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Analyzing Technology Trends for Fun and Profit

January 26, 2015

By Richard P. Mignogna, PhD, PE, GEM Lecturer

 Technology trend watching is a favorite avocation in many fields — energy, transportation, telecommunications — the list is endless. Renewable energy in general, and solar photovoltaics (PV) in particular, provides many great examples of current interest. For example, understanding trends in the efficiency of PV cells is needed to understand the future economics of solar energy. But, can we do more than simply marvel at current progress and just wait and see what comes next? The short answer is yes.

Specialists in strategic technology planning have invested careers studying the dynamics of technological advances and predicting the future direction in technologies of interest to business. The growth in PV cell efficiencies presents an ideal application.

While the relationship between PV cell efficiencies and the cost of solar energy is clear, the plethora of PV technologies available makes a very confusing landscape. Particular varieties of silicon and thin film dominate the landscape now, but for how long? The history of technological advance is replete with competing technologies vying for dominance in the marketplace (Remember the Beta vs VHS wars? Now followed by BlueRay vs HD-DVD) The current energy arena is no different. For example, silicon, thin film (in different flavors), organic solar cells, etc. are all on their own performance trajectories. How do we assess their comparative potential? Not where they are today but where they will be in the future?

Most have heard of Moore’s Law, which describes the exponential growth in computing power over time, but few know that Moore’s Law is merely a singular application of a broad class of growth models that apply to technological advance in general. Less well understood is how to apply such models to the vast quantity of trend data that has become available in renewable energy (think photovoltaics, wind energy, energy storage, etc.) and a host of other technologies of interest to energy planners, utilities, developers, manufacturers, researchers, R&D managers, strategic planners, venture capitalists, and investors in emerging technologies.

Is there a Moore’s law for energy in general and various renewable energy technologies in particular? Of course there is. The problem is there are many, and the first order of business is to define the technology of interest – for PV, think silicon vs CdTe vs CIGS vs organic PV vs etc., etc., etc. – and the metrics that will allow you to assess their performance over time.

But, there is more to this than simply turning such technology assessments into a data dredging exercise. It is common to consult with individual “experts” but unfortunately their biases often limit, albeit unintentionally, their ability to provide an objective picture. More worrisome, perhaps, would be relying on overpriced reports from the big market research houses whose optimistic growth forecasts are typically unsubstantiated, or on the projections of advocacy organizations.

Fortunately, more rigorous approaches for aggregating the diverse opinions and experiences of multiple experts are available to help arrive at a more complete picture of future advances in technologies of interest. And, combining these qualitative approaches with the aforementioned trend analyses can equip technology planners with a fairly robust suite of methods to analyze emerging technologies and plan technology investments.

It is incumbent on those who are making and managing investments to have some understanding of the dynamics of technological advance to help guide their decision making. It is not too essential that a given forecast must be proved accurate; it is rather the learning gained from engaging in the exercise that enables better decision making.

So where do you start?

1. Determine the performance parameters that can help you describe technological advance (hint: sales growth is NOT a technological performance parameter). For PV, cell efficiencies are a good place to start but there are others. For wind energy, rotor diameter, hub height, and turbine nameplate capacities are also a good starting place.

2. Obtain trend data on the metrics of interest but be careful not to mix different technologies. For example, if looking at trends in the speed of aircraft, do not mix propeller driven aircraft with jet aircraft as they are fundamentally different technologies and this will only make a mess of your analysis.

3. Understand where you are on the technology s-curve of the technology you are researching. There is always some physical limitation to the performance of every technology. Are you close to it? (See the figure below). Know how and when to apply the proper growth models (Gompertz, Pearl-Reed, Fisher-Pry, etc.) to complete your analysis.

4. If looking at the substitution of an emerging technology for an incumbent one, consider that such substitutions often take longer than expected – in spite of what you may read in the press about “game changers” – and it is not uncommon for such an attack to motivate improvements in the incumbent technology.

Finally, using the tools I’ve described in planning your technology strategy is only a starting point. Work to understand what the data is telling you. And most importantly, understand that trend is not destiny

For years, as principal in Technology/Engineering Management Int’l (TEMI) I have taught the principles of technology forecasting and technology intelligence to researchers, planners, analysts, R&D managers and others charged with strategic technology planning, competitive analysis, technology road-mapping, technology scouting, technology assessment, and technology transfer. To learn more, contact me personally at

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