Defined vs. Empirical Process Control: Choosing the Best Approach

Barry M. Milteer is a highly skilled Business, IT and Operations Consultant, and Project Management Professional with 25 years of multiplatform enterprise project management (EPM) and enterprise resource planning (ERP) experience including business case development, requirements management, solution selection, proof of concept (POC), installation/setup, configuration, deployment, and training.

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Topics: Agile, Cost Management, Quality, Schedule Management, Scope Management, Knowledge Shelf

Abstract
Project Management Professionals (PMP®s) should be familiar with the Triple Constraint Theory, which defines the three major constraints – time, costs and scope – that project managers must consider when managing projects. The Triple Constraint Theory is concerned with the overall impact to project quality that results from the trade-offs project managers make among these limitations (see Figure 1).

Figure 1: Triple Constraint Theory

When we consider the impact of the three major constraints above in terms of environmental complexity, two other related project management concepts come into play: Defined and Empirical Process Control. These high-level concepts are important to understand when choosing the best approach – agile or predictive – project managers should use on a project.

This article draws on well-known, basic project management concepts to introduce the high-level project management concepts of Defined and Empirical Process Control. It also attempts to contrast them and suggest how they might be used by PMPs in practice.

The Stacey Complexity Model (Adapted)
I have developed an adaptation of the Stacey Complexity Model[1]^,[2],[3] to recommend project/product development approaches based on degrees of environmental process complexity (see Figure 2 below). Let’s explore this model in more detail.

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