Anthony Dsouza
Jul 29, 2019

Opinion: The partial rebound

An iterative approach to research is essential to facilitate speed, collaboration, and continuous learning

Opinion: The partial rebound
In 1865 an English economist named William Jevons released a book called “The Coal Question” in which he put forth this opposing view that “increases in energy production efficiency leads to more, not less, consumption”. It’s called the Jevons paradox. 
Coal is a finite resource; therefore, most governments and environmentalists for long have pushed for greater usage efficiency. They generally assumed that efficiency gains will lower resource consumption, completely ignoring the possibility of the paradox arising. 
To put it more simply, consumers tend to travel more when their cars are more fuel efficient or we tend to increase use of our coolers or LED lights because they consume less electricity (the direct rebound effect). 
It occurs when technological progress increases the efficiency with which a resource is used, but the rate of consumption of that resource rises due to increasing demand. 

Data is the new coal, but unlike coal, it’s not finite. It is fast becoming the mandatory supplement to energy. There is a lot of pressure on big marketers today to process this resource more efficiently, because of shrinking budgets and division of spends across data sources. Big marketers assume that quick and efficient research will lower spends on a project, ignoring the possibility of this paradox. Demand for quick, no frills studies and newer clients, has seen an exponential rise in the market research industry, as compared to a decade ago. 

Contrary to common intuition, efficiency pressures in market research are therefore good for the long-term prospects of this industry, leading to an increased consumption overall. For instance, a 20% improvement in timelines, results in a 5% drop in monthly profitability - there is a 75% rebound effect (or take-back effect) because of multiple iterations or availability to do more. (Source: Internal data from key clients).
Agile testing should therefore be the new currency i.e. research that is fast, iterative and adaptive. Our point of view is that agile research needs to evolve with the right offer, if we need to fuel this paradox. 
Some actions that will help marketers and clients: - 
1) Always have a bare-bones, ‘fast’ quality service - No sandwiches, no nuts, just high speed.  
2) Automation and machine learning are the only way forward for knowledge services.
3) Modular approaches need to be the norm.
To deliver speed, many types of research have become automated and/or standardized. While these solutions offer speed advantages and cost-savings, they can suffer from quality issues that make the research faulty. Quality is not a function of price, but if someone is giving you very low prices, it’s best not to peep into the kitchen. Many of the automated and standardized solutions available today: 
• Offer samples that are not representative and replicable over time 
• Are not device agnostic 
• Do not use proven measures of success 
• Offer limited ways to analyze and interpret the data. 
Responsible sourcing of data is assumed to be a seller’s lookout; marketers are willfully turning a blind eye, because of internal cost pressures. In the longer run, such actions end up being costlier to the overall business. With increased failed launches, we are seeing a demand for solutions that are not only fast, but also high-quality. 
Machine learning will help facilitate iteration. Agile research is not only intended to be fast, it should also be iterative. Iterative approaches are essential to facilitate speed, collaboration, and continuous learning. Artificial intelligence (AI) can play an important role in iteration with its ability to automate. 
Modular approaches will also become more prevalent. Traditional processes typically follow predefined and heavy sequences. As agile research evolves, we expect these linear processes to give way to modular approaches in which research and learnings from different sources (some of which may already exist) are brought together – and, where appropriate, traditional steps are eliminated because they don’t add value. 
The market industry however, does require a rethink of focus and strategy. A large chunk of the company’s wisdom is spent marketing high priced studies in a very niche and competitive environment. Simply put, most clients are buying sachets and market research companies are focused on selling bottles to a few. The focus needs to urgently shift to joining the dots and meta-analysis generated from agile pieces. 
As the rebound effect moves above 100%, we enter Jevons paradox (also called a backfire). We are at the cusp, we need to push forward….
(Anthony Dsouza is the executive director at Ipsos Innovation, India. The views expressed in this article are his own.)


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