Applied Research PDF
Document Details
Uploaded by Deleted User
Tags
Summary
This document is about applied research, data analysis, and how it can be used in local government. It provides an overview of data, evidence, research, and its importance to the work of LGOOs (Local Government Offices). The document outlines several concepts of applied research, different research types, and details topics on this theme.
Full Transcript
Table of Content Topics Discussed Page No. Chapter 1 Designing with Evidence 1 Applied Research: Making Sense of Data, Evidence, and Insights 1 Understanding DILG Datase...
Table of Content Topics Discussed Page No. Chapter 1 Designing with Evidence 1 Applied Research: Making Sense of Data, Evidence, and Insights 1 Understanding DILG Datasets 6 Chapter 2: Unpacking the Context 12 Context Analysis 12 Analysis Tools 13 Complex Problem: Social Issues 32 Capacity Assessment 34 Capacity Development Framework 36 Data Analysis 37 Data Reporting 39 Chapter 3: Identifying Capacity Solutions 44 Data Life Cycle 44 Analytical Thinking and Data-Driven Decision Making 44 Solution-Finding Framework and Tools 46 Capacity and Performance 55 Capacity Change Matrix 56 Four Fields of Conversation 59 Chapter 4: Measuring for Results and Transforming Information to 60 Insights Results-Based Monitoring and Evaluation 61 Result Chain 62 Performance Change Matrix and RBME 65 Communicating Insights: Basics of Data Visualization 66 Visualization Tools 68 DILG Best Practices 73 Communicating Insights: Developing a Policy Brief 76 MODULE 2: APPLIED RESEARCH AND DATA ANALYSIS Module Coordinator: RD PAISAL O. ABUTAZIL, REGION IX Chapter 1: Designing with Evidence - Provide an overview of data, evidence, research, and its importance to the work of LGOOs, in particular in making informed programs, projects, and activities; - Fundamentals of data and research t build evidence for informed programs, projects and activities, Topic 1: Applied Research: Making Sense of Data, Evidence, and Insights Coach: LGOO VII Christian “YanYan” Nagaynay, DC-LGCDD, RO VI LGOO IV Kien Develos, LGA Basic Research - Also known as “fundamental” or “pure” research. Applied Research - Acquisition of knowledge on the practical application of the theoretical base already built up which is expected to solve a critical problem. - Designed to solve practical problems of modern work, rather than to acquire knowledge for knowledge’s sake. - Finding solution(s) to a real-life problem requiring an action or policy decision. - Problem-oriented, and action-directed. - It has immediate and practical use. 1 Characteristics of Applied Research 1. Solution specific and addresses practical questions; 2. Collection and analysis of data to examine the usefulness of theory in solving practical and educational problems; 3. Precise measurement of the characteristics and description of relationships between variables of a studied phenomenon; Applied Research Designs 1. Action Research Design a. Collaborative and adaptive research design that lends itself to use in work or community situations. b. Design focuses on programmatic and solution-driven research rather than testing theories c. Potential to increase the amount they learn consciously from their experience. The action research cycle can also be regarded as a learning cycle. 2. Case Study Design a. An understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships. b. Design can extend experience or add strength to what is already known through previous research c. Examines contemporary real-life situations and provides the basis for the application of concepts and theories and extension of methods. 2 3. Causal Design a. Helps researchers understand why the world works the way it does through the process of proving a causal link between variables and eliminating other possibilities; b. Replication is possible; c. There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared. d. Conditions necessary for determining causality: i. Empirical Association – a valid conclusion is based on finding an association between the independent variable and the dependent variable; ii. Appropriate Time Order – conclude that causation was involved, one must see that cases were exposed to variation in the dependent variable; and iii. Nonspuriousness – a relationship between two variables that is not due to variation in a third variable. (with 3rd party) 4. Descriptive Design a. Provides answers to the 4 Ws (What, when, where, and who) and 1 H (How) associated with a particular research problem; b. Used to obtain information concerning the current status of the phenomena and to describe “what exists” with respect to variables or conditions in a situation. Research Methodology - Is an outline of the overall data collection and analysis strategy that will be used to implement the research cycle - It should be: o Compatible with the preliminary data analysis plan; o Design in a way that ensures the intended scope of the research (i.e. objectives and research questions) can be feasibly achieved to the required quality, given the time, resources, and access available. - 3 Components in designing Methodology o Selecting the overall research method; o Selecting the appropriate data collection approach(es) o Designing the sampling strategy 3 Types of Research Method: Quantitative, Quality and Mixed Methods 4 Factors to be considered when choosing one research method over another? a. Overall applicability b. Time (key planning and decision-making milestones to inform) c. Resources available a. Material Resources b. Financial Resources c. Huma Resources d. Access to population Balance: 1. Time 2. Quality 3. Resources / Access Criteria Distinction for the use of Quantitative and Quality The most powerful research method? - Mixed method – if time, access, resources allow. - Bu ultimately, it depends on the research objectives. Individual workshop # 1 Medina-Guce, Czarina. 2022. Making Sense of Improved Local Government Units’ Comprehensive Development Plan (CDP) Compliance: Policy Structure, Support, Incentives. Department of the Interior and Local Government. 5 Evidence in the life of LGOOs) PDMU Chief John Joseph Vasquez, DILG 4A Knowledge Skills Attitudes Research Method Data Analysis Open-mindedness Data Collection Method Critical Thinking Curiosity Domain Knowledge Communication Skepticism Ethical Awareness Understanding DILG Datasets Data - A collection of information gathered by observations, measurements, research, or analysis. They may consist of facts, numbers, names, figures, or even descriptions of things. Dataset - Is a set or collection of data. - This set is normally presented in a tabular pattern. Every column describes a particular variable and each row corresponds to a given number of data. DILG Sources of Data: 1. DILG Mandate and Program o Citizen Satisfaction Index Survey (CSIS) CSIS is a set of data tools designed to collect and generate relevant citizens’ feedback on the local government’s service delivery performance and on the citizens’ general satisfaction. Social Welfare Governance and Response Public Works and Infrastructure Environmental Management Economic and Investment Promotion Health Support to Education o Seal of Good Local Governance (SGLG) - RA 11292 Is an award, incentive honor, and recognition-based program for all LGUs and is a continuing commitment for LGUs to continually progress and improve their performance. Financial Administration Disaster Preparedness Social Protection and Sensitivity Program Health Compliance and Responsiveness Program for Sustainable Education 6 Business Friendliness and Competitiveness Safety, Peace and Order Environment Management Tourism, Heritage Development, Culture and Arts Youth Development o Devolution Transition Plan (DTP) Analytics EO 138 Full Devolution dated June 1, 2021 JMC No. 2021-01 guidelines for DTPs dated August 11, 2021 o Monitoring and Evaluation of Projects Bottom-up-Budgeting (BuB) Payapa at Ligtas an