Wild horses sculpture at Drexel

Author: Susan

  • Wicked Problems

    Organizational Problems are Wicked Problems

    A wicked problem is one that is just too complex and messy (comprising multiple problem-elements) to be easily defined. As it can’t be defined, it can’t be resolved using regular analysis methods, such as those used to generate IT system requirements. Different stakeholders will define the problem in different ways, depending on the parts they have encountered in their work. The emergence of multiple problem-definitions as the problem is explored distinguishes “wicked” problems from the “tame” problems that organizational analysts and IT systems developers typically deal with. While tame problems can be defined in terms of goals, rules, and relate to a clear scope of action, wicked problems consist of many, interrelated problems, each with its own organizational scope and goals. As a result, wicked problems have vague, emergent goals and boundaries. Ways of framing wicked problems are negotiated among stakeholders who hold radically different views of the organization (Rittel & Webber, 1973).

    “It comes as no particular surprise to discover that a scientist formulates problems in a way which requires for their solution just those techniques in which he himself is especially skilled.”
    Kaplan, Abraham (1964) “The Age of the Symbol—A Philosophy of Library Education” The Library Quarterly: Information, Community, Policy, Oct., 1964, Vol. 34, No. 4 (Oct., 1964), pp. 295-304

    These types of problem are also known as systemic problems because we use systems thinking (a.k.a. systemic analysis) to resolve them. Systemic analysis methods use a “divide-and-conquer” approach to exploring problems. The sub-problems prioritized by various stakeholders are explored and debated across the wider group of change managers. Goals and potential solutions emerge as “the problem” is framed and re-framed in multiple ways over time, and across stakeholders. This process results in organizational learning, as stakeholders acquire an improved understanding of others’ perspectives across organizational functions and boundaries. Systemic analysis also allows change managers to explore the “knock-on” impacts of change, allowing them to appreciate conflicts and tradeoffs between perspectives and to predict the impact of changes to one area of the organization on other areas and functions.

    What are Wicked Problems?

    Wicked problems present as tangles of interrelated problems, or “messes” (Ackoff, 1974). Because these problems are so messy, they are defined by various stakeholders in multiple ways, depending on the parts that they perceive — which in turn depends on where they are in the organization, their experience and their disciplinary background.

    If you try to model a complex problem-situation, you will rapidly discover that any “system” of work consists of subsystems, the definition and scope of which depends on where the definer stands in the organization. To act upon a wicked problem, you need to understand the multiplicity of perspectives that various stakeholders take. Often, a single person will hold multiple perspectives depending on the role they are playing at any point in time. For example, I trained as an engineer, I was introduced to systemic analysis during my education, and I adopted a social science perspective as an academic. So I can happily (and obliviously) define any situation in three different ways, depending on which “hat” I am wearing when I do so!

    Wicked problems are so-called because they are not “well-structured” – that is, amenable to analytical methods of problem-solving. This means that analysts often experience difficulty in defining the problem that needs solving or selecting an appropriate technique to model the problem.

    “Successful problem solving requires finding the right solution to the right problem. We fail more often because we solve the wrong problem than because we get the wrong solution to the right problem.”
    Russel Ackoff (1974) Redesigning the Future. ‎Wiley.

    Wicked Problems Require Systemic Analysis

    As a result, Wicked Problems have a number of characteristics not found in the sorts of problems for which professional analysts and change-agents are typically trained. They are solved by trial and error, rely more on problem-negotiation than analysis, and need to be investigated, rather than analyzed. Any analysis imposes a model or structure that includes some aspects of the situation and excludes others, imposing an expectation that the elements found will be related in specific ways:

    “… it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.”
    Maslow, Abraham Harold (1966). The Psychology of Science: A Reconnaissance. Harper & Row.

    The bottom line is that, while most analysis approaches focus on the form of the solution, wicked problem analysis needs to investigate the nature and scope of the problem. Successful resolution of wicked problems requires appreciative design techniques (Vickers, 1968), where the definition of a solution emerges in tandem with the definition of the problem. Analysts must become enculturated in the problem-situation to understand the stakeholder perspectives that drive various definitions of wicked problems. They need to be familiar with systemic analysis of problems . Plus, they need to be good facilitators, capable of negotiating solutions across multiple stakeholders, with multiple viewpoints and priorities.

    References

    Mitroff, I.I., Kilmann, R.H. (2021). Wicked Messes: The Ultimate Challenge to Reality. In: The Psychodynamics of Enlightened Leadership. Management, Change, Strategy and Positive Leadership. Springer, Champaign. https://doi.org/10.1007/978-3-030-71764-3_3

    Pickering, Andrew (1995) The Mangle of Practice. University of Chicago Press, Chicago IL.

    Rittel, H. W. J. (1972). Second Generation Design Methods. Design Methods Group 5th Anniversary Report: 5-10. DMG Occasional Paper 1. Reprinted in N. Cross (Ed.) 1984. Developments in Design Methodology, J. Wiley & Sons, Chichester: 317-327.: Reprinted in N. Cross (ed.), Developments in Design Methodology, J. Wiley & Sons, Chichester, 1984, pp. 317-327.

    Rittel, H. W. J. and M. M. Webber (1973). “Dilemmas in a General Theory of Planning.” Policy Sciences 4, pp. 155-169.

    Vickers G. (1968) Value Systems and Social Process. Tavistock, London UK.

  • Appreciative Design & Soft Systems

    Appreciating The Context of Organizational Activity

    Human-centered design requires that we understand – or rather, appreciate – the need for changes to a “real-world” situation that is viewed as a governed by business logic and goals – rather than the engineering logic employed for IT system requirements. The intention is to improve how we understand the need for change – and the systemic impacts of making changes – through an iterative learning process based on Vickers’ concept of Appreciative Systems (Vickers, 1968; Checkland, 2000b).

    Geoffrey Vickers observed the diversity of norms, relationships, and experiential perspectives among those involved in, or affected by, a system of human-activity such as that found in business work-organizations. He argued that organizational change analysts needed methods for analysis that explored how to reconcile these perspectives, developing the concept of an “appreciative system,” the set of iterative interactions by which members of an organization explore, interpret, and make collective sense of their shared organizational reality (Vickers, 1968).

