager

  3. To coordinate and control the different sub-units, each is assigned a plan of objectives and functional metrics

  4. The system of objectives and metrics aims to coordinate ex-ante the functions to achieve the common corporate goal and provide feedback on managers' work.

  5. Managers are incentivized to achieve the best performance for their sub-unit through a "compensation" model for objectives (MBO)

The model is put in place by defining a cascade of local metrics for each sub-unit, which must be linked to the purpose of the function in achieving business objectives.

The underlying paradigm of such a model is the assumption that performance is additive, i.e., that the organization's performance is equal to the sum of the performance of individual sub-units.

To better understand, let's delve into the topic of measures.


1.2 Global and Local Measures

Let's start with the first distinction in the metric system. We define:

  • Global measures are the metrics used to set goals and analyze the performance of the organization as a whole

  • Local measures are the metrics used to set goals and analyze the performance of each sub-unit down to individuals

Since global metrics cannot always effectively measure the performance of an individual sub-unit, the local metrics system is used as a set of measures to break down the overall corporate objective into intermediate, measurable sub-objectives that are instrumental in achieving it.


2. The pitfalls to manage when drawing the control system and its metrics

The design of the control system, and the set of metrics that define it, is a complex activity. Let's start by saying that an incorrect format is the source of many problems that afflicts almost every organization.

We want to draw attention to some side effects, from which significant undesirable effects can result if they are not adequately managed during the design phase.

2.1 Conflicts between metrics and loss of harmony

“Tell me how you measure me and I will tell you how I will behave. If you measure me illogically, don't be surprised of illogical behavior” - Dr. E.M. Goldratt

The first thing to pay attention to when designing or reviewing an existing model is to respect the principles of coherence and harmony between the different metrics and how they drive toward the objectives that they must not only measure but also, above all, stimulate.

The complexity lies in creating a set of local metrics that:

  • Are consistent with the global top-level metrics

  • They are in harmony with each other and with the goals of other organizational sub-units, creating the least amount of conflict and decision-making trade-offs.

To give you an idea, let's use a simple example. Let's assume that our organization, which we call "ASSOCIATION FOR PROFITS," is organized into two departments with specific responsibilities:

  1. THE REVENUE DEPARTMENT: whose head is mandated to the task of maximizing the revenue stream for the organization and therefore is measured with a metric of Total Net Revenues

  2. THE COST DEPARTMENT: whose manager is tasked with minimizing all corporate costs, including the operating expenses of the Revenue department, and is measured with a metric of Total Operating Expenses.

The overall corporate goal is to achieve maximum potential profit.

While the objectives assigned to the two entities respect the principle of consistency with the overall goal, the two local objectives can easily conflict, creating situations of non-harmony.

Conflict cloud

The loss in harmony depends not (only) on the choice of metrics, but (mostly) on the way of interpreting and implementing them with respect to the choice of the maximization equation

We have already explained that at the root of the "divide and control" organizational models (be they Divisional, Functional, Matrix, etc.), lies a deterministic and mechanistic vision of the company, whose basic assumption is that the performance of the individual organizational sub-units is additive.

Returning to our example, a vision in which the revenue and cost department's performance add up independently to achieve the profit equation.

"There is nothing more flawed than the assumption, which underlies the vast majority of control systems models, that the performance of the whole is equal to the sum of its parts. The reality is vastly different."

What is commonly overlooked by organizational models are interdependencies; new properties can arise from the interaction between parts of the organization.

Suppose the Cost Department, to prove itself exceptionally effective and achieve the extra MBO associated with reaching 120 percent of its target, "instead of just cutting out the fat it gets to cut down on the meat," in an interdependent system. In that case, it might happen that the Revenue Department suffers in capacity to produce its result. For example, a cost reduction of X could generate a revenue reduction of 2X, with the net effect of a decline in our profit equation.

Loss of harmony between different metrics occurs whenever two measures place entities, managers, and people in the conflict between one goal and another.