Pamayanan (PAMANA) Sagana at Ligtas na Tubig sa Lahat (SALINTUBIG) Assistance to Disadvantaged Municipalities (ADM) Assistance to Municipalities (AM) Financial Assistance to LGU (FALGU) SGLG Incentive Funds o Pre and Post Evaluation for Seminars/Trainings o Quality Management System o Local Development Planning Comprehensive Development Plan (CDP) Comprehensive Land Use Plan (CLUP) Local Disaster Risk Reduction Management Plan (LDRRMP) Gender and Development (GAD) Plan and Budget Peace and Order and Public Safety (POPS) Plan And other plans 7 o LGU Segmentation Results for CapDev Support 8 2. LGU Programs, Plans, and Performance Results o Governance Assessment Report (GAR from SGLG o POC/ADAC/CFLGA/POPs Functionality o Gawad Kalasag of the Office of the Civil Defense o LCAT-VAWC Assessment o Gender-Responsiveness o Local Plans/Programs (CDP/CLUP/CBMS) o Ecological Profile o Other available data 3. Related research, studies, and policy recommendations o Policy Briefs o Literacies Creating Value from Datasets - Creating value in a dataset involves transforming raw data into information that can be used to make informed decisions and gain insights. Steps: 1. Defining the question (Problem Statement) a. What is its intended use? b. What questions it needs to answer? c. What are your objectives? 2. Collecting the data a. Quantitative (Numeric) Data b. Qualitative (Descriptive) Data c. Sources of Data i. First-party Data (directly from clients/public) ii. Second-party Data (first-party data of other organizations) iii. Third-party Data (aggregated from numerous sources) 3. Cleaning the data a. Remove major errors, duplicates and outliers b. Remove unwanted data points c. Bring structure to your data d. Filling in major gaps 4. Analyze the data a. Analyze the data to uncover patterns, trends, and relationships that can provide insights and answer questions. b. Techniques: i. Univariate or bivariate analysis ii. Time-series analysis iii. Regression analysis 9 c. Types: i. Descriptive Analysis – identifies what has already happened ii. Diagnostic Analysis – focuses on understanding why something has happened iii. Predictive Analysis – allows to identify future trends based on historical data iv. Prescriptive Analysis – allows making recommendations for the future 5. Visualize the data a. Use charts, graphs, and other visualization to communicate the insights and findings in an understandable and compelling way. 6. Share and Collaborate a. Share the data and insights with stakeholders and collaborators to get feedback and generate new ideas. This can lead to new discoveries and opportunities for further analysis. b. Should be clear and unambiguous Data Ethics and Confidentiality - Critical considerations in data analysis as they protect individuals’ privacy, build trust with stakeholders, ensure compliance with laws and regulations, and mitigate risks. Knowledge Utilization - In data analysis, refers to the application of insights and findings derived from data analysis to real-world decision-making process; - It involved taking data-driven insights and using them to inform strategic and operational decisions in various industries and contexts; - This process involves interpreting the data to develop actionable recommendations, communicating the findings to stakeholders, and incorporating the insights into decision-making processes to improve organizational outcomes. DATASET – CREATING VALUE – KNOWLEDGE UTILIZATION = DATA ANALYTICS - Data analytics is the science of analyzing raw data to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption. - Data analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain. Data is extracted and categorized to identify and analyze behavioral data and patterns, and techniques vary according to organizational requirements. 10 Usage of Data Analytics - Data analytics help a business optimize its performance, perform more efficiently, maximize profit, or make more strategically-guided decisions. - Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies can help reduce costs by identifying more efficient ways of doing business and by storing large amounts of data. A company can also use data analytics to make better business decisions and help analyze customer trends and satisfaction, which can lead to new and better products and services. - Data analytics is primarily conducted in business-to-consumer (B2C) applications. Global organizations collect and analyze data associated with customers, business processes, market economics, or practical experience. Data is categorized, stored, and analyzed to study purchasing trends and patterns. The Data Analyst - A data analyst collects, cleans, and interprets data sets in order to answer a question or solve a problem. They work in many industries, including business, finance, criminal justice, science, medicine, and government. Individual Workshop # 2 Medina-Guce, Czarina. 2022. Participatory Governance Metrics for Local Special Bodies: Lessons from Pilot for Expanded Implementation. Department of the Interior and Local Government. 11 Chapter 2: Unpacking the Context - The goal is for learners to experience the type of analytical thinking and evidence that LGUs use to identify the factors that contribute to the LGU’s performance; - To relate the importance of data, evidence, and research for LGU Context Analysis and factors of their performance; and - Using data and evidence for LGU Context Analysis and factors of their performance. Coach: Alfrainer Partido, Cordillera Alvin Rex Lucero, Region IX Chris Sequential Data – One data relates to another data. 2 Things that PREVENTS development: 1. Absence of Evidence-based data 2. Poor Analysis 3 “I” n Analysis 1. Items, Statistics (Figures) , and Indicators 2. Information 3. Intelligence Context Analysis - Is a method to analyze the environment; - It allows stakeholders to better understand the sociocultural, political, economic, and geographic factors that give rise to a crisis and will enable their response; - It’s the 5Ws and 1H of a situation or event. Its Importance in CapDev - Analysis of the LGU’s situation and capacity issues which affects their development and performance goals enables the LGU to look at the relationships of performance and capacity factors. - Before conducting a capacity assessment, there should be a clear understanding of the broader context of the LGU o Factors that contribute to the LGU’s performances o Stakeholders and their interests 12 Context Analysis Tools usage: 1. Spot Mapping - BDP 2. Resource Mapping – BDP 3. Fishbone Analysis – Legislative Agenda 4. Impact Chain Analysis – BDP & LCCAP 5. Hazard Mapping (BDP, CDP, CLUP, LDRRMP) 6. Poverty Mapping (CDP and BDP) 7. PESTLE Analysis (RDP) 8. Problem Tree (BDP) 9. Vision Reality Gap (CDP, and POPS Plan) 10. Problem-Solution Finding Matrix (CDP) Analysis Tools 1. Spot Mapping o A spatial or physical-oriented data gathering where important landmarks and physical characteristics of the barangay are gathered. Basic Services and Facilities (Sec.17(a) of RA 7160) o Use of Global Positing System (GPS) in recording the tag 2. Resource Mapping o Assess what communicated have to offer by identifying assets and resources within the locality which may be utilized for community building; o Data may be presented through inventories, maps, figures, & matrices; o Method of showing information regarding distribution, access and use of resources; topography, human settlements; and activities of a community from the perspective of community members; o Used for identifying and examining relationships between community’s resources, topography, settlements, and activities; o Identifying problems, possibilities, and opportunities. 