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Differentiating Production Processes from Functional and Administration Processes



The effective implementation of Project Production Management (PPM) requires a clear understanding of production processes within a given project production system – how they transform information and materials into outputs using capacity contributors (labor, equipment, space) and based on specific objectives, policies and requirements. This brings not only a necessary process perspective to production, but also forms the basis for production system optimization, control and ongoing performance improvement.

However, experience tells us that those adopting PPM are often influenced by Era 1 and Era 2 thinking and associated frameworks, which gravitate towards functional and administration processes rather than actual production processes. The functional / administration perspective gives a myopic view of how work is executed compared with the production perspective, which emphasizes effective engineering, fabrication, assembly, delivery and installation. Therefore, the purpose of this paper is to provide a clear definition of production processes and their components, how best to represent them for design, technical analysis, control and improvement, and in so doing, enable differentiation from functional and administration processes used in traditional Project Management.

Keywords: Capacity, Cycle Time, Flow, Inventory, Process, Production, Work-in-Process



The term ‘process’ is widely used across all industries including engineering and construction. Underlying mental models come at play when interpreting not only what “process” means, but also dictate how processes are defined, represented and used, resulting in a myriad of options to display the configuration of a process and its application. It is not the purpose of this paper to analyze these many configurations, but rather to explore what influences general thinking on processes and to concentrate on what we are calling here “production processes” and their components. Of particular interest is the ability to capture how work flows through a production process considering not only when capacity is allocated to work (doing the work), but also considering when work waits for capacity (not doing work), as the latter results in work-in-process (WIP) which contributes to longer cycle times as defined by queuing theory.

The Influence of Era 1 and 2: People are Production-Process Blind

Shenoy et. al. [1] introduced the output of PPI’s research on three distinct eras of project delivery: Era 1 – Productivity, Era 2 – Predictability and Era 3 – Profitability.

They concluded that a series of industry practices concentrate primarily on trying to make workers more productive – this thinking is labeled as Era 1 (e.g., time on tools, motion studies, use of Gantt Charts). It should not be confused with getting more throughput out of a production system, as workers becoming more productive does not necessarily result in higher system throughput as WIP is not accounted for.

They also concluded that a different set of industry practices was conceived to increase predictability of project outcomes including cost and schedules. They labeled this thinking as Era 2 (e.g., Earned Value Management, Work Breakdown Structures, the development of schedules in support of reporting and forecasting of project progress – Project Controls, Advanced Work Packaging etc.). It is important to highlight that Era 2 methods should not be confused with meeting cost and schedule targets, but rather being able to predict what may occur even if the predictions result in significant cost overruns and schedule delays (e.g., you can predict to be late, hence you are predictable).

Aligned with the thinking in this paper, Shenoy et. al. [1] discussed how a third era of project delivery evolved in response to the claims and disputes coming out of Era 2. Era 3 combines a series of practices that enable viewing a project as a production system through the application of Operations Science [2] principles and methods. By focusing on project production rather than functional and administration processes, Era 3 unlocks hidden value in project value chains including the ability to optimize, plan, control and improve project production processes that combine knowledge and craft work.

The combination of Era 1 and Era 2 practices results in a delivery approach with significant gaps. Era 1 confers a myopic view driven by productivity programs. The desire of managers for their projects to become more predictable motivates Era 2 methods as they report progress to upper management (and ultimately to shareholders). Unfortunately, this combination has had a profound influence on how process definition, execution and even improvement is approached in today’s projects, from small and simple, to large, critical and complex projects.

The combined influence of Era 1 and Era 2 practices goes beyond craft work, and is being extended even to knowledge work such as in engineering and support processes. The Era 1 focus on productivity looks to identify only when work is being done and ignores when work waits and the implications of unnecessary WIP levels to performance. Additionally, the contribution of Era 2 and the drive for predictability has pushed project teams to perform serious simplifications of reality as the means to facilitate predictability analysis, partially or fully ignoring true levels of complexity and dynamics that are common in project value chains.

All of this has resulted in a situation where the majority of the engineering and construction industry, even those contracted to perform engineering, fabrication, assembly, installation and commissioning work, operate under the illusion of fully understanding project production processes, and therefore, are underestimating the impact and unintended consequences of their decisions to project performance.

This is of significant concern as people are becoming more and more production-process blind.

Functional and Administration Processes

An additional factor in this story is the fact that the advocacy of modern Project Management practices has served as an accelerator for all organizations involved in the delivery of capital projects to embrace and customize the forty seven functional and administration processes set as standard practice by the Project Management Institute (PMI) in its Project Management Body of Knowledge (PMBOK) [3]. Although these processes are probably a good summary of how to administer a project, they don’t include any aspects of project production. Even if many believe they do, the fact is that you cannot administer project production; rather, it needs to be designed, optimized, controlled and improved using robust technical frameworks as those provided by Operations Science [2].