    The Concept of an Appreciative System
    The Concept of an Appreciative System Source: Checkland and Casar (1986), via Checkland (2000b)

    Vickers conceptualized organizational work as a stream, or flux, or events and ideas that were interpreted by participants in the organization by means of local “standards,” reflecting shared interpretation schema and sociocultural values (Checkland and Casar, 1986). Interpretations of new events and ideas are subject to the experiential learning that resulted from prior encounters with similar phenomena; these will vary across stakeholders, depending on how they interpret the purpose of the system of work-activity. To achieve substantive change, we need to understand and reconcile these multiple purposes, integrating requirements for change across the multiple system perspectives espoused by various stakeholders. These are separated out into distinct perspectives, which model subsets of activity that are related to a specific purpose or group of participants in the problem situation (Checkland, 1979, 2000b).

    Diagram showing investigation of a complex, real-world situation vs constructing models that represent the real world
    Real-World Analysis Vs. Systems Thinking About the Real World

    While both real-world analysis and systems thinking about the real world aim to produce representations of complex situations, the key difference lies in their focus: real-world analysis primarily examines data from actual scenarios to identify patterns of human-activity, relationships between actors, and issues that affect performance, whereas systems thinking takes a broader view by considering the interconnectedness of elements within a system, analyzing how they interact and influence each other to understand the big picture – and to engage in debate about how it may be improved.

    The concept of appreciative design underpins Soft Systems Methodology (SSM), an approach devised by Dr. Peter Checkland of Lancaster University in the UK, to capture and make sense of complex change requirements across multiple goals for change and the multiple rationales that underpin any organizational system of work-activity. SSM is now a highly-regarded approach to managing complex change, especially suited to the untangling of “wicked problems” (Rittel, 1972). Its contribution is to separate the analysis of “soft systems” of human-activity – what people do in their work and the logic that makes sense of that activity – from the “hard system” of IT and engineering logic that usually underpins system requirements.

    Soft Systems Methodology (SSM)

    The development of integrative system thinking methods and analysis techniques to solve ill-structured, “soft” problems is Checkland’s (1979) contribution to the fields of change management and systems analysis. Soft Systems Methodology (SSM) provides a method for participatory design centered on human-centered information systems. The analysis tools suggested by the method — which is really a family of methods, rather than a single method in the sense of modeling techniques — permit change-analysts, consultants and researchers to surface and negotiate feasible aspects of change, to explore and reconcile alternative viewpoints, and to anticipate (to some extent) the knock-on effects of changing one part of a complex system of work on other parts of this system.

    Problems are ultimately subjective: we select things to include and things to exclude from our problem analysis (the “system boundary”). But real-world problems are wicked problems, consisting of interrelated sub-problems that cannot be disentangled — and therefore cannot be defined objectively (Rittel, 1972). The best we can do is to define problems that are related to the various purposes that participants pursue, in performing their work. By solving one problem, we often make another problem worse, or complicate matters in some way. Systemic thinking attempts to understand the interrelatedness of problems and goals by separating them out.

    In understanding different sets of activities and the problems pertaining to those activities as conceptually-separated models, we understand also the complexity of the whole “system” of work and the interrelatedness of things – at least, to some extent. It is important to understand that, given the evolving nature of organizational work, a great deal of the value of this approach lies in the collective learning achieved by involving actors in the situation in analyzing changes, and that this approach in inquiry is, in principle, never ending. It is best conducted with and by problem-situation participants (Checkland, 2000b).

    Summary

    To summarize, appreciative design is an approach where emergent perspectives on what a “system” of work should achieve and how that work should be performed are modeled to produce actionable changes to the system that can be evaluated around agreed standards of performance and that preserve desired relationships between human actors and between elements of work-activity and their outcomes. This approach to modeling work-systems influenced the development of Soft Systems Methodology (Checkland, 2000b), a method to operationalize the representation and negotiation of systems of purposeful human-activity around which desirable and feasible changes can be identified and implemented.

    References

    Checkland, P. (1979)  Systems Thinking, Systems Practice. John Wiley and Sons Ltd. Chichester UK. Latest edition includes a 30-year retrospective. ISBN: 0-471-98606-2.

    Checkland P., Casar A. (1986) Vickers’ concept of an appreciative system: A systemic account. Journal of Applied Systems Analysis 13: 3-17

    Checkland, P. (2000a) New maps of knowledge. Some animadversions (friendly) on: science (reductionist), social science (hermeneutic), research (unmanageable) and universities (unmanaged). Systems Research and Behavioural Science, 17(S1), pages S59-S75. http://www3.interscience.wiley.com/journal/75502924/abstract

    Checkland, P. (2000b). Soft systems methodology: a thirty year retrospective. Systems Research and Behavioral Science, 17: S11-S58.

    Checkland, P., Poulter, J. (2006) Learning for Action: A Short Definitive Account of Soft Systems Methodology and its Use, for Practitioners, Teachers and Students. John Wiley and Sons Ltd. Chichester UK. ISBN: 0-470-02554-9.

    Rittel, H. W. J. (1972). Second Generation Design Methods. Design Methods Group 5th Anniversary Report: 5-10. DMG Occasional Paper 1. Reprinted in N. Cross (Ed.) 1984. Developments in Design Methodology, J. Wiley & Sons, Chichester: 317-327.: Reprinted in N. Cross (ed.), Developments in Design Methodology, J. Wiley & Sons, Chichester, 1984, pp. 317-327.

    Vickers G. (1968) Value Systems and Social Process. Tavistock, London UK.

  • Human-Centered Design

    In the last few years, the terms human-centered and user-centered have become synonymous in HCI and IT design, with a focus on disciplines such as “user experience” and “interaction design.” Here I will argue that neither discipline really deals with the core issues of human-centered design.

    Human-centeredness in design involves designing technology artifacts, applications, and platforms that provide a “support system” to people performing specific work or play activities as individuals, or collaborating around a set of (more or less) well-defined aims – often messily and exploratively. Asking people to describe their requirements for technology to support them in their activity doesn’t work because no-body really stops top think about how they work, or what they do to achieve a goal. When they are forced to do so, they will describe how work should be done – the formal system of procedures and rules – rather than how it is done – the informal, socially-situated system that makes work activities fit with their environment and the objectives that people have.