13 3. Fishbone Analysis o A cause-and-effect discovery tool that helps figure out the reason (s) for defects, variations, or failures within a process. In other words, it helps break down, in successive layers, root causes that potentially contribute to an effect. Categories: 1. Man/Mind (People) 2. Method (Process) 3. Materials (Product) 4. Machine (Program) 5. Medium /Measurement (Policy) 6. Milieu/Mother Nature (Place/Environment) 4. Impact Chain Analysis 14 5. Hazard Mapping o Process of establishing geographically where and to what extent a particular phenomenon is likely to pose a threat to people, property, infrastructure and economic activities. It is the process of identifying and displaying the spatial variation of hazard events or physical conditions; o 2 types of Hazard Map i. Resident-Educating Type – the main objective of this map is to provide the residents with information on the range of possible damage and disaster prevention activities. ii. Administrative Information Type – The main objective of this map is to inform the administration so that the maps can be used in warning and evacuation system. o Systems: GeoAnalyticsPH or HazardHunterPH 6. Poverty Mapping o Strengthen through RA 11315 Community-Based Monitoring System (CBMS); o Use of Statistical Simulator; o Null – data not applicable to households (replace Null with “0”); o A spatial representation and analysis of wellbeing and poverty indicators; o The Indicators are carefully selected to capture the multiple dimensions of poverty. These indicators define the basic criteria for attaining a decent quality of life and correspond to the minimum basic needs. i. Dimensions of poverty: 1. Health 2. Nutrition 3. Housing 4. Water and Sanitation 5. Basic Education 6. Income 7. Employment 8. Peace and order o Together, these indicators provide information not only on how poor a community is, but also on who in the community is poor, and where. 15 16 17 Overlay of Poverty and Hazard Mapping 7. PESTLE Analysis o Method, originally intended for organizational analysis, entailing a variety of steps and techniques to gather relevant knowledge on the macro environment, needed to understand key factors which may impact (direct or indirect) the intervention; o It is built as a guiding checklist, helping to systematize the collection of specific relevant factors – i.e. economic trends, social attitudes, technological developments, etc. - that are significant in the intervention design phase; o Pretext of SWOT Analysis; o May include positive and negative issues. 18 8. Problem Tree o Helps stakeholders to establish a realistic and overview and awareness of the problem by identifying the fundamentals causes and their most important effects; o Output: Tree-shaped diagram in which the trunk represents the focal problem, the roots represent its causes and the branches its effect. Such a problem tree diagram creates a logical hierarchy of causes and effects and visualizes the links between. o Creates a summary picture of the existing negative situation. o Step by Step Procedure: i. Identify existing problems within the problem area/domain of interest (brainstorming) A problem is not the absence of a solution, but an existing negative state or situation; Distinguish between existing, impossible, imaginary, or future problems. ii. Define the core problem (focal problem or centerpoint of the overall problem) iii. Formulate the causes of the core problem Consider that the problems identified in step 1 can also be causes of the core problem iv. Formulate the effects (consequences) of the core problem Consider that the problems identified in step 1 can also be effects of the core problem v. Draw a diagram (problem tree) that represents cause-effect relationships (problem hierarchy) The focal problem is place in the center of the diagram, forming the trunk of the tree; Causes are placed below and effects above, in sub- dividing roots and branches (like a mind map); If possible, all causes/effects of a problem should be on the same horizontal level. vi. Review the logic and verify the diagram as a whole with regard to validity and completeness. If necessary, make adjustments. Question to ask for each problem: are these causes sufficient to explain why this occurs? 19 20 Group Workshop # 3: Problem Tree 9. Vision Reality Gap o In between vision and current reality lies an enormous “chasm” that must be crossed in order to realize the desired future; o Determination of the Current Reality to the Vision or the desired future; o Measure of the difference between the end state and the existing situation; o This type of analysis shows: How large the difference is between the vision ideal state of the LGU and the existing situation: o Step 1: o Review the sectoral descriptors and their corresponding success indicators generated in connection with the formulation of the vision statement. Check indicators for the completeness of coverage. See the indicators are expressed in terms of maximum values or superlative degree. o Step 2: o Review the relevant characterization of each sector in the Ecological Profile, LDI Matrix, and other sources. o Step 3: o If quantified values for both the success indicators and their equivalent indicators in the accomplished LDI Matrix are available, simply subtract the current reality values in the LDI Matrix from the success indicator values. The difference is the vision – reality gap. o If the quantified values are not available, use the simple current Reality Rating Scale. The rating should be determined through a consensus. Then subtract the current reality rating from ten (10). The difference is the vision – reality gap. 21 10. Problem-Solution Finding Matrix (PSFM) o A tool used to diagnose development issues or what is known as problem-finding phase and determining appropriate policy interventions or what is called the solution-finding phase; o The problem-finding phase includes making meaningful observations from the available information, determining the causes or explanations of the observed conditions and exploring the positive and negative implications if no significant intervention is made; o The solution-finding phase entails identifying the appropriate policy interventions to curtail the negative implications and strengthen the positive ones. o Discerning Condition and Identifying Underlying Causes 22 Expected Output: i. Observed Condition Describes the GAP between Reality or current condition and that of the Desired State (VRG); Compare data for study area with known standards or benchmarks – if no time-series or spatial distribution of data is available; o Scenarios: Study area is Below Above, or Same as standard or benchmark Example: o World bank adopted poverty threshold of 1.90 dollars to 2.15 dollars ii. Explanation Provides supporting details to the Observed Condition; Entails probing into the causes or explanations behind the observed conditions; Asks the question “Why?” Provides the clue to finding more fundamental solutions by attacking the causes rather than the symptoms of the problems. iii. Policy Option Refers to the General Plan of Action in addressing observed condition o Notes: If negative implications predominate, then the observed condition can be regarded as a problem. Formulate policies that either mitigate the inconvenience or solve the problem permanently. If positive implications predominate, then the observed condition may be regarded as potential. - Extended PSFM o To highlight the risks in its observed condition, the sensitivity and adaptive capacity that can affect the cause of the condition, the positive implications contributed by high adaptive capacity and negative implications due to vulnerability and risks. o To capture the issues and problems posed by climate and disaster risks and presents the policy interventions that both address current needs and anticipate future impacts of climate change and disasters. o To capture the Vision-Reality Gap analysis and cross-sectorally matched with other issues and challenges. 23 o To further detail the implications of the technical findings in identified decision areas and classify policy interventions into PPAs, legislative agenda and capacity development requirements. 