Ideas for Leaders #339

HQ Controls and the Speed of Strategic Decision-Making

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Key Concept

How do control mechanisms set by corporate headquarters in large organizations influence decision-making speed at lower levels? In this Idea, six types of corporate controls are identified, their effects on decision speed are discussed, and the key mechanisms accounting for these effects are outlined.

Idea Summary

The speed at which strategic decision-making takes place in an organization has been identified by many researchers as a critical factor for performance. Competitive business environments, shortened life cycles and increasingly global markets have only enhanced the importance of decision-speed. In many organizations, however, decision-making at lower levels, such as in strategic business units (SBUs), is constrained by structural and control requirements at the corporate level. How do these constraints affect their decision speeds?

In order to answer this question, researchers from institutions including the University of St. Gallen conducted two studies to explore how control mechanisms set by corporate headquarters in multi-business firms influence decision speed at SBU levels.

They define ‘corporate control’ as attempts to manage or influence the process, content and/or outcome of strategy-making, and that there are at least six types of corporate control that can affect SBU-level decision-making: goal-setting; extrinsic incentives; decision-process control; negative incentives; conflict resolution; and strategy imposition. Some of these can positively influence SBU decision speed (goal-setting, extrinsic incentives, decision-process control), while other types negatively influence it (strategy imposition), and still others have little or no effect (negative incentives and conflict resolution).

In addition, the researchers found that there are five mediating mechanisms that influence these relationships: transparency/alignment; outcome orientation; participation, trust and timely feedback. When corporate control has a positive influence on these five mediators, they in turn exert a positive influence on decision-making speed.

Methodology: In their first study, the researchers conducted 14 interviews through which they gathered information about strategy processes and corporate control and its relationship to decision speed in five different companies. Through these interviews, they derived the six types of corporate control, detailed above.

In the second study, they examined how and why these six types of corporate control influence the speed of SBU level decision-making. They first conducted a further 30 interviews with different participants than the first study but from the same companies, then used computer software to analyze and determine why certain corporate control types affect decision speed.

Business Application

Understanding the five mediators that affect corporate control helps explain why certain managers adopt different types of controls. Previous research on decision-making speed has focused on young and small firms, and found larger companies to be at a disadvantage when it comes to fast decision-making processes. These findings, however, suggest that size-related liabilities in large corporations can be mitigated and the speed of decision-making accelerated with an understanding of the factors at play.

Strategy imposition, negative incentives, and corporate attempts to resolve conflicts between SBUs do not appear to enhance decision speed. None of these produce any of the positive mechanisms attributed to other corporate control types. Instead, the latter two in particular seem rather reactive ways for corporate headquarters to exert control over SBUs.

Using the researcher’s taxonomy of corporate control types, in conjunction with their analysis of the micro-level mechanisms operating between control types and SBU decision speed, managers can avoid a potentially unnecessary layer of control systems.

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Authors

Institutions

Source

Idea conceived

  • November 2013

Idea posted

  • March 2014

DOI number

10.13007/339

Subject

Real Time Analytics