    People are seldom alone in what they do, even when engaging in individual activity. They socialize with other people and exchange ideas, they seek advice on how to proceed, and they collaborate to achieve shared – or similar – goals. When confronted with a novel problem, most people turn to a “small world” network of trusted social contacts for input – people who share their values and perspectives – rather than conducting a wider search that includes subject experts and knowledge resources (Chatman, 1991). Even when working alone, we are never truly alone. We are thrown into a working environment that existed before we joined – a self-contained world of work and social activity that we can only understand through participation (Weick, 2004). Professionalism and practice in one organization are completely different to the practices and standards applied in another.

    When we try to understand the “user” of a software application or system, we often fail miserably because we only see the formal work activities that they perform. We miss the web of activities that their formal activity is a part of – the multiple other human-activity systems they interact with, to get things done.  User-experience design is reductionist in its focus on interaction design. It takes a human being, rich in purpose and understanding, and reduces them to the role of artifact user. Not only that, but by implication, the user of a pre-defined artifact, whose purpose is understood, but whose mechanisms of interaction remain to be fully defined. By focusing on conceptual models of use, user scripts, and activity/task frameworks for work-analysis e.g. Sharp, Preece, and Rogers (2019), it isolates the user from the social context of work, describing activities in terms of fixed procedures and embedding assumptions about how and why the artifact will be used. It loses the joyful multivocality of the human-centered approach to design. Instead of understanding that thrownness is a temporary state, where there is a choice between reaction or being proactive, user-centered design embeds reaction as a paradigm. It separates tasks from workflows, making each interaction an end in itself and enforcing the approach to design that led Lucy Suchman to write her famous treatise on situated design (Suchman, 1987, 2007). There is no linked flow of work processes, where the human being knows that (for example) they have already photocopied the report covers (onto special cardstock) and the early chapters, so now have only to copy later chapters. There is the dumb lack-of-saved-status machine, which jams halfway, then asks the user to reload the report pages in their original order, starting with the covers which need the user to load special cardstock into the paper feeder. Which they already did.

    We can support this world by understanding the various purposes of human activity and designing technology to assist in those purposes (Checkland and Winter, 2000). Human-centered design differs from user-centeredness by being systemic and multi-vocal: it is aware of the multiple networks of activity in which a human technology user engages, simultaneously. Unlike user-centered design, which focuses on a single, definable work-goal, human-centered design appreciates the multiple goals that people pursue simultaneously, for different purposes. Human-centered design appreciates the social and organizational context of work, employing analytical approaches and methods that explore the complexity of the activities that we do – and the social networks we inhabit to do them.

    Designing for humans rather than users is a choice:

    • Human-centered design explores the multiple, purposeful systems of human-activity that are required to achieve even simple work (or play) goals.
    • It treats the participants in a human activity system as autonomous individuals, not agents to be modeled, controlled, and curtailed. Human-centered design respects and supports the local knowledge required to act skillfully, using local knowledge and various forms of tacit or implicit knowledge to perform work that is often not recognized as knowledge work.
    • It recognizes that a social system of information exchange exists, of which the designed technology artifact or software is only a part, and that humans need to exercise a deliberative choice about what to record and why. Any computer-based system of data is part of a wider, human-network-based system of information.
    • Because it appreciates work as part of a wider social system,  human-centered design involves a conscious decision to support the informal communications and activities that keep the system of work connected and informed – for example, water-cooler conversations or phone calls. These informal channels produce more knowledgeable participants in the system of work, rather than resulting in recorded data records or written resources. They are often omitted from – or worse, designed out of – the formal system of “user experience design.”
    • Above all, it acknowledges that knowledge, understanding, and the meanings that we ascribe to work are emergent. We understand how to do things by doing them, then reflecting on what we did and how – after which we have a better understanding of how to do them next time. Designing any particular set of procedures into a computer-based system is not only a waste of time, but may be counterproductive, as we constantly improvise and improve on how we did things previously (learning-by-doing). Human-centered systems design allows the human to be in control of their work, rather than the IT system.

    So no – “user experience design” and “interaction design” do not support human-centeredness in work (or play). They seek to humanize the artificial processes imposed by transaction-based systems by associating these with perspectives that acknowledge the psychology of human activity, learning, and interactions with technology. But they don’t even scratch the surface of understanding situated, systemic activity. For that, you need to employ methods that complicate your perspective, such as Soft Systems Analysis (Checkland, 2000; Checkland and Poulter, 2006) – and to take human-centeredness seriously.

    To conclude, user-centered design – as the term is employed in HCI and UX – is not the same as human-centered design. User-centered design is aimed at mitigating and improving the experience of using a system of technology that was designed for another purpose than those the user prioritizes – to make money, to “engage” users on the website so they return (and spend more money), and to publicize the firm’s products and services. In contrast, human-centered design is an approach that starts with user values, priorities, and purposes. It seeks to afford uses of the system that fulfill how the user would like to access the features that they value and expect. It designs the flow of use-interactions around the expected user flow of work (or play), allowing the user to configure this flow how they want. It does not make you do illogical or stupid things, like reloading all the sheets in a photocopier feed in their original order, even when the copy failed on the last-page-but one. It does not make you enter the same information repeatedly, because the designer was too unimaginative to anticipate that a user might want to change some of the options they had selected earlier (e.g. when booking an airline ticket). And it doesn’t make you go through seven layers of a menu to reach the one page you need.

    Human-centered design is performed by people who talk to users, learn to think like users, and walk alongside them in their work. These designers not only prototype and evaluate their designs, but also listen to the feedback they are given. They value user input and see it an critical to their portfolio of design experience. In the design literature of the 1980s there was a lot of discussion of how user representatives would “go native,” when participating in design projects, learning to think like designers and subsuming the interests of their fellow users in the process. In the 2020s, we need to see more IT designers going native, learning to think like users, reworking IT system designs to support how users work, and valuing the aspects of system design that users value. That is human-centered design.

    References

    Chatman, E.A. 1991 “Life in a Small World: Applicability of Gratification Theory to Information-Seeking Behavior,” Journal of the American Society for Information Science (42:6), pp. 438–449.

    Checkland, P. 2000 “Soft systems methodology: a thirty year retrospective,” Systems Research and Behavioral Science (17), pp. S11-S58.

    Checkland, P., and Poulter, J. 2006. Learning For Action: A Short Definitive Account of Soft Systems Methodology, and its use Practitioners, Teachers and Students Chichester: John Wiley and Sons Ltd, 2006.

