Sustainability has become a key criterion in guiding technological progress. How do we define it and how is it measured?

The World Commission on Environment and Development (Brundtland Commission) defined sustainability as meeting “the needs of the present without compromising the ability of future generations to meet their own needs”. This is a useful starting point. We may interpret it as an exhortation to “preserve the life giving forces of nature.

From this exhortation has arisen the notion of “minimizing the environmental footprint”. This notion implies two actionable goals:

• Limit the number of imprints
• Minimize the size of each imprint

The first goal is achieved through social, economic and political measures. The relevant metric is “What percentage of the physical environment should be under the dominion of humankind?” The second goal is achieved by technological means, and by pursuing physical frugality.

To meet these goals we need to establish operational guidelines and metrics. Guidelines can be of two kinds:

• Absolute
• Relative

Absolute guidelines reflect definitive standards and limitations. One example would be the efforts to limit the carbon content of the atmosphere to 350 parts per million. Relative guidelines reflect progressions towards a more desirable state. These include the simple guideline of  “reduce, re-use, recycle”, to the more sophisticated “molecular accountability”.

In the next postings we examine how technological guidance can benefit relative guidelines.

Copyright: Rias J van Wyk, 2009

The effective harnessing of technology-based innovation opportunities calls for a dedicated set of skills based on technological acuity.

Technological acuity is defined as an all-encompassing grasp of the full range of technologies, and  of the pathways along which they progress. This grasp requires broad technological edification, reflecting knowledge of both a macro and micro kind.The inclusion of the macro is particularly significant. It usually does not receive much attention in technical education.

At present no traditional academic discipline focuses on technological acuity. However, within the management of technology (MOT) community, there is a specialized field of knowledge designed to meet this need. It is called Strategic Technology Analysis (STA). It is based on a system of five analytical frameworks that:

• Characterize individual technological entities
• Classify technologies
• Track technological progress
• Chart constraints and breakthrough zones
• Profile social and environmental preferences

Strategic technology analysis (STA) could be considered as a foundation for all courses involving the interface between technology and management.

Copyright: Rias J. van Wyk, 2009.

To find the array of feasible innovations from the profile of possibilities, we have to consider organizational fit. Which of the possible innovations are appropriate for the organization to pursue?

To help us select, we use the technology relevance matrix. It displays the profile of possible innovations in relation to corporate competencies. For an innovation to be considered feasible it must have elements with which the organization is familiar. These can be technological, like materials, principles of operation, structure, and size; or they could be non-technological like markets and geography.

The recent announcement by Exxon Mobil, that it would pursue the development of algal biofuel, offers a useful example. This innovation would involve an oil exploration and refining company in the biological production of feedstock.  There is also the need for genetic manipulation of the organism involved. While this technology-based innovation would “apply new and unfamiliar technology in a novel and unique manner” there is a fit between bio-based and petro-based technologies. In both cases the final product would use similar infrastructures in distribution, both involve like materials – i.e., liquid motor fuel, while the waste product of the one, i.e. carbon dioxide, serves as input to the other.

The technology relevance matrix is used to produce a list of say ten feasible innovations. From these we select the final hotlist.

The hotlist uses three criteria:

• High technological potency
• Organizational familiarity
• Managerial passion and commitment

To apply these criteria we use an intuitive procedure. It is based on a system of voting in which managers use their best judgment on the first two criteria, and then, by voting, guarantee their commitment to the project.

Copyright: Rias J van Wyk, 2009.

The profile of innovation potential is a customized overview of possible innovations offered by the changing technological landscape. This is one of the most creative and challenging tasks facing managers. Profiles will vary according to the scope of the technological playing field that management’s wish to explore. Bold strategic strategic thinking will require a view of the technological playing field that is panoramic and long-term – managers may wish to radar 360 degrees. Incremental strategic thinking will require a more modest view – 30 degrees or even 3.

The customized overview must be comprehensive, coherent and concise. This is not a phenomenon that has received much attention in the academic literature. It has probably not even been named. For instance we cannot find an appropriate single term in English to express the concept of “customized overview”. In the Germanic and Nordic linguistic traditions it is a known construct. In German it is called an “überblick”, in Norwegian an “overblikk”.

To compile an overview managers need a skill-set consisting of three items:

• Mindset
• Map
• Metrics

The mindset is described by the acronym ACE: (i) Anticipatory, (ii) Comprehensive, (iii) Engaged.The format for the map has been discussed before and is based on the functionality grid. The metrics involved have also been discussed before – techno-trends based on FPMs.

The ACE mindset is absolutely crucial. Not only is the technological landscape imperfectly mapped, but it consists of technologies at different levels of readiness – mature, emerging, and latent. Managers must have the flair to explore this bewildering array, and the resilience to articulate convincingly the insights gained.

In the next post we discuss how to proceed from a profile of possible innovations to a “hotlist” of preferred projects.

Copyright: Rias J. van Wyk, 2009

To guide technological progress aimed at  economic growth, we have to identify a  “hotlist” of technologies with superior FPMs.  These technologies  serve as candidates for innovation. Superior FPMs mean greater physical economies in each of the nine sectors.

There are different approaches to compiling such a hotlist; ranging from a pragmatic and informal approach to a systematized and formal one. Here we deal with the latter.

Three steps are involved

• Explore the possible
  
• Evaluate the probable
• Envision the preferable

The first step involves an overview of the technological landscape, and the compilation of a profile of potential innovations – a profile based on a review of  techno-trends that describe the major anticipated changes in the technological landscape. The second step involves an evaluation of these innovation possibilities and the compilation of a profile of feasible innovations. This step uses a technology relevance matrix to compare potential innovations with corporate competencies. The third step involves the selection of a hotlist from the list of feasible innovations.

