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<title>Data for Decision-Making | Applying Data for Decision-Making to Your Organization, Part 1</title>
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<ul class="agenda-navigation">
<li><a href="#overview">Overview</a></li>
<li><a href="#step-1">Welcome and Administrative Tasks</a></li>
<li><a href="#step-2">Reviewing Key Concepts</a></li>
<li><a href="#step-3">Student Activity 5.1: Developing a Data Story</a></li>
<li><a href="#step-4">Reviewing Key Concepts</a></li>
<li><a href="#step-5">Student Activity 5.2: Final Project</a></li>
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<div class="activity-menu">
<a class="toggle"><strong>Data for Decison-Making</strong> - Module 5 of 6</a>
<div class= "header-links"><a href="../D4D/index.html" target="_blank">HOME</a>
<a href="../D4D/about/" target="_blank">ABOUT</a>
<a href="../D4D/curriculum/" target="_blank">CURRICULUM</a>
<a href="../D4D/downloads/" target="_blank">DOWNLOADS</a></div>
<ol class="activity-list">
<li><a href="module-one.html">Introduction to Data for Decision Making</a></li>
<li><a href="module-two.html">Assessing your Organization’s Data Culture</a></li>
<li><a href="module-three.html">Introduction to the Data Lifecycle - Collecting Data</a></li>
<li><a href="module-four.html">Introduction to the Data Lifecycle - Analyzing and Sharing Data</a></li>
<li class="current"><a href="module-five.html">Applying Data for Decision-Making
to Your Organization, Part 1</a></li>
<li><a href="module-six.html">Applying Data for Decision-Making
to Your Organization, Part 2</a></li>
<br>
<li><a href="downloads/">Visit our downloads page for more options</a></li>
</ol>
</div>
<h1 class="activity-title">Applying Data for Decision-Making to Your Organization, Part 1</a></h1>
<section class="overview">
<p class="made-by">
<a href="https://creativecommons.org/licenses/by-sa/3.0/">CC-BY-SA</a> by <a href="https://tascha.uw.edu">TASCHA</a>
</p>
<p class="time total-time">
3 hours
</p>
<br><p class="download-box">
<a href="../D4D/documents/Module1_Contents.zip">Download this module</a> or visit our <a href="../D4DM/downloads/" target="_blank">downloads page</a> for more options
</p>
<!--<p class="summary">-->
<p><h4>Student Objectives</h4>
<ul>
<li>Review key concepts of data for decision-making and the data life cycle</li>
<li>Apply visualization techniques in order to “story tell” with data</li>
<li>Understand the importance of data for decision-making by applying the process to problems in their organization</li>
<li>Think critically about ways to use data to solve these problems</li>
<li>Practice data sharing by presenting these findings to other workshop participants</li>
</ul>
</p>
<h4>Materials</h4>
<ul>
<li>Projector</li>
<li>Computer</li>
<li>Blackboard/whiteboard (ideally)</li>
<li>Paper</li>
<li>Pencils</li>
<li><a href="../D4D/documents/Module5_Images.doc">Printout of images</a></li>
<li><a href="http://tascha.github.io/D4D/documents/Activity_5.1.doc">Activity packet 5.1</a></li>
<li><a href="../D4D/documents/Acivity_5.2.doc">Activity packet 5.2 (Final Project)</a></li>
<li><a href="../D4D/documents/StudentHandbook_Module5.doc">Student handbook</a></li>
<li><a href="../D4D/documents/Module5_DataforDecisions.ppt">Instructor Powerpoint slides</a></li>
</ul>
</section>
<ul class="agenda">
<li>
<h1>Welcome and Administrative Tasks</h1>
<div class="time step-time">10 minutes</div>
<p>Welcome the participants back. Spend a few moments going over any administrative tasks if necessary. Then, outline the structure of today. In the first half of the day, participants will be reviewing the concepts they have learned over the past two days, and will apply these concepts to a data project in order to solve a problem at their own organization using the new skills that they learned. Then, after lunch, the participants will use the remaining time to finish their projects and then present them..</p>
<p>Pause to answer any questions.</p>
</li> <!--End of step-->
<!-- Copy and paste this <li> tag to add additional steps -->
<li>
<h1>Review Key Concepts</h1>
<div class="time step-time">15 minutes</div>
<p>Next, take a few moments to review the following key concepts from yesterday. Project this image on the screen:</p>
<p><img src="http://tascha.github.io/D4D/images/data-lifecycle.jpg" alt="Data Lifecycle Chart: Collect, Analyze, Share" width="100%"></p>
<p>Ask the class about the data lifecycle. How would they describe:</p>
<ul>
<li>Collecting data</li>
<li>Analyzing data</li>
<li>Sharing data</li>
</ul>