24 Group Workshop # 4: Problem-Solution Finding Matix 11. Causal Loop o Is an analytical tool used to understand complex issues or problems that may affect the performance of LGUs. 25 o Can be used to trace the causes and effects of a problem, or a series of problems, and how they link or interact with each other; o Identifies what variables LGUs can effectively influence and what actions are beyond their ability to change. Purpose of Causal Loop 1. Offers a comprehensive view of complex issues in the LGU; 2. Provides an opportunity for stakeholder engagement; 3. Provides a coherent picture of the issue, having incorporated the views of different stakeholders. When to use the Causal Loop? - Issue identification and analysis - Solution Generation 26 Steps of Causal Loop = Systems Thinking 1. Identify a complex issue; a. Has causes and effects that have been persistent over and affect various stakeholders; b. Those which past initiatives have failed to fully solve; c. Perspective may be societal; d. Interventions must be systematic, participative, and emergent. e. Examples: 2. Identify the factors or variables contributing (cause or explanation) to the problem and their consequences (effects/implications); o List all variables (can be causes, effects or other variables that may contribute to the theme (issue); o Use Neutral Nouns (avoid verbs and action phrases) – instead of “increasing CICL” just use “CICL”; o Variables contributing to the problem and their consequences. 3. Show the links between variables by identifying what is influencing what; o Using arrows, link the factors to generate a system view of the problem, showing interrelated ness, causes and effect; o Variables/factors may be added esp. in places with missing intermediate variables. 27 4. Label the relationship between variables as “s” for similar or “o” for opposite o Relationship between Variables: 1. Same/Similar – when one variable goes up, the other goes up; when one goes down, the other also goes down. 2. Opposite – When one variable goes up, the other goes down, the other goes up. 28 5. Check if the causal loop depicts the story as it is understood by stakeholders. - Inter relationships of variables or factors affecting the problem; - Making the data statements (critical gaps in LGU performance); - Determine whether the LGU is doing well (green), somewhat doing well (yellow) or not doing well (red). - Making data statements (Critical gaps in LGU Performance) – “the yellow sticky notes”. 29 - Notes: o Story can be told in positive or negative language; o Loops need not close o Some factors may not yet link to any of the loops; o Original focus issue may turn out not to be the central issue. 12. Stakeholder Analysis 13. Local Development Indicator System o An Analytical Tool that Portrays information in 3 dimensions: i. Sectoral Dimension 1. Social 2. Economic 3. Environment 4. Physical/Infrastructure 5. Institutional ii. Temporal Dimension 1. Comparison between the latest and earlier data to describe change over time iii. Spatial Dimension 1. Compares one LGU with higher level LGUs or same class LGUs o LDIS are expressed in terms of: Ratio Proportion Percentage Average Per Capita Share o Rationalized Planning Indicator and Data Set (RaPIDS) Customization of Database at the local levels; A tool developed under LGU PFM 2 Project that aims to guide local planners in identifying development indicators that specifically applied to their LGU’s needs and characteristics; RaPIDS is a shopping cart for LGUs (they will choose indicators) 30 RaPIDS generated data: LDIS (Time, Space, and Sectoral) 31 Compare data for study area with known standards Unpacking the Context through Systems Thinking Coach: Christopher Llarenas Nature of Problem Cynefin Framework by D. Snowden and M. Boone Context Domain Approach Obvious (Simple) Problems Best Practice Sense – Categorize – Respond Complicated Problems Experts Sense – Analyze – Respond Complex Problems Emergence Probe – Sense – Respond Chaotic Problems Rapid Response Act – Sense – Respond Complex Problem - Beyond the scope of any single organization to understand and respond to; there is often disagreement about the cause of the problems and how to address them; and the problems can only be addressed, but not completely solved. What we need to understand? - Social issues are complex - Systems Thinking and Societal Learning are prerequisites for sustainable change. Nature of Complex Social Issues Nature of High Intervention Methodology Complexity Approach Dynamic Cause and effect are far Systemic Systems in time and space Thinking Social People who are part of Participative Multi- the problem look at Stakeholder things differently Engagement Generative Solutions to the Emergent Creative problem/s are not in sight 32 Systems Thinking (using Causal Loop) - Is a disciple for seeing wholes. It is a framework for seeing interrelationships rather than things, for seeing patterns of change rather than static ‘snapshots’. Today, systems thinking is needed more than ever because we are becoming overwhelmed by complexity. Group Workshop # 5: Causal Loops Other Causal Loop Notes: - Comprehensiveness of Causal Loop other than the other tools because it targets holistic approach on various sectors and stakeholders; - It requires problems and solutions from different sectors; - It is a multi-stakeholder/sectoral process; - Should be supported by datasets/evidences; - This tool helps LGU Offices in realizing that importance of considering interconnectedness of one operations to the other and deviates “silo or capsulated” approach within each offices; - The tool determines specific causes and effects and connects variables revolving around the complex societal issue. 33 Capacity Assessment Coach: Alfrainer Partido Analysis, Assessment, and Development Context Analysis - What are the factors in the internal and external environment facilitate or hinder the achievement of performance goals? - Who are our stakeholders? Capacity Assessment - What are the performance issues that need to be addressed? - What capacity do we need to improve to address the performance issues? Capacity (means) - Ability of LGUs to perform functions to fulfill their accountabilities and produce desired results. Performance (end) - Effectiveness of the LGU in doing its mission or what its mandate says, and producing desired results. 34 INPUTS to IMPACTS Capacity Assessment - Is the process of identifying the elements that facilitate or hinder the performance of an LGU; - It aims to determine the core factors that need to be addressed to improve performance; - The process of analyzing capacity uses a framework called the Capacity Pillars; - These are factors that indicate an LGU’s capacity or its “ability to perform functions to fulfill their mission and deliver desired results.” 35 Capacity Development Framework Basis of the 6 Pillars 1. Goals (SDGs, PDP, and other related plans) 2. Vision (LGU) 3. Objectives (LGU) The 6 Pillars (Institutional only) 1. Structure – Presence of appropriate structure with defined authority and accountability for performing necessary functions; (Excludes infrastructures and equipment, materials, and supply); 2. Competency – Knowledge, skills, and attitude of people who need to perform their assigned functions in the program; 3. Knowledge and Learning – Mechanisms for generating, analyzing and using data and information as basis for decision-making and continuous improvement; 4. Management Systems – Systems, processes and procedures for managing programs; 5. Enabling Policies – Presence of policy support for PPA implementation planning, developing, implementing, monitoring, and evaluating delivery functions, programs, and projects. 6. Leadership – presence of mechanism for defining one’s vision, mission and values, setting strategic directions, and ensuring transparency and accountability. 