User research and technology: a balanced act
We have discussed the importance of innovation in our previous article. Successful innovation is understanding how new technology can become commercially viable. But this understanding is primarily conceptualised around your users. To gain knowledge about your users you have to conduct user research to interpret their approach and understand their interaction with a particular technological application.
This article will focus first on understanding the “use” of a technology as an important source of learning about a technology. Subsequently, the following article will focus on the user research aspect and identify five useful user approaches. The use side of innovation can be fully explained when the usefulness of a technology and its adoption among its users is thoroughly understood.
Interpreting the technology hype
When a new technology in the market makes great promises, how do you perceive the hype and determine its commercial viability? How do you decide if the promises will at all become a reality in future? Gartner Hype Cycle is a graphical representation of the life cycle stages a technology goes through from conception to maturity and its extensive adoption. It will help you identify the potentials of the technologies and its applications. You can evaluate how relevant they can become in solving real business problems and utilise new possibilities.
The hype cycle will help you understand how a technology or application will evolve. This, in turn, will give you an excellent insight to manage its deployment within the context of your specific business strategies.
How can the hype cycle be useful?
The hype cycle works in 5 different stages. Each phase works as reference points in marketing and technology opportunities. Businesses can use the hype cycle to manage technology decisions depending on their appetite for risk. Each stage of the cycle reflects its own set of risks and possibilities.
In this stage, a technology is potentially conceptualised. There maybe a prototype but no usable products or any kind of market research yet. The potential expectations may provoke media interests and sometimes proof-of-concepts demonstrations. If you are clear that investment at an early stage can be risky and may not always prove beneficial, you can try your hand at taking a risk for an early adoption which may or may not get rewarded later.
Peak of inflated expectations
Early adopters implement the technology creating some success stories. This generates a lot of media attention and publicity for both the success stories along with the failures. Businesspeople who are more cautious understand the reasons for early investment. But when new ideas of doing things are not entirely clarified they will also emphasise on a quality analysis of the costs involved and the benefits out of it.
Trough of disillusionment
Failures and defects lead to a setback in the technology causing some producers to quit producing their products. Interests drop as implementations fail to deliver. Investments continue on the condition that the remaining producers improve their products and address the challenges.
Slope of enlightenment
The scope of the technology for further applications become evident over time. The market widely recognises its growth. Many companies at this stage come forward to implement or test it in their environments. Second and third generation products emerge from technology providers. Many businesses invest at this stage in the testing while the more cautious companies remain circumspect.
Plateau of productivity
The technology gains stability, with its applications now well established. With its extensive implementation in the market, its relevance with businesses is identified. As mainstream adoption opens up, the norms for evaluating the technology gets higher.
Special circumstances in the hype cycle
Trigger and trough
Technologies can undergo special or unique episodes as they evolve through the above-mentioned phases. They may cease to exist as a technology category or idea in itself. Instead, their functionality is embedded in other products. Technologies often split over the course of time as well. One idea may give rise to several other subconcepts as users distinguish between different application contexts and their requirements. Similarly technologies from different disciplines can combine from time to time. For instance, in the 1990s, machine learning from artificial intelligence and regression models from the field of statistics united to give rise to data mining.
“Phoenix” technologies continuously alternate between cycles of high interest and disillusionment. For example, take the case of artificial intelligence. Any social events often can trigger new awareness of a technology. Even some notable media attention, or the complete lack of their specifying, can get some technologies to cycle through, repeatedly. These technologies normally are especially slow-paced, with principal methodological hurdles. “There is often a “double-dip” that may occur. Here the media re-hypes a technology at the source of the slope of enlightenment, just before the technology kicks off to a wider base of an enterprise or user interest.”
Some technologies, on the other hand, remain in the trough of disillusionment for an extended period before becoming out-of-date or they re-emerge at some point. Such technologies can work but there is a lack of user interest and business appeal to stimulate adoption, hence failing to deliver on their promises. For example, Google glass might have arrived ahead of its time in the market. Expensive and facing privacy issues, this product also succumbed to cultural resentment, never making its mark.
Plateau and thereafter
Technologies can become extinct prior to reaching the plateau of productivity. This untimely exit is a result of something better replacing it completely before it could traverse further in the hype cycle. For example, the emergence of high definition television very quickly replaced the analogous ones in the market, owing to better adaptability.
The target audience of a technology may vary as well. The original intended audience may grow to include new groups of interested users or reduce down to only being successful in the niche sectors. The original hype about such technologies indicates they will have a greater impact on the world than they actually did in reality at least in the present. Examples of such technologies include artificial intelligence, virtual reality etc.
The rise and fall of technology mainly depend on its acceptance in the market by its users. As a simultaneous step of investigating technology, it is also essential to analyse your users and their approach towards technology.
Broadly speaking when researching users to comprehend their approach towards a product and, in the process learning about the use value of technology, to understand its prospects, two methods can be undertaken:
- Disembodied learning is where experience during use leads to an improved understanding of how a product can be operated. Prolonged use of the product creates experienced users. This, in turn, leads to alteration suggestions that require no or little design changes.
- On the other hand, embodied learning is where learning by using leads to actual design modifications, either because users modify a product directly or propose a modification to a manufacturer.
There are five frameworks to analyse innovation, and that these will be explored in a later article.
Also published on Medium.