12. Data Use in Planning and M&E 1. Indicator Database District Data Trending Indicators Activity Prioritization Plan M&E Medium Term Development Plan Annual Action Plan Plan Implementation 2. Project Monitoring Database
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16. Coordinated and Integrated Approach Take into consideration Functionality, Capacity, Flexibility at each level Build from and integrate existing systems Take the time pilot different approaches across Ghana before scaling Process is more important than the tool
Editor's Notes
Data is important at all levels of government. The national level of government utilizes information on indicators to track progress against the Medium-Term National Development Policy Framework. Also, information on project implementation and expenditure at the national level ensures accountability. The district level utilizes information for planning, implementing and monitoring/evaluation district plans.A coordinated and integrated approach is needed to ensure there are functioning data systems at all levels of government.
One such indicator may be education quality.
In one district, the district education office had noted education quality as an issue and had stated an improvement in the quality of education as a goal in the previous plan. When compiling the data, it was found that enrolment had increased over the past 3 years and that test results had decreased.
After receiving and analysing the data, the Management Information System Officer determined that the school with the highest student-teacher ratio (1:52) had the lowest passing rate (5% passing rate) whereas the school with the lowest student-teacher ratio (1:6) had the highest passing rate (71%). With further analysis, it was determined that some schools had a low student-teacher ratio, but also low results. The GES Director has determined a number of actions to take to further understand why there is low performance of schools in the district in order to develop a strategy to improve the quality of education. Without accessible and analysable data at the district this could not happen.
New data systems are consistently introduced at the district level. The result is that several parallel district data systems (DDS) are set-up, often with similar purposes. With the ever increasing number of systems at the district, it is less likely for any one system to succeed and become institutionalized. There becomes more of a likelihood of failure rather than success, and with each pass of the cycle, the problems with DDS become compounded. Each step of the cycle is described below. New System: The new data system is usually created to fill the gap of a previously created data system or to serve a specific purpose outside of the district. As a result, it is often created with little input from stakeholders in the district, although its likelihood of sustainability is based on relevance at the district level. A new stakeholder will enter the district with a specific need for data without first gaining an understanding of the existing situation at the district level, including existing district data systems. Implement at District: Officers are handed a pre-packaged data ‘system’ and expected to implement it usually with little pre-consultation other than a training on how to use the system. This ‘system’ is often just a data management tool. Does not sustain: Often the system does not meet the needs of the district users, and/or cannot be adapted or maintained easily. Since it does not meet the needs of officers it falls through the gap, and is not used. Sometimes this happens when a system is introduced without a continuous support structure in place, or when designers misunderstand the relevance and necessary processes required for effective implementation. New system: Since the previous system falls through the gap, a new and technically improved system is created by a new stakeholder, once again not taking into consideration district needs. Yet another system is introduced without input from district users and the cycle continues.
Data is often collected by district officers to meet the need of donor projects and Government of Ghana initiatives. Data is stored in reports, but how useful is this data for district level decision making?
There are too many reports and data is easily lost.
Information can effectively be stored in spreadsheets and databases, but still, it’s easy for data to get lost. Data stored in spreadsheets is a good start, but how do district decision makers turn data into information to inform decisions?
Every four years, MMDAs develop Medium-Term Development Plans to establish broad goals and objectives. Every year, districts develop Annual Action Plans to implement projects. District data should be the hub of this process, informing and monitoring the plans. District data systems should contain community level data, collated at the Area Council and District level. MTDP – Trending relevant indicators over time at the area council and district level allows districts to identify key issues to inform the districts goals, objectives, strategies, and program of action. AAP – Community level data should be used to prioritize project and activities to be implemented. Plan Implementation and M&E – District Plans should then be implemented and continuously monitored, and the monitoring data inputted back into the District Data System to inform the next planning cycle.
District decision makers are aware of the decisions they make on a: (1) daily basis, (2) yearly basis through the annual action plans, and (3) long-term basis through the Medium Term Development Plan. The question that should be asked is what data is needed to inform those decisions. The water data in this table can then be turned into information by effectively sorting and analyzing the data on a spreadsheet. For example, in this table, if a decision had to be made where to drill 1 borehole, where should that borehole be drilled?
With this additional information where would you drill the borehole?
With this additional information where would you drill the borehole? Information allows district decision makers to make better decisions. Having different pieces of information together in one place assembles the pieces of the puzzle to capture the whole picture.
Build from Existing Systems: Thoroughly understand existing systems and what needs to change before a new system is proposed. Focus on understanding the reality of district officers in the district by working alongside them and at the regional, and national levels of government. Some questions to consider include what systems already exist? What are the capacity, functionality and flexibility requirements in developing, establishing, and sustaining a district data system? Should a new system be introduced or an existing one enhanced?Proof Before Scale: Explore what works, and take note of what does not work. A system should be proven to work before it is scaled to multiple districts. Focus on designing solutions, experimenting with district officers, and revising them as needed to ensure they work.Processes Before Tools: Focus on the process of change rather than a specific tool for change. The district databases are a tool, but the process is what will create sustainable change. This process would define the attitudes and behaviors necessary for use of the District Data System to become common practice. The tool on its own is not useful without processes for maintenance and sustainability.