Author Bio
Patricia Yañez-Pagans
Patricia Yañez-Pagans is a Lead Economist in the Development Effectiveness Division (DVF) of IDB Invest, where she oversees the ex-post evaluation of projects and the knowledge and impact evaluation’s agenda. Before joining IDB Invest, she worked as an Economist in the Office of Strategic Planning and Development Effectiveness of the Inter-American Development Bank (IDB) and was Professor of Economics at the Universidad Católica Bolivia. She has also worked as a consultant on evaluation topics for different institutions, including UNICEF and UDAPE of the Bolivian Ministry of Development Planning, the IDB Research Department and the University of Wisconsin-Madison. Patricia holds a Ph.D. in Applied Economics from the University of Wisconsin-Madison, a Master’s in Applied Economics from Pompeu Fabra University, and a Master's in Social Policy and Development from the London School of Economics.
Posts by Patricia Yañez-Pagans
What can Latin America and the Caribbean Expect from the Machine Learning Revolution?
Machine Learning can help businesses organize, interpret, and use big data by extracting meaningful insights and quickly solving complex problems. It can also help guide the region’s private sector towards fully harnessing the power that data has to offer.
Can innovation testing help boost private sector development in Latin America and the Caribbean?
Knowledge is increasingly seen as a key factor in promoting higher levels of productivity, competitiveness, and growth of firms. Despite this, innovation testing remains an untapped resource that can help boost private sector development in Latin America and the Caribbean. What is the best pricing scheme to maximize the demand for a product? Can technology increase the productivity of providers in a value chain? What type of product design can have the largest demand? What are the benefits to society or wider development impacts generated by a new product or service? These are questions that could be answered with an innovation testing exercise. What is innovation testing? We refer to innovation testing as the set of studies that include a randomized control trial in which an innovative approach is being tested. The final objective is to understand the cause and effect relationship between an innovative business practice or change (e.g. new product, new business approach, innovative marketing strategy, etc.) and the effects generated by it in an outcome of interest or a target population (e.g. increased demand, change in client behavior, etc.). Testing is conducted by empirically constructing a counterfactual or control group that tells you what would have been the situation in the absence of the proposed change. At the center of testing, there are considerations of cost-effectiveness, profit maximization, scalability, replicability, and/or development impact. For a long time, the private sector has been an important engine of knowledge generation and there are multiple examples of this. Back in 1842, entrepreneurs in the manufacturing industry were already experimentally testing the impacts of inorganic and organic fertilizers on crop yields, marking the beginnings of the chemical fertilizer industry. In the pharmaceutical sphere, private sector discoveries account for 80% to 90% of pharmaceutical products in the market and the industry is regularly conducting clinical trials of new drugs before introducing them into the market. Moreover, marketing companies are constantly relying on AB testing techniques to identify changes to web pages or advertisements to maximize an outcome of interest. For example, Google+ knew that with a full-screen ad that encouraged mobile website visitors to download the app, 69% of people left the mobile website right away, while 9% of the visitors clicked on the “Install” button. After they implemented and tested a nicer, less obtrusive app ad, the 1-day active users on mobile increased by 17%. Why consider innovation testing? For achieving best results managers are increasingly moving away from guessing when doing business towards using data-driven evidence to guide their decisions. Innovation testing can bring important benefits, both in terms of learning and accountability. For those in an expansion or starting phase, it can bring important learning lessons on what works and what doesn’t work before scaling up. For those seeking to explore new approaches to doing business, it can give them responses on how to design and select the business strategy that is the most cost-effective. For those seeking to generate evidence about the wider impacts or benefits they generate in society, testing can provide them with rigorous empirical evidence about their work. This is important, in this growing trend of impact investors seeking to generate social and environmental impacts beyond financial returns. It is also valuable for financial institutions that are increasingly seeking transparency and accountability. Despite the knowledge generation appetite coming from the private sector, the use of these methods remains widely concentrated in large companies and mostly in developed countries. The reality is that conducting innovation testing exercises requires technical expertise, time, and resources. In recent years, multiple firms have embarked in innovation testing exercises and multiple support platforms have emerge to help conduct these analyses. For example, Google Analytics offers support for online experiments to test which version of a landing page results in the greatest improvement in a metric value. Amazon Machine Learning Research has been conducting studies to scale-up AB testing techniques by proposing more efficient tools that help with multivariate testing and with learning how to implement ideas to reach the highest number of customers. The financial sector has also been very keen to use casual testing approaches to better tailor financial products and services to customer’s real behavior and to improve financial-decision making processes. How do we promote innovation testing? Development Banks working with the private sector bring new opportunities to support their clients with technical skills to conduct innovation testing while simultaneously providing financial additionality. Innovation testing is a key element in the IDB Invest Development Effectiveness agenda, as reflected in our annual Development Effectiveness Overview (DEO). Our focus when supporting causal testing is twofold: helping boost private sector growth while maximizing development impact, so that this becomes in a win-win opportunity for the region. We have exciting testing projects in progress related to the impacts of manufacturing companies promoting healthy practices; the effects of using machine learning techniques to increase farmer’s productivity in agribusiness value chains; and the use of technology to improve debt repayment and savings among clients of financial institutions, among others. There is still much work to do in Latin America and the Caribbean and the first step comes from the private sector demanding more hard evidence and business intelligence. This, coupled with continued support from experts in these techniques can only strengthen and boost private sector development in the region. We invite you to collaborate with us and learn more about our work at our recently launched Development Through the Private Sector Series. To know more download our first publication here. Subscribe to receive more content like this! [mc4wp_form]