The debate between shareholder primacy and stakeholder theory concerns the legal obligations of corporate directors. Introduction A corporation is never just a machine for making money. It is a legal institution, a social system, and a vehicle for allocating power, risk, and responsibility. That is why one of the most important debates in corporate governance continues to divide scholars, executives, regulators, and investors: should corporations exist primarily to maximize shareholder value, or should they balance the interests of all the people and institutions affected by their actions? This debate is commonly framed as shareholder primacy vs. stakeholder theory. Shareholder primacy says the corporation's central obligation is to its owners, the shareholders. Stakeholder theory says the corporation owes duties to a wider circle of affected parties, including employees, customers, suppliers, creditors, communities, and sometimes society at large. This is not a purely academ...
This post examines production processes and throughput. Throughput is the rate at which a system produces output, and the central question is why some firms can increase it while others encounter a capacity ceiling that is difficult to identify. The analysis is tested against Toyota's production system and Safaricom's service and digital operations.
By Kateule Sydney — Researcher and Writer | Last Verified: 2026-10-01 | Published by Kat-Syd Resources Hub
Throughput as an operating system: process, capacity, and flow
Table of Contents
1. Process Types and When Each Applies
Process types classify production and service systems by the volume of output and the degree of customisation. Nigel Slack, Alistair Brandon-Jones, and Nicola Burgess, in Operations Management, present process types in relation to volume and variety. Robert Hayes and Steven Wheelwright developed influential frameworks for relating process choices to competitive strategy. Operations management literature commonly uses these process categories to explain how different operating configurations fit different volume-variety conditions.
The five process types are:
- Project — one-off, highly customised output (construction, consulting engagements)
- Job shop — low volume, high variety, made to order (custom furniture, bespoke software)
- Batch — moderate volume, moderate variety, produced in lots (specialty chemicals, bakeries)
- Mass or line — high volume, low variety, sequential operations (automotive assembly, electronics)
- Continuous — very high volume, very low variety, non-stop flow (oil refining, chemical processing)
The choice of process type is a strategic decision, not only a technical one. High-volume, low-variety products often favour line or continuous processes because repetition and standardisation can support high productivity and lower unit costs. Low-volume, high-variety products are generally better suited to flexible processes such as job shops or smaller batches. When the process configuration is fundamentally mismatched with the product or service strategy, incremental operational improvements may not be sufficient to close the gap.
The volume-variety relationship produces four tendencies:
- Volume-variety relationship — higher volume generally favours greater standardisation, while higher variety generally requires greater process flexibility. Advances in modular design and flexible manufacturing can reduce this trade-off
- Capital intensity — line and continuous processes are often capital-intensive; job shop and project processes are often more labour-intensive
- Flexibility — lower-volume processes tend to be more flexible; higher-volume processes tend to be more efficient
- Unit cost — unit costs often decline as volume increases because fixed costs can be spread over more units and processes can become more efficient. However, high variety and complexity can offset some of these gains
Process type constrains what is possible operationally. A firm can improve within its process type, but changing process type requires a strategic decision that affects capital investment, workforce skills, and product strategy simultaneously. Firms that recognise the constraint and redesign around it can move faster than firms that treat the process type as fixed while trying to improve their way out of a mismatch.
2. Capacity, Throughput, and Bottlenecks
Throughput is the rate at which a system produces output. Capacity is the maximum sustainable output that a system can achieve under specified operating conditions over a defined period. A bottleneck is the resource or process constraint that limits the system's achievable throughput under the relevant operating conditions. Eliyahu Goldratt, in The Goal (1984) and Theory of Constraints (1990), developed the constraint-based logic that operations scholars still use. Goldratt held that no system can produce more than its constraint allows, and that improving non-constraining stages may produce no increase in total output.
Throughput management rests on four concepts:
- Throughput — units of output produced per unit of time
- Capacity — maximum sustainable output under defined operating conditions and a defined time horizon
- Bottleneck — the resource or process constraint that limits the system's achievable throughput
- Capacity utilisation — the ratio of actual throughput to maximum capacity
The mechanism can be stated simply: every system has at least one binding constraint, and that constraint determines the throughput ceiling for the system. If the constraint runs at full capacity, the system reaches its ceiling. If the constraint loses time to downtime, changeover, or defects, the whole system loses throughput. The managerial implication is counter-intuitive. Firms should manage the constraint with care, protect it from disruption, and avoid over-investing in non-constraining stages. Once a constraint is relieved, a new constraint emerges elsewhere, and the process repeats. Capacity expansion decisions should target the current constraint, not the stage that is easiest to improve.
Goldratt's five focusing steps are the standard sequence:
- Identify — identify the system's current constraint or bottleneck
- Exploit — make the best use of the existing constraint without major investment
- Subordinate — align other processes and resources with the constraint's requirements
- Elevate — increase the capacity of the constraint when exploitation is insufficient
- Repeat — after the constraint changes, return to identification and continue the cycle
Throughput improvement is a systems problem, not a local problem. Improving a non-constraining stage may not increase system throughput. Increasing the capacity of the current constraint can increase throughput when the constraint is genuinely limiting system output and no other constraint becomes binding first. That logic is what makes the theory of constraints operationally valuable, and it is the logic that many firms fail to apply because their performance metrics reward local efficiency over system throughput.
