How Much Evidence is Enough? Learning How to Use Evidence-Based Policy and Practice

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Evidence-based policy making is essential to good governance. But how do we know when we have enough information to make the best decisions? And how to we ensure that the decisions we are making are the correct ones?

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Importance of evidence-based policy model

Government branches use evidence-based policy making to make the best decision concerning government run programs by relying on the available research and information. The main characteristic of this decision-making model is being able to identify what works and what does not. It identifies and points out the instances where the evidence of program efficiency is lacking. The evidence-based approach makes the budgets more reliable and realistic since the policy makers are able to use evidence when making key budgeting and policy decisions. The use of evidence results into decisions that are meaningful to the nation. During the implementation of the projects, the evidence-based model becomes useful as it relies on systems to monitor program implementation and assessing key outcomes.

Governments can reduce the wastage of public funds using the outcomes of the evidence-based model. Reliance on evidence by policy makers when making budgetary choices reduces wasteful spending of funds. It also allows identification and elimination of the ineffective programs before the allocation or use of resources in the wasteful programs. Due to the improved efficiency, governments will have money to use on other important projects.

Since government is able to make an evaluation of the untested programs, the government enhances the expansion of innovative programs that deliver the best outcomes. The evaluation helps determine the viability of the programs before their implementation. Once the testing is over, governments are able to identify the best opportunities to allocate funds to achieve the best results. This ensures that the most innovative programs are fully funded to realize their full potential.

In addition, accountability is strengthened when evidence based policy making is used. People can only be called to account for their results when accurate data is readily available. The reliance on evidence requires accurate data collection and correct reporting on the operations and outcomes of a program, which makes it easier to call the agencies, managers and other providers to account for their results.

When is information enough?

Knowing exactly when the information available in enough to make a decision is often a hard task to undertake. However, too much information is sometimes counterproductive as it results in wastage of time and only complicates the decision-making process. A 1998 study by Psychologists from Princeton and Stanford on the implication of unnecessary information concludes that human mind dislikes information gaps. The research findings also confirm that people always want to gather much information, even in circumstances where they have the right information to make a concrete decision.

The study was conducted by observing how a group of people made a decision concerning the loan application based on a students’ unpaid loan amount. The respondents were placed into two groups where each group was given a differing set of information. The first group had clear and direct information while the second had ambiguous information. There were three choices available to the respondents. They would either dismiss or approve the loan immediately or delay their decision awaiting enough information to make their decision. The results of the study had 71% of the first group respondents disapproving the loan applications unlike 21% of the second group respondents. Due to the unclear information, all group two participants requested for additional information before making their decision.

Making the best evidence based decision

It is critical that decision makers avoid falling victims of wanting more information when they already have enough. They should learn to analyze the available information before proceeding to seek additional information. Some of the best practices include the following:

Setting Clear Goals

The goal of the analysis has to be as clear as possible before engaging in information analysis. Unclear goals are likely to result into paralyzed state of action. Decision makers have to avoid the paralysis by analysis, which is a state of overthinking about a decision to the point where they are unable to make any decision. Such situation will most likely arise when measurement of the performances does not meet the set goals. However, when the goal is clear but there are still some doubts about making a decision, we should only seek enough additional information only to deny or confirm the goal.

Rapid outcome mapping approach (ROMA)

ROMA is a decision-making tool developed by Oversees Development Institute and has undergone testing in several seminars globally. It is an effective 8-step approach to making effective evidence-based decision. The approach requires clear goals to avoid the paralysis by analysis.

The first step involves having a clearly defined overarching policy objective to guide the decision-making process. An accurate mapping of the policy context surrounding the issues follows the policy definition. The third step entails the identification of the key and influential stakeholders who have a role to play in the decision-making process. The stakeholder identification precedes the development of a change theory. The fifth step entails the development of strategies that will assist in the achievement of the milestones in the change process.

The sixth step in the ROMA approach is ensuring that engagement teams possess the necessary competencies to implement the already identified strategies. The competency assessment ensures smooth deliver of the necessary results and on time. The second last step requires the establishment of an action plan that will be crucial in assisting the team to meet the policy objectives identified in the first step. The final step involves the development of a monitoring and learning systems that allows effective monitoring of the change in progress.