Renos Vakis. Behavioral psychology to improve decision making

Notes from the workshop Behavioural psychology to improve decision making by Renos Vakis from the World Bank’s eMBeD unit, and organized by Department of Foreign Affairs, Institutional Relationships and Transparency of the Catalan Government and held in Barcelona, Spain, on 11 February 2019.

Renos Vakis. eMBeD unit. The World Bank
Behavioral psychology to improve decision making

We are human beings and, as so, we are social.

How do we make decisions?

  • Automatic thinking
  • Social thinking
  • Mental models

What do decision makers do:

  • Contextual definition of problems.
  • Map behaviours.
  • Solution, evidence, iteration.

Main problems in decision-making:

  • Bias of confirmation: when the individual seeks or interprets new evidence as confirmation of their beliefs or theories already conceived.
  • Bias of confidence: when subjective confidence of someone over their own judgement is higher thant the objective precision.
  • Framing and aversion to losses: we tend to take more risks in the “losses” frame rather than on the “gains” frame. We prefer not losing rather than gaining.

Case study: paying taxes in Poland

(Some) people do not pay taxes.

  • Reasons: architecture is complex, mental effort to understand how paying taxes work, bad perception of what happens with taxpayers money (e.g. corruption), etc.
  • Possible solutions: improve electronic procedures, etc.

Experiment in Poland: sending letters to “remind” tax evaders that they should pay. Letters work, but they work better the harder the tone of the letter.

Case study: water saving in South-Africa

Water consumption invoices included explanations on pricing and the different price thresholds. Especially poor people was responsive to such information, but not as much richer one. Then other information was included: how one behaved according to the average citizen and publicly acknowledging those more efficient in saving water. Then rich people also were responsive and saved water.

Mapping behaviors

Diagnosing bottlenecks:

  • Decisions
  • Actions
  • Mindsets
  • Information
  • Context

Map a given process, identifying all the behaviors —especially decisions and actions— and see how they are conditioned or determined by information, beliefs, procedures and tasks, social norms, etc. This should help us to accurately find out the potential decision or action bottlenecks: steps where one may or may not make a decision or do an action depending on several factors. If these are properly identified and characterised, we can act upon those factors to improve the likelihood of decisions to be made and actions to be carried out.

Group decisions and mindsets



Social conformity
Independent behavior Interdependent behavior
Empiric Customs
It is what I want to do.
Descriptive norms
Everyone does it.
Normative Moral norms
It is the correct thing to do.
Social norms
It is what everybody expects from me.

Messages can be shaped in a way that refer to different kinds of norms and thus have different effects on people. Besides, social norms and mental models are strong conditioners (even determinants) of behavior and it is crucial to take them into account when designing and executing public policies.

Fixed mindset —belief that certain things cannot be changed, or that one is born with some skills that cannot be changed— vs. growth mindset— things can be changed, one’s own skills can be improved. We have to foster growth mindsets.

Solutions

The EAST framework: easy, attractive, social, timely.

Strategies to address biases:

  • Decision judges.
  • Cooling period.
  • Behavioral worksheet.
  • 1-2-4: assess the decision individually, discuss with colleague, discuss in group.
  • Decontextualize and recontextualize.
  • Considering the opposite.
  • Mindsets and mind aligning.
  • Frames, pliers and padlocks: aversion to risk, incentives, committments.
  • User experience.

Report. Evaluation of the Open Data for Development program

Cover of the report for the Evaluation of the Open Data for Development program

From October 2016 to June 2017, Manuel Acevedo and I conducted the evaluation of the Open Data for Development program, a USD 15 million initiative (direct plus indirect funding) led by IDRC, the Government of Canada, The World Bank and DFID / UK Aid.

This has been a terrific experience on many levels. The most important one was acknowledging how advanced the field is and, even more important, how deep the sensation is that a point of no return has been crossed in terms of open data, open government, transparency, accountability, open development, etc. Some important outcomes will, of course, still take some time to take place, but the path is been paved and the trend is gaining momentum quickly, adding up critical mass at each stage.

The collaboration and excellent attitude of all the actors involved in the project (we interviewed 41 people and read more than 150 working documents and 128 bibliographic references) was another aspect of the work that is worth highlighting. Special gratitude goes to Fernando Perini, Erika Malich, Katie Clancy and Tricia Wind at IDRC. It is not every day that one finds people so willing to have their work thoroughly scrutinized, to explain things without making excuses, to expect the evaluation to be an opportunity to learn and to improve. Same goes for the team at the World Bank and the Government of Canada (especially Amparo Ballivian and Yohanna Loucheur, respectively).

This impression of people taking seriously their work, including third parties’ evaluation and insights is confirmed not only by the publication of the report with the evaluation of the Open Data for Development program, but also the publication of the response of the Management of the program to our evaluation, providing both context and commitment to the recommendations made by the evaluators.

Below can be downloaded the three documents generated by the evaluation: the full final report, the executive report and the management’s response.

If I am allowed to, I would like to state that both Manuel and I are quite proud of the recommendations we made at the final section of our evaluation. Of course, the recommendations come from the many and richest inputs that everyone we talked to or read about kindly gave us. These recommendations are as follows.

  • OD4D: greater emphasis on the right side of the OD4D equation (i.e. “for development”)
  • Reticulating OD4D: towards an expanded network vision for OD4D
  • Build capacity for gender-purposeful programming
  • Invest in strategic partnerships
  • Greater engagement with the D4D community
  • Support OD intermediaries
  • Place knowledge management at the core of OD4D implementation processes

We hope the evaluation and, especially, the recommendations are useful not only for the program but for the whole open data and open data for development community. We remain at the disposal of anyone in need of more information, doubts or suggestions.

Abstract:

The evaluation focuses on both accountability and learning. The primary intention of the evaluation is to provide accountability to the program’s management and organizational governance structures for program results. In addition, it reflects upon OD4D’s implementation in order to inform future programming on open data for development themes. The process was guided by five evaluative questions, on (1) Results, (2) Design, (3) Management, (4) Policy and (5) Gender. The evaluation report addresses these five topics, and also refers to some cross-cutting issues which were identified during the process. The analysis is completed with a final section with key recommendations for the upcoming new phase of the program.

Downloads:

logo of PDF file
Full report:
Acevedo, M. & Peña-López, I. (2017). Evaluation of the Open Data for Development program. Final report. Ottawa: IDRC.
logo of PDF file
Executive summary:
Acevedo, M. & Peña-López, I. (2017). Evaluation of the Open Data for Development program. Executive report. Ottawa: IDRC.
logo of PDF file
Management’s response:
International Development Research Center (2017). Management’s response to the independent evaluation of the OD4D program. Ottawa: IDRC.