    Checkland, P., and Winter, M.C. 2000 “The relevance of soft systems thinking,” Human Resource Development International (3:3), pp. 411-417.

    Sharp, H., Preece, J., and Rogers, Y. 2019. Interaction Design: Beyond Human-Computer Interaction, 5th EditionWiley, UK, 2019.

    Suchman, L. 1987. Plans And Situated Action Cambridge MA: Cambridge University Press, 1987.

    Suchman, L. 2007. Human–machine reconfigurations: Plans and situated actions Cambridge, UK: Cambridge University Press, 2007.

    Weick, K.E. 2004. “Designing For Throwness,” in: Managing as Designing, R. Boland, J and F. Collopy (eds.), Stanford CA: Stanford Uniersity Press, pp. 74-78.

    Selected Papers:

    Gasson, S. (2008) ‘A Framework For The Co-Design of Business and IT Systems,’ Proceedings of Hawaii Intl. Conference on System Sciences (HICSS-41), 7-10 Jan. 2008. Knowledge Management for Creativity and Innovation minitrack, p348.  http://doi.ieeecomputersociety.org/10.1109/HICSS.2008.20.

    Gasson, S. (2005) ‘Boundary-Spanning Knowledge-Sharing In E-Collaboration’ in Proceedings of Hawaii Intl. Conf. on System Sciences (HICSS-38), Jan. 2005. http://doi.ieeecomputersociety.org/10.1109/HICSS.2005.123

    Gasson, S. (2003) ‘Human-Centered vs. User-Centered Approaches To Information System Design‘, Journal of Information Technology Theory and Application (JITTA), 5 (2), pp. 29-46.

    Gasson, S. (1999) ‘A Social Action Model of Information Systems Design’, The Data Base For Advances In Information Systems, 30 (2), pp. 82-97.

    Gasson, S. (1999) ‘The Reality of User-Centered Design‘, Journal of End User Computing, 11 (4), pp. 3-13.

  • Socio-Technical System Design

    Origins of Human-Centered Design

    A few years ago, I published an academic paper – which proved to be one of my most-read articles, on user-centered vs. human-centered design. In that paper, I compared the typical analytic methods and tools for user-centered design to an idea of human-centered design that came out of the field industrial engineering. Having seen the recent explosion of “user-centered” design fields such as User Experience design, I feel even more strongly that human-centered design is a discipline that has not yet fulfilled its potential for changes to the way in which we design technology systems for both work and play.

    Human-centered design ideas come out of an emancipatory labor movement – originally in the UK – that looked at the constraints imposed by technology on work and focused on the impact of design on the quality of working life. This “socio-technical” approach to design (Emery & Trist, 1960) originated in studies of industrial processes, often embedded in the rapid societal and technical change of post World War II Britain conducted by researchers from The Tavistock Institute of Human Relations in London. A research team led by Eric Trist, Ken Bamforth, and Fred Emery studied the organization of coal-mining teams for various types of mine and coal-seam environment, concluding that the design of working arrangements and the use of technology needed to be balanced with the conditions in various type of working environment. They noted the tension between the need for miners to self-organize into collaborative groups that increased productivity by allowing miners autonomy in selecting their team role, and management directives which constrained group autonomy because this empowered the miners – and allowed them to negotiate the higher rates paid for skilled labor (Trist et al., 1963). They coined the term “sociotechnical” to define an approach to the design of working arrangements that balanced the socially-situated needs of human workers with the use of machinery to automate repetitive and dangerous work.

    The ideas behind socio-technical design really took off in the 1980s, with the explosion of affordable office technologies and personal computing. Some notable thinkers in this aspect of design include:

    Mike Cooley (Architect or Bee?, 2016), who explained how technology design choices exerted control over the labor force at the expense of social good. A key element of his arguments was to explain how the combination of conceptual design ability with the practical ability to understand the context of practice across multiple domains – common in the renaissance – has given way to a “deep dive” specialization in one area or another. This separation of “planning” from “doing” leads to design problems, as designers cannot envision the context in which their design will be used and make stupid mistakes. It also excludes consideration of social good when making design choices. Technology decisions are made on the basis of manufacturing cost rather than long-term, environmental impact.

    Ken Eason, who argued in his early work (e.g. Eason, 1982) that designers’ choice of design approach affected system usability: a technology-led approach leads to ‘fire fighting’ when negative organizational effects become apparent; and user involvement in design tends to fail as users take longer to understand new technology than developers, so design is complete by the time they are able to make a contribution. He proposed an evolutionary design process that builds slowly from small-scale systems to large ones, retaining the flexibility to change and adapt to emerging user needs, promoting user learning via system prototypes and training, and involving users in system evaluation. His later work discusses how the typical “closed system” approach to IT design (goal-oriented and focused on predefined requirements) constrains the “open system” approach to design needed to balance the emergent needs of human users with technology goals, and also cater for the evolving system requirements engendered by changing global business environments (Eason, 2009).

    Howard Rosenbrock (1981, 1988), was a visionary engineering theorist, who not only developed innovative techniques approaches to algorithm design for control engineering, but also saw engineering as an “art” (Rosenbrock 1988) that needed to balance the design of technology with the social needs, personal experience, and judgment of human beings. The opening to his 1981 paper, Engineers And The Work That People Do, contains the most chilling description of a work environment that I have ever read:

    The plant was almost completely automatic. Parts of the glass envelope, for example, were sealed together without any human intervention. Here and there, however, were tasks which the designer had failed to automate, and workers were employed, mostly women and mostly middle-aged. One picked up each glass envelope as it arrived, inspected it for flaws, and replaced it if it was satisfactory, once every four-and one-half seconds. Another picked out a short length of aluminum wire from a box with tweezers, holding it by one end. Then she inserted it delicately inside a coil which would vaporize it to produce the reflector, repeating this again every four-and-one-half seconds. Because of the noise, and the isolation of the work places, and the concentration demanded by some of them, conversation was hardly possible.

    Rosenbrock, H. H. (1981). Engineers And The Work That People Do, pg. 4.

    This description still sends shivers down my spine. Not just because of the working conditions, but because of the casual way in which Rosenbrock mentions that the few manual work-processes on the light-bulb factory floor are not automated only because they are too complex or expensive to automate. They used human-beings for repetitive, demeaning jobs in which the environment made it too difficult to socialize with others, simply because they were cheaper or easier than designing an automated solution.