<p>As they describe the concepts, have them discuss different aspects of each step in the cycle. For instance, with regards to collecting data, what necessary steps are there?</p>
<p>For the collection phase, review:</p>
<ul>
<li>Primary data</li>
<li>Secondary data</li>
<li>Data collection protocols</li>
<li>Metadata (descriptive, administrative, and rights)</li>
</ul>
<p>For the analysis phase, review:</p>
<ul>
<li>Choosing method of analysis</li>
<li>Preparing data for analysis</li>
<li>Data cleaning</li>
<li>Data coding</li>
<li>Descriptive statistics</li>
<li>Visualization</li>
</ul>
<p>For the sharing phase, review:</p>
<ul>
<li>Why is data sharing important?</li>
<li>Possible digital formats for sharing (.xls, .csv, .doc, .PDF, .JPEG, etc)</li>
<li>Data documentation</li>
<li>Publishing data</li>
<li>How can participants share data and which methods are best for certain types of data (i.e. excel is good for disaggregated data; pdf is not).</li>
</ul>
<p>Pause to ask if anyone has questions so far.</p>
</li> <!-- end of step-->
<li>
<h1>Activity 5.1: Developing a Data Story</h1>
<div class="time step-time">35 minutes</div>
<p class="download-box"><a href="http://tascha.github.io/D4D/documents/Activity_5.1.doc">Download Activity 5.1</a></p>
<p><i>Adapted from <a href="Datatherapy.org">Datatherapy.org</a></i></p>
<p><b>Objectives:</b></p>
<ul>
<li>Apply key concepts of data visualization</li>
<li>Learn to think critically about best practices in communicating data visually</li>
<li>Connect data visualization to storytelling</li>
<li>Create a “Data Storybook”</li>
<li>Provide and receive constructive feedback regarding other data visualizations from workshop participants</li>
</ul>
<p><b>Materials Needed:</b></p>
<ul>
<li>Paper</li>
<li>Pencils</li>
<li>Color pencils, crayons, or markers (whatever is easily available)</li>
<li>Art decorating supplies that are easily available within your own country</li>
<li>Finding a Story worksheets</li>
<li>About 6 different datasets for every group of 30 participants (i.e., two groups of 3 participants can have the same dataset if necessary)</li>
</ul>
<p><b>Introduction:</b> (Use the following information to introduce and explain the activity to the class)</p>
<p><i>From <a href="Datatherapy.org">Datatherapy.org</a>, Accessed May 2017</i></p>
<p>A key component of data visualization is knowing how to tell a story. In data visualization, there are often just a limited number of “key” pieces of information that you want to convey to your target audience. This could be trends that you as an analyst noticed, or outliers that should be given special attention. Using a visualization turns this information into something that is quickly and easily digested by people who may not understand the relationships that you found in the data just by looking at a summary table.</p>
<p>Any dataset has the potential for multiple stories to be told. Picking the most appropriate story based on your audience and goals is hard. In this activity, participants will be broken into a minimum of five groups, with at least two or three people per group. Each group will be provided a sample dataset that is relevant for their country and copies of one of the five following story-type worksheets. Each participant in the group should complete a worksheet.</p>
<p>Next, each group should share their completed worksheets internally and choose one to develop into an actual story narrative. This activity builds capacity to turn “dry” information into a compelling story. It also reinforces the link between data presentation storytelling.</p>
<p>Next, groups will present their work to the class. After each presentation, lead a Q&A discussion with the participants. Some guiding questions include: would this story resonate with our target audience? Is this story a complete picture of the data we have? What makes this story compelling? How could it be made more compelling? Is this the most important story to tell at this moment in time? Is there anything important missing from the story that needs to be provided for context? Can this story be misinterpreted in any ways?</p>
<p><b>Developing a Story - Factoid Stories</b></p>
<p><i>Adapted from <a href="Datatherapy.org">Datatherapy.org</a></i></p>
<p><b>Directions: There are many different things that you can communicate with your data. Using the dataset provided and the following guiding statements, develop each piece of a data story. When finished, share your story with your small group. Your group should then choose one story to develop into a more complete narrative to share with the class.</b></p>
