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Dr Terence Love
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A presentation for Faculty of Industrial Design Engineering at TU Delft on 21 June 2021.

A video of the presentation and discussion is available HERE and the PowerPoint slides are available HERE.

A practical challenge is to find design theory that is universal and practicable across all design fields.

Dr Terence Love, CEO at Design Out Crime and CPTED Centre; and Mark Ames, Principal Adviser at Hivint

(Note: This paper is the work of the authors and has not been reviewed by or authorised by Hivint and does not represent the views of Hivint.)

Traditional IT folk tend to regard industrial control systems (ICS) as poor in cyber-security terms. They present a real challenge to traditional IT folk. Typically, ICS are Windows and Unix and Linux servers running specialist software applications. That’s reasonably familiar, but these systems are not connected to people or data stores: they’re connected to pumps and switches and relays and valves that open and close, switch off and on.

Often referred to as OT (Operational Technologies), these are the systems that control large important electrical grid infrastructure and manufacturing plants, nuclear power stations, sewage plants, oil and gas plants, water processing systems and the like. Another name for them is SCADA (Supervisory Control And Data Acquisition) systems.

If bad actors can take control of SCADA/OT systems they can create tremendous amounts of long-term damage, and threats to life for large populations: a perfect terrorism scenario.

CPTED design methods currently typically lack adequate means of inspection and review of: the design  and implementation; underlying reasoning; foundation of design decisions;  and any checks for CPTED causing adverse outcomes.

Program logic models offer a way of improving CPTED design processes through addressing these issues.

Program Logic Models

Program logic models provide a formal basis for evaluating CPTED programs and interventions at all stages in their implementation.

Any program or intervention comprises five phases:

  1. Events prior to any work on the program or intervention
  2. Identifying the need and scope of the program or intervention
  3. Designing the program or intervention
  4. Implementing the program or intervention
  5. The outcomes and changes following the implementation of the program or intervention

Good research avoids bias.

Bias appears when personal considerations start to influence how research is done and its findings. For example, people get concerned when medical researchers are funded by companies who have a financial interest in the research findings benefiting their business.

Personal interest and bias can influence which research questions are asked; which methods are chosen; which participants are selected and when; which data are collected; how data are analysed; how data and findings are interpreted and what findings are promoted.

It is useful to distinguish between design outputs and design outcomes when researching or practicing design. They can be seen in terms of a sequence in which design activity results in a design output (a design)  that can be made into a real world product (actualised design) with real world consequences (design outcomes). 

Design outputs and design outcomes are different. They are different concepts and have different roles, properties and purposes. To make useful and valid theory about design activity, it seems to be important to distinguish between them.

In design research, design outcomes are more often a better focus of design theory, especially in relation to design activity.

Design History can better contribute to development of theories in design research. Historical analysis of practices of design potentially offers much more than the history of designed objects. Such a history of real mainstream design practice offers a better understanding of the origins of academic design research. It indicates the primary origins of design research and design thinking was to address the very real practical and organisational problems of design teams with hundreds of designers and limited ability to create drawings.

There are four very different foundations for undertaking design research. The differences between them are reflected in the different research methods for data collection and analysis and validation of theories. These differences are also reflected in four different ways of writing up such research in reports, theses, journal articles, conference papers and books.

Many authors have tried to create definitions of design in line with their design practices. Design theory based on such practice-based definitions and the definitions themselves are problematic. How do I know? I've tested hundreds of definitions of design. There is one definition of design that stands out by addressing the practical and epistemological problems of other definitions. Even better, it is really simple and straightforward:

A design is a specification for making or doing something

This paper proposes the study of discontinuities in design practices and theories as a useful tool in design research. Discontinuities appear to a large extent  to coincide in a single boundary. As a result, this suggests design theories be seen as two distinct realms. An implication is the need for a second, distinct body of design theory, practice and philosophy. A defining criteria of this second body of design-related knowledge is the creation of designs that are beyond individual human comprehension: a matter of human biological limitations. The paper builds on multiple elements of prior analysis by the author relating to discontinuities previously assumed to be continuous.

The following  is my list of some of the key guidelines, tools and rules of Design Thinking. They're for design solutions in which collaboration with stakeholders is important; when outcomes  are significant; and the behaviour of the outcomes resulting from the design are dynamic. They  apply from 1H to  7H design solutions (High levels of complication, high stakeholder investment in success, high risk, high significance, high cost, high technology, high complexity in outputs and outcomes). The list has been accumulated over design projects, research  and reviews of tricks, tools and tips of design thinking since the 70s.  The list is incomplete and additional items will be added over time.

Some time ago, University Distinguished Professor Ken Friedman of Swinburne University asked me on the Jiscmail discussion list 'phd-design' to define what I mean by ‘epistemological validity’. It was a good question, and the role of reasons in literature seems like a good starting point to explain.