    Participative Design

    Obviously, any blog post cannot capture the whole of the socio-technical movement, with all the complexities that the various studies introduced. Here, I have tried to outline the tip of the iceberg, explaining the motivations that led to the HCI, CSCW, and agile design fields that influence contemporary design. But I cannot leave this discussion before mentioning the key influence of End Mumford. Professor Mumford was critical in promoting the importance of user participation in design (Mumford, 1983). She even conducted studies to demonstrate how users “went native” when participating in technology design, as technology-design skills were considered so glamorous and career-enhancing (1975). She devised a method – the ETHICS approach – that illustrated how to analyze requirements in ways that both balanced the technical and the social aspects of design, but also managed the inevitable subversion of social (work-system) design by considerations of technical expediency and optimization (Mumford & Weir, 1979; Mumford, 1995).

    So how do we design human-centered systems that support workers in the work they need to do, while allowing them autonomy in the way that they do this work? The process devised over many years is to use socio-technical systems design.

    Figure 1. Socio-Technical Systems Design

    As shown in Figure 1, above, socio-technical design balances the needs of a “supported system” of people doing work – a.k.a. the social system, with a “supporting system of information and communication technology – a.k.a. the technical system. It is important to start with the social system: the people who do the work are unfailingly the people who understand best what it requires, in the way of information and computing support. It is also important to see the drivers of design as the need to balance changes to the two systems, so the IT system supports the system of work (and not vice-versa). I refer to this principle as the co-design of business-process and IT systems. This concept was inspired by the Soft Systems Methodology approach of Peter Checkland (1981). Checkland argues that designed IT systems often solve the wrong problem, because designers fails to appreciate that the point of design is to support purposeful systems of human activity, rather than pursuing the separate aims of a technology architecture, data structures and information systems (Checkland, 1981; Winter, Brown, & Checkland, 1995). Socio-technical systems design balances the needs of the systems of purposeful human-activity (work or play) in which various people engage, and the supporting system of information technology and user experience design that makes those activities possible.

    References

    Checkland, P. (1981) Systems Thinking, Systems Practice, John Wiley & Sons, Chichester.

    Cooley, Mike (2016). Architect or Bee? The Human Price of Technology. UK: Spokesman Books. ISBN978-0-85124-8493.

    Eason, K. D. (1982). The Process Of Introducing Information Technology. Behaviour and Information Technology, 1(2), April-June 1982>
    Reprinted as Eason, K.D. (1984) “Managing Technological Change,” in Rob Paton, Suzanne Brown, Jake Chapman, Mike Floyd and John Hamwee (Eds.) Organizations: Cases, Issues, Concepts. The Open University, Milton Keynes, UK.

    Eason, K. D. (2009). Before the Internet: The Relevance of SocioTechnical Systems Theory to Emerging Forms of Virtual Organisation. International Journal of Sociotechnology and Knowledge Development, 1(2). 

    Emery, F. E., & Trist, E. L. (1960). Socio-Technical Systems. In C. W. Churchman & M. Verhulst (Eds.), Management Science Models and Techniques (Vol. 2). Oxford UK: Pergamon Press.

    Mumford, E. & Sackman, H. (1975) Human Choice and Computers, North-Holland Publishing Company.

    Mumford, E. & Weir, M. (1979), “Computer Systems in Work Design: the ETHICS Method”, John Wiley, New York

    Mumford, E. (1983) Designing Participatively: A Participative Approach to Computer Systems Design. Manchester Business School, Manchester, UK.

    Mumford, E. (1995) Effective Systems Design and Requirements Analysis: The ETHICS Approach. Macmillan, Basingstoke, UK

    Rosenbrock, H. H. (1981). Engineers And The Work That People Do. IEEE Control Systems Magazine, 1(3), 4-8.

    Rosenbrock, H. H. (1988). Engineering As An Art. AI & Society, 2(4), 315-320.

    Trist, E., Higgin, G., Murray, H., and Pollock, A. B. (1963) Organisational Choice. London: Tavistock Publications.

    Trist, E. L. (1981). The evolution of socio-technical systems. Toronto: Ontario Quality of Working Life Centre. Report access is provided courtesy of Larry Miller’s Blog on Leadership, Learning and Culture.

    Winter, M. C., Brown, D. H., & Checkland, P. B. (1995). A Role For Soft Systems Methodology in Information Systems Development. European Journal of Information Systems, 4(3), 130-142.

  • Coordination, Cooperation, and Collaboration

    I was musing about the differences between these three concepts. They are not explained clearly in any resource I could find (although many people take a stab at this), so I thought I’d try bending my brain around the problem. The three types of collectivity appear goal-oriented (as in, sharing a common purpose), but there are big differences between the ways in which group members interact – and the reasons for these types of interaction.

    Cooperation is when people share ideas about how to work, or share effort to complete the work towards a shared goal, which is understood in common. People work together to complete a task that would be much more difficult to complete individually. Cooperation often involves deciding how to divide the work between individuals in a group for an optimal outcome – for example, in software or organizational change projects. Work may be divided laterally (each person takes a separate slice of the work towards a deliverable), vertically (each person takes a separate deliverable), or performed collectively, where people share the effort required to achieve a goal (for example, analyzing a business process that is too diverse – involving too many stakeholders – for one person to explore in a reasonable amount of time).

    Coordination is the organization of work-tasks across individuals to achieve a complex goal that requires analysis (breakdown into subtasks) before it can be addressed. People work together towards a common goal within an agreed timeframe, even if they don’t understand all the tasks required at the start. They organize their activities around a schema, which provides a model of the parts of the work to be done. They divide their labor on the basis of this schema, with individuals or sub-groups completing each part, which is assembled into a whole once all relevant parts have been completed. They may collaborate to perform shared subtasks.

    CCC2

    A Work Breakdown Schema (WBS) Used For Coordination of Work

    Coordination may be organized around interim deliverables, which are completed individually from subsets of the work-schema, then assembled once all the parts are complete. The underpinning concept to coordinated work activity is that of a plan – a plan of work, or a plan of how the parts of the whole are organized. This is used to guide the coordination of work, across individuals and across groups. For example, in traditional software project management, work is coordinated around a work breakdown structure (WBS).