36 Capacity Development - Process by which individual competencies and institutional capacities are enhanced through strategic and integrated interventions to equip and empower LGUs to fulfil their accountabilities and produce desired/results. Samples of Performance Issues and Capacity Issues Data Analysis / Interpretation Purpose: - To help assess or describe) the extent by which projects are meeting their intended objectives or desired results; - To understand or seek explanations as to why a project is doing poorly or performing well; - To provide clues to problems and identify possible actions needed to improve project performance; and - To provide project managers with a sound basis for decision making. Basic Steps: 1. Aggregate collected data a. Check data quality b. Devise dummy tables c. Aggregate data per indicator 2. Examine aggregated data a. Compare latest outcomes with outcomes from previous period; b. Compare outcomes with predetermined targets; c. Compare outcomes with set standards or achievements at the national level. 3. Examine “breakout” data a. Breakout latest outcome data by vaious categories e.g. by type of LGU b. Compare latest outcomes for each category with previous period; c. Compare latest outcomes for each category with pre-determined targets. 4. Examine indicator findings 5. Make sense of the numbers 37 Statistics in Data Analysis Quantitative data – numerical and analyze with statistics. 1. Descriptive Statistics a. Used to describe and analyze data collected about a quantitative variable; b. Describes how many and what percentage of a distribution share a particular characteristic; c. Ex: 33% of the respondents are male and 67% are female 2. Inferential statistics: a. Used with random sample data by predicting a range of population values for quantitative or qualitative variable. b. Ex: Most of the respondents are female due to the context and limitation of the problem. Distributions - Measures of Dispersion o How different the data are o Example: How much variation in the ages? - Measures of Central Tendency o How similar the data are o Example: How similar are the ages of the people in this group? o The 3-M’s: Mode: most frequent response Median: Midpoint or Middle Value in a distribution Mean: Arithmetic Average o Which to use depends on the type of data you have Nominal Ordinal Interval Ratio Other Ways of Working with Data 1. Ranking – ordering or sequencing 2. Trend Analysis 3. Cross-Tabulations 38 Data Reporting Keys to Writing Reports 1. Keep purpose and audience in mind; 2. Use words that are: simple, active, positive, familiar, and culturally sensitive; 3. Avoid abbreviations and acronyms; 4. Limit background information to what is needed, place technical information in an appendix; 5. Provide enough information about your data collection methods so others can judge its credibility; 6. Write an executive summary; 7. Organized around major themes or items of inquiry; 8. Place major points first. Lead each paragraph with your point; 9. Support conclusions and recommendations with evidence; 10. Place technical information, eg., survey instruments in appendix; 11. Leave time to revise, revise, revise!; and 12. If possible, have an external reviewer with expertise on the issues and knowledge, review the final draft. Graphical Presentation - Add interest; - Communicate information more clearly than text; - Attract reader’s eyes to particular point; and - Increase the impact of a report. Characteristics of Good Graphics - Simple; - Communicate without needing text; - Consistently numbered and titled; - Sources provided and credit given; - Called out in the text; - Correctly placed in the text; - Permission to us ( id needed) - Easily reproduced; - Culturally appropriate; - Patterns can be distinguished; and - Clearly labeled. Kinds of Visuals: 1. Illustrations – maps, sketches and line drawings, photographs; 2. Charts and Graphs – organization charts, Gantt charts, graphs; 3. Tables – data tables, classification tables (matrices) 39 Connect Narrative to Illustration - If you use a picture or illustration, be sure to use the narrative of the report to tell the audience what they are supposed to see in the picture; and - Direct them to the picture and tell them what to look for. Effective Charts - Avoid busy patterns; - Use the message in the title; - Use white space; - Keep the chart simple; - Keep scales proportional; - Use title to convey message; - Put supporting data in an appendix; - Easy to read o Use upper and lower case (not all capital letters) o Only a few type faces Types of Charts 1. Line Chart – Shows trends over time; 2. Single Bar Chart – Compare linear or one-dimensional characteristics; 3. Multiple Bar Chart – Compare two or more characteristics with the values of a common variable; 4. Pie Cart – Show parts of a whole; 5. Scatter Diagram – Show trend or relationships 40 Format Style for Graphs - No overlapping categories - Patterns or textures that are clear even when photocopied; - Patterns clearly labeled using a legend; - Have no extra line and patterns – only what is necessary; - Avoid black – it is difficult to reproduce accurately; - Lettering that does not go below 10 pt. font. Line Graph - A way to summarize how two pieces of information are related and how they vary; - Show data changes over time - Show continuous interval or ration data Scatter Diagram - Similar to a line graph except coordinated have no lines between them; - Used if you want to see if there is a relationship. Tables - Used to present information in an organized manner; - Types: o Data table Used to present numerical information; In the report, describe what to look for in the data table; Include the year and source Principles: Round-off number to no more than two significant digits – recommend using whole numbers; Give averages of rows and columns (as appropriate) to help audience make comparisons; Put the most important comparisons into columns; Too many line may make it difficult to read. o Classification Table (Matrix) A layout that shows how a list of things has been organized according to different factors; Can help illustrate complex information 41 Visual Information Design from Edward Tufte - Draw attention to the substance of the data, not something else; - Less detail in the grid, lines, detailed label; - Most amount of ink should be devoted to actual data; and - Avoid “chartjunk” – unnecessary decoration. Some Common Mistakes in Interpreting Data - Using percentage when the numbers are small; - Attributing causality when not demonstrated; - Over-generalizing the results; - Drawing sweeping conclusions based on small amounts of information. Formulating Findings - Describe results in clear language and easy to understand charts and graphs; - Make judgement backed up by the evidence; - Identify major reasons for successes, failures and constraints. Some Common Mistakes in Reporting - Reporting perception as fact; - Failing to anchor statements on the data; - Mis-reporting the statistics; - Failing to provide the context - Over indulgence in preliminaries M&E Reports: Basic Format 1. Introduction – purpose and background 2. Methodology – brief in body of report; details can go in appendix 3. Findings – present data so audience can understand present data selectively 4. Conclusion – should answer objective/questions 5. Recommendations – make sure evidence was presented in the body to support recommendations Writing Reports: Final Notes - Think about your reader; use clear simple English; - Don’t lose focus on the objective of the report; - Place major points front; - Always support your recommendations with evidence; - Annex technical or detailed information; and - Provide executive summary if report is more than 10 pages 42 Group Workshop # 6: General Analysis Report 43 Chapter 3: Identifying Capacity Solutions - Understanding the capacity needs of the LGU and formulating recommendations through the use of various analytical tools and processes; - Using data and evidence for understanding the capacity needs of the LGU and formulating recommendations. The Data Life Cycle Analytical Thinking and Data-Driven Decision Making Analytical Skills - Qualities and characteristics associated with solving problems using facts. - 5 Key Skills: o Curiosity Wanting to learn something; Share an experience where you learned a new knowledge out of trying something new; The desire to know and why your future depends on it; and Know what you learn about it. o Understanding Context Context is the condition in which something exists or happens; & Understanding the full picture. o Having a Technical Mindset The ability to break things down into smaller steps or pieces and work with them in an orderly and logical way. o Data Design How you organize information 44 o Data Strategy The management of the people, processes, and tools used in data analysis. 