<p>Often a dataset will contain one specific piece of information (a “factoid”) that you want to pull out and make understood by your audience. This information could be an outlier that has a significant difference from the rest of the data, or it could be something important that is common across the entire dataset. In addition to helping make an important detail understood, this can serve as an entry to help your audience understand more (and potentially more complex) parts of the data.</p>
<p>Complete the following:</p>
<p>One interesting factoid is</p>
<p>This stands out from the rest of the data because</p>
<p>It is important to tell this story because</p>
<p><b>Developing a Story - Interaction Stories</b></p>
<p><i>Adapted from <a href="Datatherapy.org">Datatherapy.org</a></i></p>
<p><b>Directions: There are many different things that you can communicate with your data. Using the dataset provided and the following guiding statements, develop each piece of a data story. When finished, share your story with your small group. Your group should then choose one story to develop into a more complete narrative to share with the class.</b></p>
<p>One important story that can be told is the interaction between parts of your data. Recall from previous discussions the term “correlation”, which describes a relationship between two or more variables. If one goes up, so does another. Or if one goes down, another other goes up. It does not, however, mean that one variable impacts the other or “causes” the other to change. Although the reasons for the interaction can take time to discover (likely more time than is available during this session), awareness of the correlation can nonetheless be important.</p>
<p>Complete the following:</p>
<p>The two (or more) pieces of the data that interact are</p>
<p>The nature of their interaction is</p>
<p>It is important to tell this story because</p>
<p><b>Developing a Story - Comparison Stories</b></p>
<p><i>Adapted from <a href="Datatherapy.org">Datatherapy.org</a></i></p>
<p><b>Directions: There are many different things that you can communicate with your data. Using the dataset provided and the following guiding statements, develop each piece of a data story. When finished, share your story with your small group. Your group should then choose one story to develop into a more complete narrative to share with the class.</b></p>
<p>Different pieces of your data can be important to compare to describe and draw out key similarities or differences. This comparison story is composed of smaller stories. Why is the story in one part of your data different than that of another? Or how does one small story show a larger story for the entire dataset?</p>
<p>Complete the following:</p>
<p>The data we want to compare are</p>
<p>Comparing these data shows that</p>
<p>It is important to tell this story because</p>
<p><b>Developing a Story - Change Stories</b></p>
<p><i>Adapted from <a href="Datatherapy.org">Datatherapy.org</a></i></p>
<p><b>Directions: There are many different things that you can communicate with your data. Using the dataset provided and the following guiding statements, develop each piece of a data story. When finished, share your story with your small group. Your group should then choose one story to develop into a more complete narrative to share with the class.</b></p>
<p>It is common for our minds to focus on how things change over time. Creating a story that shows change resonates with our natural curiosity and is important for understanding our data.</p>
<p>Complete the following:</p>
<p>The data show a change over time in</p>
<p>The data change from</p>
<p>to</p>
<p>It is important to tell this story because</p>
</li> <!-- end of step-->
<li>
<h1>Review Key Concepts</h1>
<div class="time step-time">20 minutes</div>
<p>Review the following key concepts with the participants. This could be done by playing a review game where the class is split into teams and has to answer questions about each concept, or could be done by a simple instructor-led review. For each concept, be sure to spend time with the participants and have them describe each term’s significance in data for decision-making.</p>
<p>Again, as before, try to have the participants provide their own definitions before</p>
<ul>
<li>Data</li>
<li>Data for decision-making</li>
<li>Stakeholders</li>
<li>Assessment</li>
<li>Mission</li>
<li>Vision</li>
<li>Data producer</li>
<li>Data consumer</li>
</ul>
<p>Ask, what are the key steps to using data for decision-making? Remind the participants:</p>
<ul>
<li>Identify a problem or research question</li>
<li>Assess data available to you and your data needs</li>
<li>Identify stakeholders</li>
<li>Plan for how data will be used, analyze, and shared</li>