    Collaboration is the pooling of effort, to achieve a joint goal, which everyone in the group of coordinated workers may not understand in the same way (so this is not a shared goal – subgoals may emerge through the processes of discussion and experimentation over how to perform the work). People work together, taking different parts of a task, to achieve a goal that, if not understood in common at the start of the process, will probably be understood in the same way by the end. Collaboration requires trust (that other people will work towards a common goal), but it is more adaptive than coordinated work – instead of agreeing a model of the task in advance, collaborators develop a shared model of the task deliverables as they collaborate on the task. Working together increases the amount of shared understanding between people, which allows them to improvise and adapt the plan of work to contingencies that arise. So both goals and work-practices evolve as shared practice increases shared understanding between collaborators. Software developers, working on agile software projects, collaborate in analyzing how to coordinate their team’s work around a feature-breakdown then coordinate team work around each person implementing the next feature in the backlog. Finally, they collaborate around integrating the feature components into a coherent prototype system.

    Coordination schema, where sub-goals are merged to achieve an integrated outcome

    Collaboration schema, where sub-goals are explored and defined independently, then merged to achieve an integrated outcome

    Collaboration is organized around sub-components (or sub-goals) of the planned outcome that are defined separately. Each sub-component emerges through discussion and experimentation, so the parts are managed autonomously by delegating them to different people. It is only at the integration stage that the shape of the whole solution can be understood.

  • Design Methods as Performative Objects

    Brown and Duguid’s (2001) concept of a “network of practice” has been niggling away at my consciousness. The idea is that a collection of people are enabled to understand each others’ work because of commonalities in practice, but not to the extent that a Community of Practice creates shared ways of framing and performing work:

    “we include under the rubric … groups whose members, to the extent that they have common practices, are able to read and understand one another’s work. Disciplinary networks of practice cut across heterogeneous organizations, including, for example, universities, think tanks, or research labs. Professions make up yet other such networks of practice, where again similar practitioners, by virtue of their practice, are able to share professional knowledge through conferences, workshops, newsletters, listservs, Web pages and the like. … different networks of practice cut horizontally across vertically integrated organizations and extend far beyond the boundaries of the latter. Along these networks, knowledge can flow.” (Brown and Duguid 2001, p. 206)

    So create closer bonds than organizational membership, spanning organizational boundaries. If the type of intersubjectivity that derives from shared practice (i.e. what Polanyi calls tacit knowledge) does not underpin a network of practice, what does? This rings true, given the observation that IT professionals identify more with the interests of their profession than with their organization (Chou and Pearson 2012). Which brings me to the second property of networks of practice:

    “it is important to note that networks of practice may also inhibit the flow of knowledge. As Lynn et al (1996) show, professional networks will occasionally work to resist the spread of ideas felt to be inimical to the interests of the network’s members.” (Brown and Duguid 2001, p. 207).

    So how do networks of practice share knowledge? Brown and Duguid have an explanation:

    “We have used the notion of networks of practice to explain leakiness. This is not, we have suggested, simply an inherent property of some kinds of knowledge. It does not result from making knowledge explicit and so tradable. It is, rather, a function of the common underlying practice, which creates social-epistemic bonds. Where practice doesn’t prepare the ground, knowledge is unlikely to flow.” (Brown and Duguid 2001, p. 207)

    But this is not very satisfying when members of the network are not co-located. Surely, “common underlying practice” includes some form of shared framing as the basis of those social-epistemic bonds? I thought back to the work of Howard Rosenbrock (1981), who explains that IT professionals’ paradigm of system design with the aim of making users interchangeable results in deskilled, repetitive, and unfulfilling jobs for those who use these systems. He explains:

    “The paradigm is transmitted from one generation to another, not by explicit teaching but by shared problem-solving. Young engineers take part in design exercises, and later in real design projects as members of a team. In doing so, they learn to see the world in a special way: the way in fact which makes it amenable to the professional techniques which they have available.” Rosenbrock (1981, p.6),

    So we have design methods as a form of performativity, embedding ways of framing job design, as well as creating a shared design practice that ignores users’ psychological and motivation needs. But surely, IT professionals are continually learning, acquiring new skills and approaches to system design? It would appear not:

    “The fact that most IS professionals learn the bulk of their technical skills during college or immediately afterward encourages recruiters to focus on technical skills for new hires. IS professionals generally learn non-technical skills in the workplace.” (Lee et al. 2001, p.28).

    All is not lost. Lee et al. (2001) go on to observe

    “IS professionals generally learn non-technical skills in the workplace. And because these non-technical skills are so valuable in the long term, new hires need to possess the aptitude to learn these skills. This may help explain why recruiters prefer graduates who took more MIS classes than those who concentrated strictly on computer science courses.” (Lee et al. 2001, p.28).

    How can we remedy the perspective that leads to such impoverished outcomes? As Rosenbrock observes, IT systems can be seen as a replacement for human ingenuity and skill, or as a way of supporting these. We have a choice to automate or to informate work (Zuboff 1988). We also have two chances to undermine the automation-on-rails approach taught in so many methods classes. Back to the network of practice idea. IT professionals have a network of practice with really strong bonds. We can teach IS methods more thoughtfully to those who return – for ongoing education in Masters degrees, etc.  Finally, we can mobilize the network of practice, on LinkedIn and elsewhere, to ensure that IT professionals are aware of the types of skill and knowledge-preserving approaches to organizational system design that we would want to see used in our own organizations.

    References

    Brown, J.S. and Duguid, P. 2001. “Knowledge and Organization: A Social-Practice Perspective,” Organization Science (12:2), pp. 198-213.

    Chou, S.Y. and Pearson, J.M. 2012. “Organizational Citizenship Behaviour in It Professionals: An Expectancy Theory Approach,” Management Research Review (35:12), pp. 1170-1186.

    Lee, S., Yen, D., Havelka, D., and Koh, S. 2001. “Evolution of Is Professionals’ Competency: An Exploratory Study,” The Journal of Computer Information Systems (41:4), pp. 21-30.

    Rosenbrock, H.H. 1981. “Engineers and the Work That People Do,” IEEE Control Systems Magazine (1:3), pp. 4-8.

    Zuboff, S. 1988. In the Age of the Smart Machine. New York NY: Basic Books.

