Learning and innovation in the public sector
One of the most notorious obstacles that Latin America faces to increase general wellbeing in an inclusive manner is the lack of knowledge regarding what is the best way to design and implement a public policy. In other words, more is known about "what" needs to be done than about "how" to do it.
An important part of the knowledge that is necessary to manage public services generates precisely within the organizations that offer them. In effect, it is there that decisions are continuously made regarding the use of resources, and this flow of experiences contains essential information to generate learning regarding management, which may lead to better public services.
Thus, it is important to consider some ways in which to generate knowledge based on experience, as for example, measurements of the advance of the projects throughout time, evaluation of results associated to them, and evaluations of its impacts whether qualitative or quantitative [1]. In this respect, the international community has made efforts to promote the generation of evidence through methodologically rigorous impact evaluations, and evidence-based policymaking. However, the generalization of these practices is still modest. Why? Why is it that in some cases the State does not evaluate the impact of its programs?
One of the reasons is that evaluations have associated costs and risks that decrease the incentives to use them as management tools, leading to fewer evaluations being carried out than desirable. This implies a lower generation of knowledge and, therefore, fewer decisions based on reliable and pertinent information. However, greater and better information does not always lead to better decisions. The innovation process of policies is complex, because it depends on institutional and specific factors and because it involves many actors with interests that sometimes diverge. As a result, few innovations emerge from the application of learning derived from evidence.
Although decisions regarding innovation occur at different moments, in most cases the bureaucracy is in charge of the implementation and follow up of public programs, as well as of managing the provision of services. Therefore, to understand the management decisions taken in the public sector, it is necessary to understand the bureaucracy.
It is clear that if the bureaucrat knew that his decision to innovate would result in greater wellbeing, he would always make an adequate decision: innovate when the conditions are appropriate and not innovate if the contrary is the case. However, there is no certainty that innovation is beneficial, as there might be external factors that prevent the achievement of the desired objective. For example, an unexpected change of key officials to carry out an innovation may reduce the political and budgetary support of the proposal and, therefore, decrease its possibilities of success. Thus, when making the decision to change, the bureaucrat faces the risk of spending important resources and even undermines his institution. If the bureaucrat decides to innovate when it is not possible, or if he does not detect the possibility of innovation when he should, his poor decision may lead to worse services and, therefore, a lower probability of being promoted.
The following graph presents some correlations that inform about possible determinants of the motivation to innovate (Panel 1) and the perception regarding the receptiveness of an institution to the proposals to innovate (Panel 2) according to the worker's position and the sector he belongs. Panel 1 shows that being a boss is associated to a higher motivation to innovate; there does not seem to be a significant difference in this motivation between the public and private sector; and being a boss is not associated to a greater motivation to innovate as a result of being in the private sector, the difference is not statistically significant. Panel 2 shows that bosses in the private sector have a greater possibility of perceiving a better disposition toward innovation in their work units.
Motivation to make suggestions for improvement, and willingness of the area to accept new ideas. Differences in the probability by setor and position a/ b/
a/The graph reports the coefficients and confidence intervals to 90 percent, estimated by least ordinary squares. For the left side panel, the question used as a dependent variable was: how much do you agree with the statement that you make suggestions for improvement?. For the right side panel, the question was: how much do you agree with the statement that in your area of work new ideas are accepted? In both cases responses have a value of 1 (totally disagree) to 5 (totally agree). The scores represent the difference in the values of those variables between each group, and the vertical line is the confidence interval of the estimate of difference. The regression controlled for city and educational level.
b/ The cities included in the survey are Buenos Aires, La Paz, Sao Paulo, Bogota, Quito, Mexico City, Panama City, Lima, Montevideo, and Caracas.
Source: own, with data from 2014 CAF Survey
In Colombia the first steps have been taken toward a culture of learning and program evaluations. The country has the National System of Evaluation of Management and Results (SINERGIA, for its acronym in Spanish), created in 1994 within the National Development Plan, to generate the necessary information for compliance with the goals of the plan, which is renewed every four years. The policies to be evaluated are defined by the Comité Intersectorial de Evaluación y Gestión y Resultados (Evaluation, Management, and Results Inter-sectorial Committee), and third parties hired through a system of competitive bidding carry out the evaluations. SINERGIA also provides technical supervision for the evaluation, and publishes a document with the results obtained in each case, which may be consulted on their web page.
The Reporte de Economía y Desarrollo 2015 (RED) (Economy and Development Report), developed by CAF, Development Bank of Latin America, presents evidence of a diagnosis of the status of the monitoring and evaluation of public policies in the region, and analyzes, in first place, the process through which experience becomes knowledge from the perspective of those who decide and act in public management, emphasizing the incentives and political risks they face. In second place, it explores how the learning can become innovation in public management, new ways to do things, identifying the institutional factors that may favor this process. The idea is to contribute to think about the development of public institutions that are capable of learning about what they do and not waste the learning.
[1] Impact evaluations differ form evaluations of results as they seek to quantify the part of the observed result that may be attributed with confidence to the project or policy.
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