16 Access to computers, digital literacy, and perceptions of data security impose limitations on digital data storage. Not all department offices have access to computers: estimates suggest there is one computer for every 30 civil servants.37 Those who do have computer access often have little or no training in file management or the use of basic data-storage and -analysis programs such as Excel. Local officials have remarked to The Asia Foundation that paper data storage is safer and more secure—“you can’t hack paper”—while digital storage has significant risks of being lost or tampered with. TABLE A. Example government spreadsheet Village Households Disabled persons Elderly persons (over 65) Internally displaced persons Village A 65 2 10 0 Village B 87 2 8 Village C 113 2 14 Village D 35 Village E 47 5 1 9 0 2.4 HOW IS DATA ANALYZED AND USED AT THE LOCAL LEVEL? There is great variation in how much use township department offices make of the data they collect, and there is no established culture of data-based decisionmaking. Most data collected at the local level is used simply for recordkeeping or to answer requests from parent agencies. While there are many examples of township department officials using data to inform their decision-making, data is not systematically and routinely used in this way. Many township department offices view the bulk of the data they collect as something for use by district, state/region, and Union departments and ministries. For some officials, the data collected by their department serves purely to satisfy queries from higher-ups. While data practices at those higher levels are beyond the scope of this report, data is often aggregated to provide sectoral or national snapshots of the country’s development—through the Central Statistical Organization’s Myanmar Statistical Yearbook and Selected Monthly Economic Indicators,38 for example, or the Planning Department’s GDP calculations. Analyses of these types of data may be useful for shaping laws and policies at the Union or state/region levels, but they do not lend themselves to developing township-specific policies or supporting township-level decision-making. There is, therefore, a real need for greater data use at the township level to shape local decision-making. A common form of data use at the township level is in summary tables of descriptive statistics for basic analysis. For example, information such as demographic data, revenue collections, birth and death records, and departmental infrastructure investments may be aggregated into a table for review by department officials. Such tables allow for the review of basic administrative functions—for example, how have revenues varied among different areas, against targets, and in comparison with previous years—but they shed no light on the differences among communities, information that may be needed for emergency response or decisions about specific services. More complex data analysis and data visualization by township department offices is rare. For example, while department officials may carry out analysis to understand tax collection, they may not calculate averages or percentages that could be used to understand data trends in a more sophisticated way. Complex descriptive or predictive analytics, such as through algorithmic or econometric models, does not occur at the local level. The absence of more sophisticated data analysis limits the ability of departments to build an evidence base for making decisions. Data is often presented in simple tables, rather than in visualizations such as charts or graphs or mapped spatially. The use of other forms of data