</ul>
<p class="summary">Dismiss the class for a ten-minute break.</p>
</li> <!-- end of step-->
<li>
<h1>Activity 5.2: Final Project</h1>
<div class="time step-time">3 hours (spread out across Modules 5 and 6)</div>
<p class="download-box"><a href="http://tascha.github.io/D4D/documents/Activity_5.2.doc">Download Activity 5.2</a></p>
<p><b>Objectives:</b></p>
<ul>
<li>Review key concepts of data for decision making and the data life cycle</li>
<li>Apply visualization techniques in order to “story tell” with data</li>
<li>Understand the importance of data for decision making by applying the process to problem in their organization</li>
<li>Think critically about ways to use data to solve these problems</li>
<li>Practice data sharing by presenting these findings to other workshop participants</li>
</ul>
<p><b>Materials Needed:</b></p>
<ul>
<li>Paper</li>
<li>Pencils</li>
<li>Posters or large pieces of paper for presentation</li>
<li><a href="http://tascha.github.io/D4D/documents/Activity_5.2.doc">Activity 5.2 Participant Guide</a></li>
</ul>
<p><b>Instructions:</b></p>
<p>This activity represents the culmination of what the participants have learned over the past few days. In this activity, participants will be put into groups of 3-4. They will be asked to think of a problem that they would like to solve using data, apply this problem to the data lifecycle, and then present their results to their peers. Remind the participants of the steps they should follow:</p>
<ul>
<li>Identify a problem or research question</li>
<li>assess data availability and your data needs</li>
<li>Identify stakeholders</li>
<li>Plan for how data will be used, analyzed, and shared</li>
</ul>
<p>The attached worksheet provides a step by step process for the participants to go through each of these pieces as they complete their project.</p>
<p><b>Activity 5.2 Participant Guide: Final Project</b></p>
<p>Directions: This project will have you apply what you have learned in the past few days to a real-life scenario at your own organization. In this project, you will 1) identify a problem or research question, 2) assess data available to you and your data needs, 3) identify stakeholders, and 4) plan for how data will be used, analyzed, and shared.</p>
<p>You will present your projects, along with a sample visualization of your data, on a poster board to the class. Your poster board should also have the following information:</p>
<ul>
<li>the problem you are addressing</li>
<li>the stakeholders of this problem</li>
<li>your data collection plan</li>
<li>how you will analyze your data</li>
<li>how you will share your data</li>
</ul>
<p>This worksheet will provide you with helpful steps to complete along the way as you work through your project. To begin, review the process for developing a data collection plan.</p>
<ul>
<li>What questions or problems are trying to be addressed?</li>
<li>What do you need to know?</li>
<li>When will you collect new data (primary), and when will you use existing data (secondary)?</li>
<li>What instruments will you need to create?</li>
<li>Who will be involved in data collection, and for how long?</li>
<li>What documentation will be needed to use the data again?</li>
</ul>
<p><i>Phase One</i>: <b>Defining the Data Problem</b></p>
<p><b>Directions: Use this guide to help you think through a key issue you are trying to address, the factors that contribute to that issue, the people it affects, existing data surrounding the issue, potential sources of new data, and how to use those data to make a decision.</b></p>
<ol>
<li>What is the primary question, problem, or issue you want to address? Why it important to others/society? Why is it important for you to address it (e.g. are others looking into it?)?</li>
<li>What is causing and impacting the problem or issue? What issues surround the problem that keep it from being solved?</li>
<li>What people and/or communities does the problem impact?</li>
<li>Who else is currently or has tried to work on this?</li>
<li>What data do you need to make more informed decisions and programming to address the issue?</li>
<li>How would you use those data to address the issue?</li>
<li>What data exist already? What do they focus on and how up-to-date and reliable are they?</li>
<li>What additional data do you need to address the problem or issue?</li>
</ol>
<p><i>Phase Two</i>: <b>Identify Stakeholders</b></p>