3. Lean Flow and Waste Elimination
Lean production is an operating philosophy focused on creating customer value, improving flow, eliminating non-value-adding activity, reducing variability, and pursuing continuous improvement. Lean originated in the Toyota Production System and was formalised for Western audiences by James Womack, Daniel Jones, and Daniel Roos in The Machine That Changed the World (1990). Masaaki Imai's work on kaizen provided the continuous improvement engine that sustains lean over time.
The eight forms of waste are:
- Overproduction — producing more than is required or producing it before it is needed
- Waiting — idle time caused by unbalanced process stages or delayed inputs
- Transport — unnecessary movement of materials or products between stages
- Over-processing — doing more to the product than the customer requires
- Inventory — excess stock at any stage of production
- Motion — unnecessary movement of people or equipment within a stage
- Defects — work that has to be re-done, scrapped, or corrected
- Unused human talent — failing to use the knowledge, skills, creativity, and problem-solving ability of employees
Lean is easier to state than to sustain. The mechanism is simple: identify value from the customer's perspective, map the value stream, make the value-creating steps flow, let the customer pull value, and pursue perfection continuously. Lean seeks improvement by reducing waste, improving flow, stabilising processes, and continuously solving problems. Just-in-time delivery, kanban scheduling, andon problem signalling, and standard work are the tools that support these principles. Lean is not a one-time project. It is a management system that requires continuous attention from leadership and continuous involvement from front-line workers.
The five lean principles are:
- Value — define what the customer actually values and is willing to pay for
- Value stream — visualise every step, delay, and information flow in the process
- Flow — arrange value-creating steps so product moves without interruption
- Pull — produce only what is needed, when it is needed, by the next downstream stage
- Perfection — pursue continuous improvement as a permanent discipline
Lean is a systemic commitment, not a toolkit. Firms that adopt lean tools without changing management philosophy often see initial gains that erode over time. Firms that embed lean into management systems and organisational routines are better positioned to sustain improvement over time than firms that treat lean as a short-term collection of tools. That distinction is the one that matters most in practice, and it is the one that many firms underestimate.
4. Throughput Metrics and Operating Discipline
Throughput metrics are the operating measurements that reveal how well a production or service system is performing. Goldratt's Theory of Constraints uses throughput, inventory, and operating expense as global measures of system performance. These can be supplemented with operational measures such as quality yield, lead time, and responsiveness. Slack, Brandon-Jones, and Burgess extend the metric set to include customer-facing measures such as delivery reliability and quality conformance.
The core metrics include:
- Cycle time — the time taken to complete one unit of output at a given stage
- Lead time — total time from order to delivery across the whole process
- Throughput rate — units produced per unit of time
- Capacity utilisation — actual output as a percentage of maximum capacity
- First-pass yield — percentage of output that passes quality checks without rework
- Overall equipment effectiveness — availability multiplied by performance multiplied by quality
Metric selection is not straightforward. Throughput metrics must be aligned with system objectives, not local efficiency. A plant that maximises machine utilisation may produce excess inventory that increases holding cost and hides quality problems. A plant that measures throughput rate without measuring first-pass yield may report high output while generating rework that consumes capacity downstream. Effective practice is to measure the system holistically, including throughput, lead time, and quality, rather than optimising any one metric in isolation. Overall equipment effectiveness is useful for evaluating equipment effectiveness, but it should not be treated as a complete measure of system throughput or business performance. From a throughput perspective, utilisation of the constraint generally deserves greater managerial attention than utilisation of non-constraining resources.
The five system-level metrics that should anchor the dashboard are:
- System throughput — finished goods or services produced per period, measured at the system level
- Inventory — work in process and finished goods held at any point
- Operating expense — the cost of converting inventory into throughput
- Quality yield — the proportion of output that meets specification without rework
- Responsiveness — the ability of the system to change output in response to demand shifts
Metrics are a management choice. Different metrics produce different behaviours. A firm that measures the right combination of throughput, quality, and responsiveness will make better operating decisions than a firm that measures only local efficiency. The metric set itself should change as the operating environment changes, because a metric that drove the right behaviour in a stable market can drive the wrong behaviour in a volatile one.
5. Toyota and Safaricom
Two public illustrations of process and throughput design are Toyota, whose production system is a benchmark for line-based throughput, and Safaricom, which operates a mixed service architecture that combines high-volume digital services with more variable customer-facing interactions. Although the concepts in this post originated largely in manufacturing operations, process type, capacity, bottlenecks, flow, and throughput also apply to many service operations.