1. People: Making sure they know how to use the right data to find solutions; 2. Process: Making sure the path to solution is clear and accessible; 3. Tools: Making sure the right technology is being used. Analytical Thinking Involves identifying and defining a problem and then solving it by using data in an organized, step-by-step manner; 5 Key aspects: Visualization The graphical representation of information Strategy / Strategic See what you want to achieve with the data and how you can get there. Problem-orientation An approach in order to identify, describe, and solve problems 6 Problem Types: 1. Making predictions o Predictive analytics, using data to make informed decisions about how things may be in the future; 2. Categorizing things o Grouping data based on common features; 3. Spotting something unusual o Identifying data is different from the norm 4. Identifying Themes o Recognizing broader concepts and trends from categorized data; 5. Discovering Connections o Identifying similar challenges across different entities – and using data and insights to find common solutions; and 6. Finding Patterns o Using historical data about what happened in the past to understand how likely it is to happen again. Correlation Being able to identify a relationship between two or more pieces of data; Correlation does not result to causation Big-picture and detail-oriented thinking 45 Being able to see the big picture as well as the details and about figuring out all of the aspects that will help you execute a plan. Big picture thinking: Zoom out and see the possibilities Detailed-Oriented Thinking: Details matter, the more someone or someone or something matters to us, the more the details relating to them matter to us. Data-driven Decision Making Involves using facts to guide strategy. 3 Steps: 1. Figure out the business need (a problem that needs to be solved); 2. Find Data; 3. Analyze and use it to solve the problem. Solution-Finding Framework and Tools Solutions – byproduct of decision-making 1. Problem-Solution Finding Matrix (PSFM) 46 Sample PSFM Expanded PSFM 2. Objective and Strategy Analysis Objective Tree Look at objectives rather than problems; The analysis of problems in the Problem Tree is the basis and starting point for the Objective Tree analysis; 47 Show a means – ends hierarchy as opposed to cause-effect hierarchy of the problem; and This provides a summary picture of the designed furute situation, including the indicative means by which encs can be achieve; As with the problem tree, the objective tree should provide a simplified but robust summary of reality; It is a tool to aid analysis and presentation of idea/objectives; and Its main strength is that it keeps the analysis of potential project objectives firmly based on addressing a range of clearly identified priority problems. Steps: 1. Reformulate the problem statement - in the problem tree into a positive, desirable, and realistically achievable condition or objective. Do not simply rewrite a negative expression into a positive one; 2. Check the derived mean-ends relationship – to ensure validity and completeness (no missing links) of the hierarchy. You may ask the question “Will one layer of objectives achieve the next?” 3. Revise the logic. If necessary: o Revise the statement, or replace; o Add objectives if needed to achieve theo bjective at the next higher level; o Delete an objective that is nor suitable or irrelevant; or o Leave unchanged (if a statement makes no sense after rewording. 4. Complete the Objective Tree- by connecting the boxes with means-ends arrow. 48 5. Select strategies from the objectives o At times, two or more objectives may be combined, or part of it may become an independent strategy. o It is also possible to combine two or more strategies into a larger strategy. o When you consider combining strategies, it is important to keep in mind what the combination is intended to achieve. 3. Futures Thinking: Scenarios Local Governance Resource Center – a dynamic and interactive convergence platform that contributes to building the DILG as a knowledge- centric organization and builds learning communities that pursue local governance excellence through knowledge sharing and innovation. SWOT Analysis of LGRC – (Behavioral, Funding, Interventions, and Defining Relationship) Considerations: 49 o VUCA World: Volatile, Uncertain, Complex and Ambiguous o Global Pandemic o Digitalization o Space Travel Value and Mindset - Critical exploration of future possibilities. Future – is a verb and a process of actively shaping change. By reimagining the future as an asset, we can drive the change we want to see. We can’t change the past, but everything we do now changes the future. Present/current – reactive solutions; Future/emerging – proactive solutions. Future Thinking – (the theory and methods) and foresight (the practical application) are a set of approaches and tools designed to help their users identify emerging issues, negotiate uncertainties, articulate scenarios, develop a common vision of a desired future through wide participation, introduce innovation, and design robust policies and strategies. Tools: Scenarios – developing alternative futures 1. No change scenario 2. Adaptive change scenario 3. Marginal change scenario 4. Radical change scenario 50 4. Local Governance Model Capacity Development Analysis – aims to develop a tool for the DILG to analyze the LGU’s Capacity Development (CapDev) Agenda, make sense of the data collected from the Capdev Agenda, inform the DILG and LGA of the emerging CapDev needs of the LGUs, and direct the prioritization of responsive CapDev interventions for LGUs. 51 52 Scope : 53 Context Mimaropa Specific PPAs to address needs of CapDev 5. Capacity Framework DILG adopts CapDev Framework in 2021 (MC 2021-067); Common understanding of the conceptual underpinnings of capacity, performance and their implications to the local development; Provides a holistic and multi-faceted view of capacity and capacity development; and Helps ensure strategic capacity development. 54 Capacity and Performance: Capacity – ability of LGUs to perform functions to fulfill their accountabilities and produce desired results. Capacity Pillars: Factors that enable the LGU to perform its function, fulfill their accountabilities and produce the desired result; and Elements that need to be present and functioning in the LGU organization context. Development of the Pillar 55 Capacity Change Matrix Provides a concise documentation of the current and desired state of each capacity pillar for a governance/performance/outcome area. Almost same as the Vision-Reality Gap tool; Enables the LGU to look at the coherence, alignment and appropriateness of strategies and interventions to improve capacity. 56 Sub-Group workshop # 6: Identification of Capacity Needs Capacity Development Intervention - Current State – CapDev – Desired State Desired State of Capacity - The changes on the current capacity situation that would enable the LGU to operate in a way that will ensure the attainment of its desired performance. 1. What would the future state look like if the current issue/s are addressed? 