We discuss these three steps in the following two posts.

Copyright: Rias J. van Wyk , 2009.

As stated earlier, technological progress is  measured by improvements in FPMs. These improvements can be traced back to many sources, including technologies with higher FPMs than their predecessors. We offer four examples.

• IBM and the development of electronic computing. This led to an improvement in the FPM: Output of information (I), per unit of time (T). It was achieved by the introduction of electronic components – a new and unusual technology at the time.
  
• Litton and the creation of the microwave industry. This led to an improvement in the FPM: Output of matter, i.e. heated substance (M),  per unit of energy (E) required. It was achieved by the use of the magnetron, a component from radar technology.
  
• Corning and the manufacture of optic fibers. This led to an improvement in the FPM: Output of information (I), per unit of space (S). Corning was traditionally an oven-ware company serving domestic customers and now offered information transmission technology.
  
• Monsanto and the development of genetically modified organisms. This led to an improvement in the FPM: Output of matter, i.e., crops (M), per unit of space (S) required.  Monsanto was traditionally a bulk chemical company that now employed biologically based info-tech to create seeds with new growth characteristics.
  

In each case technological progress, and consequently economic growth, was achieved by applying new and unfamiliar technology in a novel and unique manner.

Can we formalize the procedures for encouraging and managing technology-based innovation? Recent advances in theory has made this easier.

We explore these in future posts.

Copyright: Rias J. van Wyk, 2009

As technological progress takes place, new values for FPMs emerge, and the technological frontier advances from its present position to a new one. Using techno-trends, based on FPMs as described earlier, it is possible to track technological progress as it occurs throughout the technological landscape.

As this is such a critical phenomenon, the question arises whether there is an organization that systematically tracks technological progress and charts the locality of the technological frontier?

Surprisingly, very few organizations are involved in this activity. Technoscan Centre, that hosts this blog, is one. It has produced a compilation that is in an “advanced prototype phase”. (Van Wyk, Rias J.; Karschnia, Bob; and Olson, Wayne; 2008, “Atlas of technological advance”, Research.Technology Management, September/ October, Vol. 51, No 5, pp. 61-66). This work covers the full spectrum of technologies.

Koh, H. and Magee, C.L., of MIT, have produced two of the most exhaustive studies of technological progress, using FPMs. They have tracked developments over many decades and have done this for the domains of information (I), and energy (E). (“A functional approach to studying technological progress: Applications to information technology” Technological Forecasting and Social Change, 2006, Vol. 73, No. 9, pp. 1061-1083. And also: “A functional approach to studying technological progress: Extensions to energy technology” Technological Forecasting and Social Change, 2008, Vol. 73, No. 6, pp. 735-758).

There are also many examples of technology roadmaps for particular industries. But by and large, a definitive quantitative study of overall technological progress has yet to emerge.

Copyright 2009; Rias J van Wyk

Essentially this is because inventors are increasing, or maintaining, output, while reducing the inputs of matter (M), energy (E), and information (I), and the requirements of time (T) and space (S). These changes in FPMs,  occuring throughout the technological landscape, reflect economic improvements as measured in physical units. Such improvements translate into improvements for the economy as a whole as measured in monetary values, in other words, economic growth.

Better FPMs, occurring throughout the technological landscape, are the keys to making  the link between technological progress and economic growth visible.

When technological progress is viewed in this way, the question may be asked whether there is an ultimate end-state. The answer is twofold:

1. We can conceive of an ultimate “omega state” using the mathematical limiting values that will emerge when we extrapolate the FPMs. In the long run the inputs of M,E, and I, as well as the requirements of T and S, all tend to zero.
2. In practice, and long before omega state, other constraints will make themselves felt. These include constraints imposed by ultimate theoretical limits from the field of physics, and constraints imposed by temporary barriers existing in the various fields of engineering.

Omega state is a convenient mind-set. In this state all FPMs tend towards infinity. We find this a useful construct to serve as a backdrop for structuring technology foresight.

Copyright: Rias J. van Wyk, 2009.

We measure technological progress by means of time-related graphs, i.e., techno-trends, of improved functional performance in each of the nine pathways. These improvements reflect the triple trends of technological progress. We construct these trends from time series of functional performance metrics (FPMs) that are identified for technologies in every pathway.

In practice a minimum of five FPMs are required to reflect technological progress in each case. (i) Three FPMs reflect improvements in the ratio of output to input, (ii) One FPM is required to reflect improvement in throughput. (iii) And one FPM is required to reflect improvement in functional density.

Taking the first pathway in the grid, i.e., matter processing, as example, the five FPMs would be:

• Output of M/Input of M
• Output of M/Input of E
• Output of M/Input of I
• Output of M/T
• Output of M/S

In this definition M,E and I refer to matter, energy and information, while T and S refer to time and space respectively.

This approach generates a chart of 45 types of technology trend that describes progress across the full technological landscape.

Copyright: Rias van Wyk, 2009.

The macro-framework that is most convenient for this purpose is the functionality grid. It groups technologies in terms of their functionality – i.e., their ability to transform physical reality. Nine functionalities are differentiated. These are depicted below.

The functionality grid offers theorists a most convenient format for analyzing technological progress:

• It offers a way of classifying trends in FPMs
• It can be used to trace historical trends in technological progress
• It provides a format for structuring a technology outlook