The application of these processes without a robust production perspective can be disastrous for project performance. It is common to see procurement plans that ignore the implications of purchasing strategies to the creation of unnecessary levels of WIP on project sites and the associated unintended cost (e.g., double handling, use of space, obsolescence, preservation, etc.) as well as implications for the use of cash. It is also common to see project schedules that are re-baselined, not only once but several times, due to the impact of multiple sources of variability.

Along with the introduction of functional and administration processes, sometimes referred to just as business processes, came the need to map them. After a close examination of literature [7],[8],[9] on business processes and business process mapping, it can be concluded that there exists a strong focus on the sequence of steps with a clear objective of generating a diagrammatic representation of that sequence through a variety of flowchart formats or process maps. The emphasis, however, remains on capturing the correct sequential and parallel routings, decision points and triggering events. Not surprisingly, these are typical requirements in software development and automation, as these processes then become the basis of software programming. In other cases, there is a significant emphasis on information flows and data flows, but certainly little to no consideration of transformation of physical materials into outputs, acknowledgement of finite cycle times, work in process, or much less, the physical laws governing the interactions of the activities describing the work captured in a process map.

Figure 1. Project Management Process Groups and Knowledge Areas Matrix [3]

The Myth that CPM Schedules Represent Production

Many people in the engineering and construction industry recognize that functional and administration processes are not production processes. However, they operate under the assumption that project CPM schedules do provide an accurate view of project production, especially schedules that are labeled as Level 4 or 5, or even those recognized as short-term lookahead schedules.

This belief system has evolved over the years and is very strong in today’s capital projects world. Project professionals operate thinking that because a schedule exists: 1) work will occur as per the schedule, 2) the schedule reflects the work in the field, 3) project teams are capable of managing project production using the schedule, 4) field personnel will use the schedule for daily operations, and 5) if work is exposed to delays, schedules are not detailed enough, to name a few. Under this belief system, schedules become some sort of psychological insurance that creates the illusion of certainty and being in control. Unfortunately, this only lasts a short amount of time because then variability kicks in. Expressions such as ‘we don’t trust the schedule’, ‘we don’t trust the forecast’, ‘that schedule is for the owner’, ‘we are still working on the schedule (while work is being done in the field)’, are just symptoms of a production system out of control.

So, what has contributed to this belief system? History tells us that the use of today’s project schedules have been heavily influenced by several events including, but not limited to, the work done by Frederick Taylor and his assistant, Henry Gantt, as they developed a way to visualize how work flows in a 1910’s manufacturing environment (today, the engineering and construction industry uses Gantt Charts to represent schedules (Gantt, 1919)), the development of the Critical Path Method (CPM) by Kelly and Walker (Kelley & Walker, Critical-path scheduling and planning, 1959), (Kelley, Critical-Path Planning and Scheduling: Mathematical Basis, 1961) in the 1950s, and the influence of the U.S. Department of Defense and the introduction of the Earned Value Management method. This body of work has positioned the use of schedules as the basis for reporting and forecasting project progress. The obsession with being able to report and forecast progress has reached such limits that it is common to see project teams develop 3-4 week lookahead schedules using customized worksheets that capture types of work (e.g., piping, mechanical, electrical, instrumentation) and how much manpower gets allocated to each type. This turns into the basis of calculation for how much is burned versus earned, and for instance, the infamous Productivity Factor (burned / earned) used in oil and gas and industrial construction, which is driven by the goal of keeping it under 1.0. Short-term Lookahead Schedules ignore sequence, not to mention, all basic aspects of planning production.

In conclusion, current scheduling practices have become a necessary platform for Project Controls and its purpose of reporting and forecasting progress. However, this has also created the myth that schedules are an accurate representation of project production.

Project Production Processes

In its Glossary [10], PPI defines ‘production’ as the act of transforming or changing the shape, composition or combination of materials, parts, subassemblies or information to increase their value. At the same time, ‘process’ is defined as a set of one or more operations designed to transform a set of entities into another form to achieve a particular purpose resulting in production of a physical product or completion of a service.

Based on these definitions, we can define a project production process as the response to certain demand that transforms materials and information using capacity contributors – labor as in craft or knowledge workers; equipment as in construction equipment and engineering development systems; and space as in physical and virtual space – into physical or non-physical outputs, which could represent unfinished goods (queues) or finished goods (stocks). The connection between multiple project production processes working in response to a single or multiple demand signals represents a project production system. Under this premise, schedules represent the demand for the system, and the production system represents the supply in response to the demand. Schedules are therefore not a representation of the production system. To accurately represent the system and its production processes, and understand how it behaves, not only do we need to introduce new graphical means to capture and represent this transformation, but also how optimization and control is performed using different strategies, mechanisms, measurements, and tools, not using schedules.

As a production process consists of operations, we will use boxes to denote these operations. As each operation transforms the output of the preceding operation into outputs, we need to contemplate the existence of queues, which are simply unfinished work waiting to be processed and that we represent using triangles in between two operations. In addition to queues, stocks (information and/or materials) are required and positioned ahead of specific operations depending on the design of the production process. Stocks are graphically represented by a cylinder shape. The following figure provides a graphical display of this mapping language including definitions.