<p><b>Directions: Recall that a stakeholder is a person with an interest or concern in something. Defining a problem in which to use data to make a decision is a crucial first step in data for decision-making. Another important piece of data for decision-making is understanding who your stakeholders are by performing a stakeholder analysis. Understanding all the actors and their relative influence over the problem will help you frame your plans within the existing government, civil society, academic, and other systems responsible for addressing a problem.</b></p>
<p>When you think about your stakeholders, you should consider:</p>
<ul>
<li>Communities: Individuals or groups who are affected by the problem.</li>
<li>Change agents: Individuals and groups directly working on the issue. These include community groups, NGOs, and others on-the-ground.</li>
<li>Support groups: Foundations, governments, NGOs, and others with resources to address the issue.</li>
<li>Policymakers: the people who can control government responses to the issue.</li>
</ul>
<p>Find the stakeholders in the problem you have just defined. Think through:</p>
<ol>
<li>Who are the stakeholders in the community who are affected by the problem or issue? These can be individuals and groups.</li>
<li>Who are the change agents? These are individuals and groups directly working on the issue, who include community groups, NGOs, and others on-the-ground.</li>
<li>Who are the support groups? These are foundations, governments, NGOs, and others with resources to address the issue.</li>
<li>Who are the policymakers? These are the people who can control government responses to the issue)?</li>
<br>
<p><b>Next, for <i>each</i> stakeholder answer:</b></p>
<li>In what ways do they engage with the problem?</li>
<li>In what ways do their goals align with yours? In what ways are your interests in the issue opposing?</li>
<li>How much influence and power do they have to make change?</li>
<li>How do/can they use data to make decisions about the issue?</li>
<li>Where are the gaps in data that impact their decision-making? What would more/better data allow them to do?</li>
</ol>
<p><i>Phase Three</i>: <b>Plan for how Data will be Used and Analyzed</b></p>
<p><b>Directions: Remember the data lifecycle:</b></p>
<p><img src="http://tascha.github.io/D4D/images/data-lifecycle.jpg" alt="Data Lifecycle Chart: Collect, Analyze, Share" width="100%"></p>
<p>For each phase of the cycle, think through the following:</p>
<p><i>Data collection</i></p>
<ol>
<li>Where can you get primary data? Of all the possible data you could collect, which are most realistic given your time and resources?</li>
<li>Where can you get secondary data?</li>
<li>What resources (new and/or existing) will you need to collect your primary and secondary data?</li>
<li>What will be your data collection protocols?</li>
<li>What will be in your metadata (descriptive and administrative)?</li>
</ol>
<p><i>Data analysis</i></p>
<ol>
<li>What will be your method(s) of analysis?</li>
<li>What resources (new and/or existing) will you need to collect your primary and secondary data?</li>
<li>How will you prepare your data for analysis?</li>
<li>How will you clean your data?</li>
<li>How will you code your data?</li>
<li>How will your normalize your data?</li>
<li>What descriptive statistics might be interesting?</li>
</ol>
<p><i>Data visualization</i></p>
<ol>
<li>Who are your primary audiences for visualization? Why?</li>
<li>What will be the mediums by which you create visualizations? (e.g. paper reports, digital reports, websites for mobile, websites for computer) Why?</li>
<li>What stories do you think you might want to tell with your data through visualization? Why?</li>
<li>What resources (new and/or existing) will you need to visualize your data?</li>
<br>
<p>For your project, create a sample visualization on your poster board. Be prepared to answer why you chose this visualization and what main points you hope to communicate about your data.</p>
<p>Remember some key components for data visualizations:</p>
<ul>
<li>Visualizations should be created to tell a story</li>
<li>Discuss any limitations and be aware of how your data may be misleading</li>
<li>Create legends that tells viewers what data are being used</li>
<li>Label all axes and create descriptive titles</li>
<li>Provide links to the original data, or contact information for the data producer</li>
</ul>
</ol>
<p><i>Data sharing</i></p>
<ol>
<li>Why is data sharing important for this project?</li>
<li>Who are your primary audiences for sharing? Why?</li>
<li>What formats will you share your data in?</li>
<li>How will you document your data?</li>
<li>How will you publish your data?</li>
<li>What resources (new and/or existing) will you need to share your data?</li>
</ol>
</li> <!-- end of step-->
</ul>
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