2. What is the improvement? 3. What would be there that was lacking/missing before? 4. What would be working better compared to the current situation? Capacity Development - Process by which individual competencies and institutional capacities are enhanced through strategic and integrated interventions to equip and empower LGUs to fulfill their accountabilities and produce desired results. Capacity Development Interventions - Consist of strategies or actions that need to be done to strengthen the capacity pillars. 57 Types of CapDev Interventions (General) 1. Human Process Interventions 2. Techno-structural interventions 3. Human Resources Management 4. Strategic Interventions Types of CapDev Interventions (Specific) Tips on CapDev Interventions 1. Think of alternatives to Training 2. Identify complementary CapDev Interventions 58 Four Fields of Conversation (O. Scharmer) How to elevate? - Humble Inquiry is the fine art of drawing someone ou, of asking questions to which you do not already know the answer, of building a relationship based on curiosity and interest in other person. 59 - Powerful Questions? 1. Generates curiosity in the listener 2. Stimulates reflective conversation 3. Though-provoking 4. Surfaces underlying assumptions 5. Invites creativity and new possibilities 6. Generates energy and forward movement 7. Evokes more questions Chapter 4: Measuring for Results and Transforming Information to Insights - Discuss the importance of results-based monitoring and evaluation (M&E) and summarize and communicate the findings of the LGU analysis; - Measuring the effectiveness of interventions, ensuring accountability and facilitating learning and continuous improvement. Coach: Leah Marie Sanchez, Melany Quinton, and Adrian “Eydi” Lopez 60 Results-Based Monitoring and Evaluation Legal Basis: - AO 25, s 2011 RBPMS - JMC 2015-01, s 2015 Adoption of NEPFP (DBM-NEDA) - NBC No. 565, s. 2016 – RBMER Policy Framework Measure to Manage - Toolkit for RBME of CapDev Programs Purpose - To know the extent to which projects are meeting the intended objectives and desired effects; - To build greater transparency and accountability in terms of the use of project resources; - To provide management with a clear basis for decision making; and - To improve future planning and design of projects using lessons learned from project experiences. Key Components / Elements of RBME - Clear results chain agreed with stakeholders - Structured set of performance indicators - Plan for data collection, integration and analysis - Mechanism for reporting/communicating results - Sound evaluation framework and methodology - Sustainable institutional set-up for M&E Results - are Outputs, Outcome and Impact of a development intervention. 1. Outputs – products, services, goods produced by utilizing the Inputs 2. Outcome – immediate direct effects using output, what the project expects to achieve at beneficiary level; and 3. Impact – Long-tem effects resulting from continued presence of Outcome, the change expected over the long term. Intervention 1. Inputs – money, people, materials, facilities and equipment; 2. Activities – actions, processes, events, what is done with inputs 61 Result Chain - Is the causal relationship between intervention (inputs, activities), and Results( Outputs, Outcome, Impact); - It describes the logical relationships or the chain of events that links inputs to activities, activities to outputs, outputs to outcomes and outcomes to impact. Result – End of Mind : Intervention: Things we can do 62 Results-Based Monitoring - Continuous process of collecting and analyzing information on key indicators, and comparing actual results to expected results. Answers the question - are we achieving out targets? Results-Based Evaluation - Periodic assessment of the design, implementation and results of an ongoing, or completed intervention to determine its relevance, efficiency, effectiveness, impact, and/or sustainability. Answers the question - are we on tract / achieving our objectives? Monitoring vs. Evaluation 63 Result Framework - Is the program logic that explains how the development objectives is to be achieved, including causal relationships and underlying assumptions; and - Other terms used for results framework include: Results Matrix (UN), Logical Framework (EU), Design and Monitoring Framework (ADB). Monitoring and Evaluation (M&E) Plan - Is a table that builds upon a program / Project’s results framework to detail key M&E requirements for each indicator and assumption; - It summarizes key indicator (measurement) information in a single table; and - It is a detailed definition of the data, its sources, the methods and timing of its collection, and the people responsible. 64 Performance Change Matrix and RBME 65 Communicating Insights: Basics of Data Visualization Prerequisite prior to Data Visualization - Ensure datasets are free from error (typo may lead to outliers) - For ease of analyzing and visualizing data, it is highly recommended to transform textual / qualitative data into numerical forms. (from yes/no to 0/1). This way we can conduct statistical analysis through Excel. 66 Data visualization - Is the graphical representation of information and data by using visual elements like charts, graphs, and maps; - Is a tool that provides an accessible way to see and understand trends, outliers,, and patterns in data. Uses of Data Visualization - Processes big data - Provide trends and patterns - Unveils areas for Improvement - Helps in faster and Better Decision Making Rules to Better Communicate Data - Know your Audience - Identify your Key Message - Keep your Data Simple and Concise - Always include Captions - Fine Tune your Data Visualization Tool - Use Color Effectively - Avoid Misleading Data - Do not use Unnecessary Visual Elements - Explore Other Sources - Get the Right Tool 67 Visualization Tools 1. Single Value (one numerical value) 2. Single Value with indicator (voluminous numerical and textual data) 3. Table 68 4. Line Chart 5. Bar Chart – Specific Data 6. Pie Chart – Specific and fixed data values but only involved smaller number of categories 69 7. Scatter Plot - Correlation between income class and locally-sourced revenues. 8. Area Chart 9. Combined Chart 70 Reporting Voluminous Qualitative Data - Group related statements and look for recurring themes Presenting Geospatial Data 1. Use points of varying sizes to represent multiple data in various locations at once 71 2. Use maps to show distribution and location 3. Using Maps to show direction 72 DILG Best Practices 1. E-SLDR (State of Local Development Report of LGUs from LGPMS 2. Traffic Light System a. SLGL Governance Assessment Report i. Provides information on the LGU’s performance on specific criteria under each Governance areas 73 b. DOH LGU Health Scoreboard c. Online Dashboards i. Full Disclosure Policy Portal ii. Subaybayan 74 iii. Document Management System iv. Community-Based Monitoring System - QGIS 75 Opportunities 1. Increase productivity in the workplace 2. Provision of Contextualized technical assistance to clienteles 3. Strengthen Multi-Stakeholder Collaboration 4. Influence Government Legislation and Policy Reforms Challenges 1. In-depth Analysis 2. Inter-possibility of multiple Platforms 3. Data Results and Intervention Linkage “Measure the most you can and Show the least you can” – D. Roefs Communicating Insights: Developing a Policy Brief Importance of Communicating Insights 1. To gain support and approval (LCEs have the authority to approve policies, programs and projects); 2. To ensure alignment with the local government’s priorities (The LCE sets the agenda for the LGU and determines its priorities); 3. To secure resources (The LCE is responsible for allocating resources to different programs and projects); and 4. To ensure effective coordination (LCE can help to ensure that different departments and stakeholders are aware of the proposed interventions and are working