Conflict does not necessarily arise only between different entities and functions. Still, it can occur within the same entity and the same manager when measured against conflicting sub-objectives (such as working with zero inventory and maintaining high production efficiency).

Such conflicts can cause paralysis, inertia, and, most importantly, the search for compromise solutions instead of win-win solutions.


2.2 The "measurement disease."

Another pitfall in designing the metrics system is getting caught up in the illusion that the more the dashboard is crowded with indicators, the more we are in control.

A wide variety of measures are set in managerial control models, which set targets to coordinate and control every function and process:

  • margins on the standard cost of sales to measure and control sales functions

  • production efficiency metrics and variances from typical product cost to measure manufacturing

  • variances in standard cost from target cost to measure R&D

  • metrics on the unit cost of transportation to control logistics

  • metrics on non-quality costs

  • etc

The reality is that the proliferation of local metrics and targets only pushes management more vehemently to focus on its outcome, even at the expense of the overall goal, going on to create a multitude of opportunities for conflict already at the level of individual metrics, as well as at the stories of their implementation and interpretation. We call it the measurement disease.


3. The approach to measures in the Theory of Constraints

We will now discover how the Theory of Constraints, by analyzing at the root the rules governing the performance of a complex system, allows us to identify the principles for setting up an effective control system and metrics framework both for making decisions and for analyzing the feedback provided by the system, solving the root causes of the problems and undesirable effects that occur when incorrect measurement models are employed.

Free subscribe to our download center to read the full articles with its extra:

  • 3.1 The real levers of performance in the world of complex systems

  • 3.2 The TOC approach to restoring harmony

  • 3.3 The TOC measurement system

  • 3.4 How to measure constraint and non-constraint functions

  • 3.5 The choice of measures

  • 3.6 Measures must be financial

  • 3.7 Metrics and decision making

  • 3.8 Metrics and organization


“We are drowned in oceans of data; nevertheless, it seems as if we seldom have sufficient information” Dr. E.M Goldratt

What is information? Information is the answer to a specific question.

The quality of the information depends not only on the available data but essentially (and above all) on the quality of the question that is asked and for which an answer is requested. In the face of a poorly formulated question, you will always receive an incorrect or incomplete answer.

The effectiveness of the information depends on the use that must be made of the answer obtained: well-formulated question, correct answer. Still, the information is used to do something for which the information is not a necessary and sufficient condition to get the expected result.

The metrics of the control system represent the questions that are systematically asked to receive feedback on the progress of business processes and the checklist against which to evaluate the effectiveness or otherwise of a decision.

Since the metrics system affects the decision-making process and provides feedback on what to do (and what not to do), setting up a correct performance measurement model is a fundamental (necessary) step in promoting the improvement of business performance.

We want to emphasize that the design and implementation of an effective system of metrics:

  • It cannot be limited to a mere intervention in the information systems that produce the measurements of the indicators from the raw data.

  • it is not even a very intervention in the set-up of business processes

To make the system of metrics really effective it is essential to work also (and above all) on the following fronts:comprendere perché oggi si utilizzano certe metriche, e capire a quali paradigmi esse fanno riferimento

  • understand why specific metrics are used today, and understand which paradigms they refer to

  • understand the wrong paradigms and replace them with new ones

  • identify metrics that need to be abandoned and new ones that need to be introduced

  • align and make coherent global measures and local measures

  • incorporate the system of metrics into the evaluation processes and planning and decision-making processes, becoming the standard practice and the new DNA of the company

  • align organization and design of metrics to balance responsibility and authority

  • intervene in information systems to implement the algorithms necessary for the calculation of reference KPIs


We at Real Throughput, with our thirty years of experience in the Theory of Constraints, Lean and Six Sigma, APICS, and Business Design & Transformation have the know-how and expertise in the field to help corporate leadership question, design and implement a new system of performance management and effective decision-making metrics, able to connect global strategic objectives to the local goals of the organizational units, up to design information systems to support Business Control Towers and simulation models for scenarios to support decisions.

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