Tag Archives: computer-assisted organizing

Applying industrial engineering to information technology

This post is part of my collaborative research with Shinsei Bank on highly-evolvable enterprise software.  It is licensed under the Creative Commons Attribution-ShareAlike 3.0 license.  I am indebted to Shinsei Bank for supporting this research and to Jay Dvivedi for mentoring me in the art of enterprise systems.  All errors are my own.

The fourth edition of Herbert Simon’s Administrative Behavior contains a brief section titled “Applying information technology to organization design”.  In the industrial age, Simon says, organization theory was concerned mainly with how to organize for the efficient production of tangible goods.  Now, in our post-industrial society, problems of physical production have diminished in importance; the new challenge is how to organize for effective decision-making.  Simon characterizes the challenge as follows:

The major problems of organization today are not problems of departmentalization and coordination of operating units.  Instead, they are problems of organizing information storage and information processing–not division of labor, but factorization of decision-making.  These organizational problems are best attacked, at least to a first approximation, by examining the information system and the system of decisions it supports in abstraction from agency and department structure. (1997, 248-9)

In essence, Simon proposes that we view the organization as a system for storing and processing information–a sort of computer.  Extending the computer metaphor, organizations execute software in the form of routines (March and Simon call them performance programs).  Department structure, like the configuration of hardware components in a computer, has some relevance to the implementation of decision-making software, but software architects can generally develop algorithms without much concern for the underlying hardware.

Continue reading

Computer-orchestrated work

This post is part of my collaborative research with Shinsei Bank on highly-evolvable enterprise software.  It is licensed under the Creative Commons Attribution-ShareAlike 3.0 license.  I am indebted to Jay Dvivedi and his team at Shinsei Bank for supporting this research.  All errors are my own.

In my research on computer-assisted organizing, I set out to understand how computers alter the fabric of organizations.  Here’s how I framed the problem in my dissertation:

In the computer age, complex information processing tasks are divided between humans and computers.  Though designed and developed by humans, computers are autonomous agents that function as independent decision-makers.  The dynamics of electronic information processing influence the dynamics of organizing and organizations in ways that cannot be understood in purely  human terms. (Brunner, 2009)

My dissertation focused primarily on two aspects of this transformation: how computers drive further specialization in information processing work, and how computer-assisted work increases business scalability.  A third aspect of the transformation had been on my mind ever since my days as a management consultant: it seems that computers and people are trading places within organizations.

In the past, humans created organizational structure through their patterns of interaction, while computers were plugged in to this structure to perform specific tasks. Increasingly, these roles are reversed: computers create organizational structure, while humans plug in to the computer system to perform specific tasks.  Shinsei Bank’s mortgage loan operations provide an elegant example of the phenomenon. Rather than human credit approvers managing the loan application process from beginning to end and using computers to perform calculations or look up policies, a loan application system manages the process, calling on human appraisers, data entry clerks, analysts, or supervisors to provide input as necessary.

In Jay’s words, the computers orchestrate the work.  The Oxford English Dictionary defines orchestrate as follows:

To combine harmoniously, like instruments in an orchestra; to arrange or direct (now often surreptitiously) to produce a desired effect.

The word seems apt. In computer-orchestrated work, computers arrange and direct business processes in order to “combine harmoniously” the work of individuals.  Much like an assembly line, computer-orchestrated work enables individuals to focus on simple, well-defined tasks, while computers handle the coordination and integration of these fragmentary outputs. As bureaucracy1 eliminated the reliance of organizations on specific individuals by defining roles, so computer-orchestrated work enables organizations to survive without the patterns of human interaction that define and sustain the structure of traditional organizations.

Computer-orchestrated work may greatly increase organizational performance. By lowering to nearly zero the marginal cost of coordination and integration, computer-orchestrated work makes possible greater specialization, which accelerates learning and increase efficiency. Moreover, computer-orchestrated work lowers the costs of monitoring and metering, potentially reducing agency costs. Computer-orchestrated work is easier to analyze and modify, which facilitates innovation and increases the returns to highly-skilled human labor (c.f. Zuboff, 1989). Although the design challenges are significant, computer-orchestrated work may be an essential tool for creating more intelligent organizations.

1In the Weberian sense, as a highly effective organizing technology.

Insourcing at Apple

In my doctoral dissertation, I develop a theory of computer-assisted organizing that links the rise of computer systems to the shift from integrated organizational capabilities to decentralized capability ecosystems.  Although I believe the predictions of the theory probably hold true in aggregate, Apple’s recent move to bring chip design in-house illustrates how firm-level strategic considerations influence the division of information processing tasks across ecosystem participants.  Presumably Apple won’t in-source all chip design: they’ll focus on domains where they can develop capabilities that strongly complement the firm’s software and hardware design.