From the industrial age until now, the nature of the work being performed in modern societies has totally changed in nature. Unfortunately and far too pervasively, work’s estimators have not adapted.
In this paper, we aim to make project teams aware of not only optimal techniques but also the tendency to abandon them in the heat of their work without even realizing it. Without some form of reasonable estimation, much modern work would be too risky even to attempt. Failing projects commonly have poor estimation as a root cause. Only with serviceable estimates can effective budgeting and feature selection and trades be made.
We give clarity to this problem and its origins and propose solutions by examining two primary work types, knowledge work and task work, and address the issue of projects that incorporate both types. We present the key related concepts of continuous estimation, estimation in size versus time, and relative versus absolute estimation. We illustrate the value of each when applied to knowledge work.
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Even when these types of estimation are done well initially, constant diligence is necessary to maintain the discipline of their application, a discipline too often lost. Without it, many projects are at serious risk of cancellation or failure.
The Purposes of Estimation
Estimation is an indispensable element of project work. The end result is a concept of the effort required to do each work element, which can be translated into financial terms for project-feasibility determination and resource-allocation projections. However, when done well, a much overlooked and invaluable benefit is the (perhaps forced) discussions that result in greater understanding of the work at hand. Fortunately, the same techniques invaluable in producing great estimates also encourage collaboration and understanding.
Although lean thinking considers estimating wasteful, in the authors opinion the approach used there is perfectly in synchronization with the agile movement’s estimations in relative terms, which are then adjusted to the actual rate of work progress.
Vital Distinctions Between Types of Work
Cost overruns continue to plague industry with serious and sometimes fatal results for the sponsoring organization, the particular project, or perhaps the current career of the project manager. To get to the root of many of today’s work challenges, we must begin with the realization that not all work is the same. Let’s distinguish between two types of work that must be treated and estimated very differently: knowledge work and task work. Our primary focus is on the knowledge work that makes up the bulk of current project work as opposed to product work.
Knowledge work is work that usually requires “thinking.” Knowledge workers are considered people who “think for a living.” For example, doctors, lawyers, software developers, engineers, teachers, nurses, financial analysts, and architects perform non-routine tasks that require some level of thinking and creativity. As businesses have increased their dependence on information technology, the number of fields in which knowledge workers are necessary has increased dramatically.
The key differentiation between knowledge work and task work is its primary core of non-routine problem solving that requires a combination of convergent, divergent, and creative thinking.
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The Management of Knowledge Work
The traditional plan-based approach to work isn’t flawed in and of itself; it just isn’t suitable for managing knowledge work. In the task-work-based construction industry, the plan-based approach is suitable. The blueprints, which are the requirements, are fixed and probably won’t change substantially while the building is being built. Therefore one can estimate how long it will take to build the steel pillars, pour the concrete, and so forth. The reason why the traditional plan-based approach is suitable for the construction industry but not a knowledge industry like the software industry comes back to the difference between the way we control the process of doing knowledge work versus the way we control the process of doing task work.
There are two major approaches to controlling any process:
- The defined process control model
- The empirical process control model
The defined process control model requires that every piece of work be completely understood. Given a well-defined set of inputs, the same outputs are generated every time. A defined process can be started and allowed to run until completion, and it will always produce the same results. The defined process control model provides and exercises control through planning, coordination, and control. The defined process control model is usually suitable when:
- No creativity or “new thought” is needed during execution;
- There are mostly predictable actors that you can coordinate and control; and
- It is possible to identify, define, schedule, and order all the detailed activities.
The empirical process control model, on the other hand, is suitable for processes that are imperfectly defined and that generate unpredictable and unrepeatable outputs. An empirical process cannot be rehearsed but will provide a great deal of learning, experience, and discovery that may or may not be relevant the next time the process is executed. The empirical process control model provides and exercises control through frequent inspection and adaptation. The empirical process control model is usually suitable when:
- Creativity and “new thought” are needed during execution;
- There are mostly unpredictable actors that you cannot coordinate or control; and
- Execution cannot be planned in detail but rather by inspection and adaptation.
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For many years, the majority of people involved in knowledge work have based their control model on the defined process. But any form of knowledge work doesn’t necessarily generate the same output every time given a certain input. Creativity and the human thought process are unpredictable by nature.