  • Responsive Web Design

    I manage the website for an Animal Rescue shelter. I have been struggling with the design of the site for some time now, as I have some users who are still using IE6 under windows XP (on an SVGA screen), some who want to view the site on their mobile phones, and some who have really wide displays and think my two column design looks outdated (it does). While looking for a solution, I came across the concept of responsive web design. Because the reference I just provided is stuffed with code snippets (and I personally think it is obscure), I will point you instead to some really great examples that demonstrate how a website design can be responsive.

    There is a neat concept at play in most of these designs, where a webpage layout is segmented into multi-device layout patterns, that simply “flow” differently, depending on the screen size that the user will display the site on. But screen size is not the only consideration – images have to be resized to scale with the device and the performance of the device must be considered (it is painful to load a large, graphics-intensive page on a slooow tablet!). I was also musing that – most relevantly to this course – site menus and navigation toolbar interfaces have to be designed so that they will work on any device or layout. Which is harder than you’d think, simply because of the layout conventions that we use on a typical web-page.

    Off to experiment with scripts and pageflow layouts …

  • The Relevance of Actor-Network Theory

    A recent emphasis on sociomateriality appears to have entered the IS literature because of discussions by Orlikowski (2010) and the excellent empirical study of Volkoff et al. (2007). Now that people have been sensitized to the literature on material practice, actor-network theory is classified as “tired and uninformative” [1]. Which leads me to wonder just how many IS academics have actually read the actor-network theorists? Or pondered how this applies to technology design?

    Long before people started discussing socio-material “assemblages,” Bruno Latour (1987)and John Law (1987) were discussing how technology developed by means of “heterogeneous networks” of material and human actants, the combination of which directs the trajectory of technology design and form. Latour (1999) suggests that he should recall the term “actor-network,” as this is too easily confused with the world-wide web. Yet actor-networking – in the sense of a web of connectivity, where heterogeneous interactions between diverse individuals, between virtually-mediated groups, and between individuals and material forms of embedded intentionality – is exactly what is going on in today’s organizations.

    In addition, Michel Callon’s (1986) work on how the “problematization” of a situation in ways that aligns the interests of others leads to their enrolment in a network of support for a specific technological frame. Once support has been enrolled, such networks endow irreversibility, which makes changes to the accepted form of a technology solution incredibly difficult. So we have paradigms that are embedded in a specific design. Akrich coined the term “script” to define the performativity of technology and the term was adopted by the other leading actor-network theorists [2]. This thread of work articulates incredibly deeply the ways in which technology design directs its users (and maintainers) into a set of roles and worldviews that are difficult to escape. We must “de-script” technology to repurpose it to other networks and other applications – which is much more difficult than one would suppose, given the embedded social worlds that are carried across networks of practice with the use of common technologies (Akrich 1992).
    So what does actor-network theory give us? It provides a conceptual and practical approach to understanding and modeling why design takes specific forms – and what needs to be “undone” for a design to be conceived differently than in the past [3]. It provides a rationale for understanding technology as a network actor in its own right, influencing behavior and constraining discovery. The assumptional frameworks for action embedded in – for example – a software book-pricing application will direct the evaluation of price alternatives in ways that reflects the model of decision-making adopted by the software’s author. This results in the type of stupid automaticity that recently saw an Amazon book priced at $23,698,655.93 (plus $3.99 shipping). The cause of this pricing glitch was traced back to an actor-network of two competing sellers, unknowingly connected via their use of the same automated pricing software [4].

    Finally, I want to observe that a lot of the recent “materiality of practice” literature has identified new phenomena and new mechanisms of actor-networks. For example Knorr Cetina (1999) has sensitized us to how epistemology is embedded in socio-technical assemblages, Rheinberger (1997) has demonstrated how some technical objects are associated with emergence while others enforce standardization and Henderson (1999) demonstrates how the use of specific representations can conscript others around an organizational power-base. But I would argue that these effects can be understood by using Actor-Network Theory as one’s underpinning epistemology – and that exploring actor-network interactions continues to reveal ever newer mechanisms that are relevant to how we work today. I would strongly recommend Bruno Latour’s latest book, Reassembling The Social.

    Notes:
    [1] I have to declare an interest here – this comment was contained in a review of one of my papers … 🙂
    [2] As Latour (1992) argues: “Following Madeleine Akrich’s lead (Akrich 1992), we will speak only in terms of scripts or scenes or scenarios … played by human or nonhuman actants, which may be either figurative or nonfigurative.”
    [3] One of my favorite papers on the topic of irreversibility in design is ‘How The Refrigerator Got Its Hum,’ by Ruth Cowan (1995). Another good read is the introduction to the same book by MacKenzie and Wajcman (1999).
    [4] The amusing outcome is recounted by Michael Eisen, at http://www.michaeleisen.org/blog/?p=358

    References:
    Akrich, M. 1992. The De-Scription Of Technical Objects. W.E. Bijker, J. Law, eds. Shaping Technology/Building Society: Studies In Sociotechnical Change. MIT Press, Cambridge, MA, 205-224.
    Callon, M. 1986. “Some elements of a sociology of translation: domestication of the scallops and the fishermen of St Brieuc Bay.” J. Law, ed. Power, Action, and Belief: a New Sociology of Knowledge? Socioogical Review Monograph 32. Routledge and Kegan Paul, London, 196-233.
    Cowan, R.S. 1995. “How the Refrigerator Got its Hum.” D. Mackenzie, J. Wajcman, eds. The Social Shaping of Technology. Open University Press, Buckingham UK, 281-300.
    Henderson, K. 1999. On Line and on Paper: Visual Representations, Visual Culture,and Computer Graphics in Design Engineering. MIT Press, Harvard MA.
    Knorr Cetina, K.D. 1999. Epistemic Cultures: How the Sciences Make Knowledge. Harvard Univ. Press, Cambridge, MA.
    Latour, B. 1987. Science in Action. Harvard University Press, Cambridge MA.
    Latour, B. 1992. “Where Are the Missing Masses? The Sociology of a Few Mundane Artifacts.” W.E. Bijker, J. Law, eds. Shaping Technology/Building Society: Studies In Sociotechnical Change. MIT Press, Cambridge MA.
    Latour, B. 1999. “On Recalling ANT.” J. Law, J. Hassard, eds. Actor Network and After. Blackwell, Oxford, UK 15-25.
    Law, J. 1987. “Technology and Heterogeneous Engineering – The Case Of Portugese Expansion.” W.E. Bijker, T.P. Hughes, T.J. Pinch, eds. The Social Construction of Technological Systems: New Directions in the Sociology and History of Technology. MIT Press, Cambridge MA.
    MacKenzie, D.A., J. Wajcman. 1999. Introductory Essay. D.A. Mackenzie, J. Wajcman, eds. The Social Shaping Of Technology, 2nd. ed. Open University Press, Milton Keynes UK, 3-27.
    Orlikowski, W. 2010. “The sociomateriality of organisational life: considering technology in management research.” Cambridge Journal of Economics 34(1) 125-141.
    Rheinberger, H.-J. 1997. Experimental Systems and Epistemic Things Toward a History of Epistemic Things: Synthesizing Proteins in the Test Tube. Stanford University Press, Stanford CA, 24-37.
    Volkoff, O., D.M. Strong, M.B. Elmes. 2007. “Technological Embeddedness and Organizational Change.” Organization Science 18(5) 832-848.