The application of this mapping language enables the ability to capture how work flows through a production process including not only when capacity is allocated to work (doing the work within an operation), but also when work waits for capacity (not doing work as work waits in a queue). The more the amount of work waiting in queues, the more work-in-process (WIP), which contributes to extending production cycle times as defined by queuing theory. Readers can explore the advantages of this mapping language for understanding production systems by using a software tool called Process Mapper made available by the Institute at its website [11]; additionally, this edition of the Journal provides a tutorial on how to use this tool. This way of capturing production processes may be antagonistic to many, as people focus mainly on capturing the doing, ignoring the not doing (e.g., queues). Bottom line is that the cost associated with a production process incorporates not only doing the work, but also not doing it. The price is not the final cost.

Figure 2. Project Production Process Mapping Language & Definitions

Units of Production and Standard Work Processes

The idea of standardizing processes is not new. When focusing on functional and administrative processes, many will standardize processes just to come up with a standard, so people follow the standard. Having a standard also allows for process automation through software programming.

Although the idea of standardizing processes also applies to production, the main objective is to be able to clearly define the start and end of cycle times and measure execution performance accordingly, so as to find ways to reduce cycle times. Also, operating through a standard sequence of work allows for variability reduction (based on Operations Science, variability cannot be eliminated) as standard processes become the basis for control.

But the definition of a standard sequence of work goes beyond just the identification of the operations in the production process. Defining standard processes goes hand in hand with defining the unit of production. One question is: what is the production process producing? For instance, in a foundations production system, we can distinguish several types of units of production depending on the system. Depending on the asset design, there may be a sub-production system for precast piles, with operations such as Drive and Crop. In this example, the piles production system operates based on a unit of production: a pre-cast pile. Similarly, another sub-production system may be the footings production system, which targets a finished footing including pedestals as the output; hence, the unit of production is a footing. Examples like this abound in engineering and construction, and in each case, the idea is that a unit of production moves through the standard production process, although literally, the unit of production does not physically move necessarily.

In addition to the standard sequence of work and the unit of production, production processes have batching rules. Depending on the design of the production system, different operations may have different process batches; in other words, how many units of production are processed at the same time. An operation may also have different rules for how batches of work are transferred or released from one operation to the next or to a final stock. The following schematic illustrates process and batching rules in production processes using a short pile production system as example.

Figure 3. Unit of Production, Process and Transfer Batches


Era 1 and 2 practices have a heavy influence in the engineering and construction industry. This has resulted in a strong belief system that 1) proposes the focus should be in productivity programs, 2) operates under the myth that as long as we have robust schedules, things will work as planned, and if not, new baseline schedules are developed, 3) puts significant emphasis on functional and project administration processes versus production, and 4) focuses on reporting and forecasting project progress. This belief system has moved people away from project production and optimization, which impacts the ability for even “experienced” project teams to think about and accurately represent project production processes, let alone effectively plan, integrate, control, execute and improve them.

This paper introduced a method to depict project production processes using an Operations Science framework. Understanding project production processes becomes the first step towards project production optimization and performance improvement in order for the engineering and construction industry to move beyond reporting and forecasting progress. If true and sustainable project profitability is desired, we must look at exactly how work is defined, designed, executed and improved, independently of who performs the work and any contractual boundaries.


  1. R. G. Shenoy and T. R. Zabelle, “New Era of Project Delivery: Project as Production System,” Journal of Project Production Management, Volume 1, pp. 13-24, 2016.
  2. W. J. Hopp and M. L. Spearman, Factory Physics (Third Edition), Long Grove IL, USA: Waveland Pr. Inc., 2011.
  3. Project Management Institute, A Guide to the Project Management Body of Knowledge (PMBOK) 6th Edition, Newton Square PA, USA: Project Management Institute, 2017.
  4. H. L. Gantt, Organizing for Work, New York: Harcourt, Brace and Howe, 1919.
  5. J. E. Kelley and M. R. Walker, “Critical-path scheduling and planning,” in IRE-AIEE-ACM ’59 (Eastern) Papers presented at the December 1-3, 1959, eastern joint IRE-AIEE-ACM computer conference, Boston MA, USA, 1959.
  6. J. E. Kelley, “Critical-Path Planning and Scheduling: Mathematical Basis,” Operations Research, no. May-June, pp. 296-320, 1961.
  7. M. V. Rosing, H. V. Schel, and A.W. Scheer, The Complete Business Process Handbook: Body of Knowledge from Process Modeling to BPM, Volume 1, First Edition, Elsevier Inc., 2015.
  8. M. Weske, Business Process Management: Concepts, Languages, Architectures, Third Edition, Springer, 2019
  9. M. Kirchmer, High Performance Through Business Process Management: Strategy Execution in a Digital World, Third Edition, 2017.
  10. Project Production Institute Glossary.
  11. S. Georgy, “Using the PPI Process Mapper Tool”, Journal of Project Production Management, Vol 3, Issue 4.