Toyota operates a hybrid production architecture. Core models are assembled on line processes with high volume and standardised platforms, while customisation is layered in through modular design and option packages. The system runs on line balancing and heijunka, which deliberately smooths production to reduce the variability that would otherwise disrupt the constraint. Kaizen operates as a daily practice, and Toyota has long encouraged employees to identify and implement improvement ideas as part of that culture. Toyota remained one of the world's largest vehicle manufacturers in 2025, with production on the order of ten million units across its group. The Toyota Production System has evolved through decades of continuous improvement, and its large production volume provides an illustration of how a highly developed production system can operate at scale.
Safaricom operates several service configurations simultaneously. Network infrastructure and field operations require significant flexibility and vary with the technical complexity of each intervention. M-PESA processes a very high volume of standardised digital transactions through highly automated service processes. Customer service involves a higher degree of interaction and variation than automated transaction processing, requiring more flexible service processes. Safaricom monitors operational indicators such as network performance, transaction reliability, and service availability. Its different services have different operating characteristics and therefore require different process controls and performance measures.
The comparison illustrates how different organisations can use different process configurations in response to differences in volume, variety, technology, and customer requirements. In both cases, process type was matched to the volume and variety profile of what the organisation produces. Toyota standardised where variety could be absorbed through modular design. Safaricom segments different functions into different process configurations rather than forcing them all through one. In both, throughput was managed as a system property rather than a local one. Toyota protects the line's constraint by smoothing demand. Safaricom's services require differentiated process controls and metrics across different functions. In both, the metrics are designed to surface problems rather than hide them. Toyota treats the surfacing of problems as a healthy signal, and Safaricom's operating model relies on transparent performance indicators.
Neither firm achieved its throughput performance simply by adopting a template. Toyota built the Toyota Production System over decades. Safaricom operates within the specific conditions of the Kenyan telecommunications market. The frameworks describe the principles. The design discipline is what makes them work.
Judgement
The Toyota and Safaricom cases illustrate a useful proposition: throughput is both a design and an operating outcome. Process architecture determines many of the system's structural limits, while operating discipline determines how effectively those limits are used. Firms that treat throughput as something to be optimised within an existing process architecture can hit a ceiling. Firms that also treat throughput as a design problem and redesign the process architecture around the volume and variety profile of their product or service can find gains that were not available through operational improvement alone.
My detailed conclusion is this. The process-type framework and the volume-variety relationship are useful starting points, but some conventional treatments undersell three things. First, they can undersell how often firms operate more than one process type. Large service organisations can contain multiple process configurations simultaneously, particularly when they provide different services with different levels of standardisation and customer interaction. The framework is a design vocabulary, not a classification system, and firms that treat it as a classification miss the design opportunity. Second, they can undersell how much throughput is determined by constraint management. Goldratt's constraint logic has been taught for forty years, and yet many firms still optimise non-constraining stages because those are the stages whose metrics they can see. The bottleneck is often the point at which targeted improvement can have the greatest effect on system throughput, provided that the constraint is correctly identified. Third, they can undersell the trade-off between throughput and responsiveness. A firm that maximises throughput in a stable market may lose responsiveness when the market shifts, and a firm that maximises responsiveness may lose throughput in normal times. The design discipline is to hold both in balance, and the balance point moves as the market moves.
The strongest counterargument to my position is that throughput is fundamentally an operational achievement, and that firms with excellent operating discipline outperform firms with sophisticated process design. I take that objection seriously. In many firms, the difference between average and excellent throughput comes from execution, not architecture. But the objection misses the point. Operating discipline can only extract what the architecture allows. A firm with excellent discipline inside a poorly designed process still hits the architectural ceiling. The firms that outperform over decades are the ones that hold both design and discipline together.
My recommendations follow from that conclusion:
- Match process type to product strategy explicitly — and recognise that changing process type is a strategic decision that affects capital, workforce, and product simultaneously
- Identify the constraint and manage it as the system's throughput ceiling — protect it from disruption and avoid over-investing in non-constraining stages
- Treat lean as a management system rather than a toolkit — firms that adopt the culture sustain improvement, and firms that adopt the tools alone often do not
- Design the metric set to surface problems rather than hide them — and update it as the operating environment changes
- When you operate multiple process types in one organisation, segment the metrics and operating disciplines accordingly — rather than forcing every function through the same framework
Throughput should not be treated solely as an operational metric. It is also shaped by process design. Process types define the structural options, bottlenecks define the system's constraints, and operating discipline determines how effectively the available capacity is converted into output.
References
- Slack, N., Brandon-Jones, A., & Burgess, N. Operations Management — Pearson
- Toyota Production System — Toyota Global
- Sales, Production, and Export Results — Toyota Global
- Safaricom FY2025 Annual Report and investor materials — Safaricom
- Womack, J., Jones, D., & Roos, D. (1990). The Machine That Changed the World — Free Press
- Goldratt, E. M. Theory of Constraints — TOC Institute
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Written by Kateule Sydney — Researcher and Writer
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