  • Designing Social Media Platforms For Online Learning

    Recently, I have been using a collaborative social media platform, designed for online learning, to run one of my classes. The idea was, that as we are studying social informatics, we could study the effect of using social media on our own workflows first hand. I also thought that – in these days of daily Facebook and Twitter use – a social media site would add some relevance to the class. My thinking was that the “right-brain” expression that Daniel Pink extolls as critical to motivation in the 21st Century – the design, narrative, synthesis, empathy, play and sensemaking skills – would be enabled by the use of social media (Pink, 2005). The site has a WIKI, blogs, discussion forums, and an interactive chat facility. I was proposing that we used Google+ hangout for short class discussions by video. For the first week, I set students the task to post to the WIKI, to post to their own blog, to locate some web readings, and to join Google+ if they had not already done so.

    By Thursday (from a Monday start), almost all of the students had posted to the discussion forum. Several had asked me questions by email. But no-one had posted to the Blog or the WIKI. By Friday, two of the more technologically-literate students had made blog posts. But most of the activity was still on the discussion forums – and only three students had provided me with Google+ contact details. Then I started to question my own assumptions. All of the students had used Blackboard for their online course access, which revolves around an asynchronous discussion board. So they were used to interacting via an asynchronous forum. I had assumed that they would be excited to use more “social” media for class interactions or for sharing what they had discovered about the topic. But how did this fit into their idea of how they would behave in an online class? Very badly. Most students sign up for online courses because this provides them with choices about what to do, when. They have a low learning-curve for using a discussion forum. Anything else is hard work.

    Clay Shirky talks about the cognitive surplus that is available from zillions of digitally-literate people with mundane jobs and untapped creativity. He argues that this expresses itself in the groundswell of free, open source software initiatives and in the crowdsourcing phenomenon (Shirky, 2010). But graduate students with a full-time job are already using their cognitive surplus in grappling with new areas of learning. My assumption that they may have some left over for experimenting with social media may be false. The problem is that the learning curve gets in the way of the “right-brain” expression that I wanted to encourage. I may need to rethink how far experimenting with social media is constraining people’s’ ability to express themselves.

    References
    Daniel Pink  (2005) A Whole New Mind: Why Right-Brainers Will Rule the Future. Berkeley Publishing: New York.
    Daniel Pink (2005) Revenge Of The Right Brain, Wired Magazine, Feb. 2005.
    Clay Shirky (2010) Cognitive Surplus: Creativity and Generosity in a Connected Age, Penguin Press: New York.
    Clay Shirky (2010) How Cognitive Surplus Will Change The World. TED Talk Video, June 28, 2010.
    Clay Shirky and Daniel Pink  (2010) Cognitive Surplus: The Great Spare-Time Revolution. Wired Magazine, June 2010.

  • Organizational Forms Of Coordination

    I have been working for a while on comparing the results from some very complex research studies of collaborative design in groups that span disciplines or knowledge domains. I was stunned to realize that I had different types of group activity depending on the sort of organization.

    By “organization,” I mean the way in which work is organized, not the sort of business they are in. I noted three types or organization, that seem to respond to collaboration in different ways:

    • Tightly-coupled work organizations rely on well-defined work roles and responsibilities to coordinate tasks across group members. When people in this sort of group have to make decisions, they partition these decisions, based on expertise. Because they all know each others’ capabilities and roles, they don’t have to think about who-knows-what: this is just obvious. This type of organization falls down when people don’t perform their role reliably. For example, if the whole system relies on accurate information coming into the group, someone who misinterprets what they observed can undermine the whole group system.
    • Event-driven organizations rely on external crises and pressures to coordinate group action. People in this sort of group have strongly-defined roles in the wider organization that take precedence over their role in the group — for example in management taskforce groups, business managers tend to prioritize their other work over problems that the group needs to fix. When people in this sort of group make decisions, they partition these decisions according to who-claims-to-know-what, who has time to do the work, and who knows people connected to the problem. They get to know each others’ capabilities over time, but this is a slow process as priorities and decisions are driven by external events, rather than a shared perception of what needs to be done. This type of organization falls down when decisions or actions that were put on a back burner because of another crisis inevitably become a crisis themselves because they were not followed through.
    • Loosely-coupled organizations rely on ad hoc work roles and cooperation among group members. This type of group is commonest in business process change groups, professional work-groups, and community groups, where people are there because they share an interest in the outcome.  When people in this sort of group make decisions, they partition these decisions according to who can leverage external connections to find things out and who has an interest in exploring what is involved. People often share responsibilities in these groups, comparing notes to learn about the situation. This type of organization falls down because it is hard to coordinate. So shared tasks are performed badly because someone knew something vital that they failed to communicate back to the group.

    Wild Horses
    Managing group collaboration can be like taming wild horses

    Why would we care about these different types of organization? Well these structures affect how we approach problem-solving and design. If we (process and IS analysts) need to work with one of the tightly-coupled work-groups, we need to identify who has the decision-making capability for what. It would not occur to a tightly-coupled group member that anyone would not realize who to go to for what. If we need to work with an event-driven group, we have to realize that our work will not be a priority for them — it must be made a priority by gaining an influential sponsor who can kick a$$ within the group(!).  If we work with a loosely-coupled group, we need to engage the interest of the group as a whole. Working with individuals can lead to failure, as this type of group makes decisions collaboratively, not on the basis of knowledge or expertise.

    I have a fair amount of evidence for this line of thought and I am pursuing other factors that make these groups different. More to follow …