towards the same goal. Mechanisms in Communicating Insights 1. Written Communication 2. Presentations 3. Meetings 76 Developing Policy Briefs Policies - Are guides to actions to carry out the objectives or achieve the targets. Policies can take the form of: o Regulatory measures (legislation) o PPAs o Services - May be in the form of programs and projects, legislations or services extended to the public as regular functions of local government offices/departments (Guide to CDP Preparation) Policy Options - Include programs, projects legislative measures and CapDev interventions (EPSFM) - Such options may be: o Directed to the cause of the observed condition o Directed to positive effects of the observed condition o Directed to negative effects of the observed conditon Policy Options/Policy Interventions - Refer to the broad classification o interventions to nclude regulatory measures and legislations, programs, projects, and activities (CDP+). Policy Brief - Is a document that outlines the rationale for choosing a particular policy alternative or course of action in a current policy decision-making; - A medium for exploring an issue and distilling lessons learned from the research; - Powerful tool that condenses complex information into a concise and compelling document; - A vehicle for providing advice: o Convince the target audience of the urgency of the current program; o Persuade the target audience to adopt the preferred course of action. - Policy Brief = Agenda Setting and Policy Formulation 77 Purpose of Policy Brief 1. Identify a problem or issue 2. Summarize the available evidence and research 3. Analyze the options for addressing the problem or issue 4. Recommend a course of action 5. Provide information to support the recommendations Characteristics of Policy Brief: 1. Focus. Need to strategically focus on achieving the intended goal of convincing target audience. 2. Policy-minded rather than academic. The common audience of policy brief are interested in what you found and what you recommend. They do not need to know the details of the methodology. Focus of meanings, not methods. 3. Strong Evidence. Policy brief should be based on firm evidence and a rational argument. The information (drawing on the evidence) should identify that a problem exists and the consequences of adopting particular alternatives. 4. Limited Scope. The policy brief should focus on a particular problem or issue. Do not go into all the details Instead, provide enough information for the reader o understand the issue and come to a decision. 5. Succinct. Be short and to the point. Remember your target audience. 6. Understandable. The policy is easy to read and appears interesting. There is a well-explained and easy to follow he argument. 7. Accessible. Ensure the information in the policy brief is easy to navigate. Text should be subdivided using clear descriptive titles. 78 8. Promotional. The policy should look attractive and grab the reader’s attention. Consider the use of color, graphics, and photographs. 9. Practical and Feasible. The policy brief needs to be realistic. The target audience will be more interested in recommendations they can implement – that are politically, economically, socially and technically feasible. Structure of Policy Brief - Policy brief can take different formats. - No more than 3-5 pages long and are structured in a clear and concise format. - They should focus on the most important issues and recommendations. - Structure: o Executive Summary Aims to convince the reader that the brief is worth in-depth investigation and warrants further reading Distil the essence of the brief Ask yourself, “What are the main points you want to get across?” The executive summary should always appear in the cover of the brief or at the top of the first page so that it is the first thing a reader will see. It can be helpful to write the executive summary last because you will gain clarity on its content as you draft other sections. o Context and Importance of the Problem Explain the significance/urgency of the issue Content: The Problem (what is the problem, its importance and relevance of the policy to the issue) Context (What happens, where, who is involved?) Causes of the current situation (Why? Give the evidence or example) Effects of current situation (What effect does it have? Give evidence or examples) The reader needs to be convinced early on the problem warrants action. Tips: This should set up the rest of the document and clearly convey your premises. The goal is to leave your readers with a clar sense of what your paper is about while enticing them to continue reading. Avoid jargon and overly technical language. Focus on highlighting the benefits and opportunities stemming from the research. Possible Problem Statement Outlines 79 o Critique of Policy Option(s) Here is when you focus on detailing the shortcomings of the current approach or options being impended. Explain the advantages and disadvantages of each of policy option. Tips: This should lay down the possible interventions to address the identified problem; The goal is to give your readers options to pursue aligning to his/her executive/legislative agenda; Avoid jargon and overly technical language Consider using tools and techniques to evaluate policy option. (e.g. Cost-Benefit Analysis, Impact Assessment, FGDs, Comparative Analysis, PRINCE Analysis) o Policy Recommendation Describe clearly wat should happen next. Provide a detailed and convincing proposal of how the failings of the current policy approach need to be addressed. Suggest revisions in policy, what are the various options? Effects of the revised policy. How will the policy changes affects the situation Tips: Remember that we have scare resources, Our LGU budget is also limited. We need to prioritize interventions; State the recommendations clearly in a way that is easy to understand; Make them easy to understand Think of the conclusion as a mirror to your introduction: you are once again providing an overview of your argument, but this time you are underlining its strength rather than introducing it. 80 o Appendices Although the brief is a short and targeted document, authors sometimes decide that their argument needs further support and so include an appendix. Appendices should be included only when absolutely necessary. Designing Policy Brief - The design and presentation of your brief are important considerations and can help keep the reader engaged. o Titles and Subheadings Titles act as reference point to entice readers; Include sub-titles or headings to break up the text and draw the reader’s attention to the main topic of each section; Use verbs to make headings more dynamic; Phrase headings as questions to spark a reader’s curiosity; Headings should contain relevant information without being too long; Characteristics: Short To the Point Catchy 81 o Sidebars Add greater depth to the main discussion and hook a reader’s attention; Visually break up the brief and make documents easier to read; Should be: Short Descriptive Engaging Action-Oriented o Lists Lists are an effective and visually interesting way to simplify dense content. They should be no longer than 5-7 bullet points; Each bullet point should express complete thoughts; Avoid using bullet points that are only one or two words in length. o Graphics Visuals are easily one of the best ways to make policy briefs more interesting for readers Every visuals should serve a purpose and help to illustrate arguments. Choose effective visuals for the information you would like to communicate; Include captions for photos and other visuals to explain the content to the reader. 82 Group Workshop #7: Development of Policy Brief 83 References: 1. E.O. 138 – Full Devolution 2. MC 2021-101_ Guidelines in developing capacities of LGUs in the context of Full Devolution 3. RA 11292 SGLG Law 4. RA-10173-Data Privacy Act 5. RA 11315 – CBMS 6. CapDev Toolkit 7. Toolkit for RBME of CapDev Programs 84