Data Collection

SWOT Data Analysis

Before building your data quality plan, a great tool to prep is a SWOT Data Analysis. It is used in the business world to assist and assess agencies to aid in decision making. SWOT analysis is a framework that identifies the strengths, weaknesses, opportunities, and threats within your external and internal view of data management. This tool is all about thinking through possible factors that can affect your data negatively and positively. Here we will break down each area.

Strengths:

Strengths are the areas that your agency or CoC and data are doing well. It asks the question, “What is unique about your programming to end homelessness?” and ”What are the strengths of how you currently collect and maintain data?” This is your chance to list all the accomplishments and what’s working right within your agency. One of the main questions being asked is, “What are some things your agency or CoC do well surrounding your data?”

Example: Continuum The biggest strength is their efficient coordinated entry process. Continuum A has all the stakeholders in constant communication who helped build a process that works for all clients through an equitable system. They regularly review their coordinated entry process for improvement.

Weaknesses

Weaknesses are the areas that your agency or CoC currently struggle with. This is one of the most difficult sections for many organizations, more time and honesty should be spent on breaking down the faults of your programming and data. Weaknesses ask the question, “What areas are lacking in your programming and data?” Think about the things you could improve on in your system. Two main questions to ask yourself include: “What are some things your agency or CoC lack in your data?” and “what resources are you currently lacking?”

Example: Continuum B’s case managers are feeling overworked and feel unable to complete the intake process promptly is the biggest weakness. Case managers feel no one is taking their concerns about the intake process into consideration. This weakness can threaten the timeliness and accuracy of data.

Opportunities:

Opportunities are where you get to dream big. It asks the question, “What developments can you see happening for the future of your programming and data?” as well as “What opportunities can you take advantage of?” Spotting the opportunities allows you to think out the goals and create the right action plans that will aid in developing your data quality plan and incorporating these opportunities you discovered. 

Example: Continuum A’s great coordinated process and having the right stakeholders at the table is an opportunity to build city-wide reports to find all gaps within the systems that would ruin building an equitable city.

Threats:

Threats consist of anything that is negatively affecting your programming and data. This is where you get a chance to think out the obstacles that can potentially occur in this journey. The main question that threat asks includes, “What threats can prevent you from doing well?”

Example: Continuum B is having a new full administration change at the city level, in which no one has experience with the intake process, HMIS, and more. This could result in a halt in the intake process due to training needs. 

The SWOT Analysis is a tool to get everyone thinking and to begin understanding the big picture when it comes to your data. SWOT Analysis is similar to a vision board and helps plan and begin to develop your data quality analysis with more focus. Below is a sample of a simple SWOT Analysis.

In this example, Organization A has built an effective intake process that includes impactful assessment questions that meet all the data needs. However, Organization A is currently having issues with the reliability of their data due to timeliness concerns, stemmed from staff buy-in. This organization sees software issues and federal guideline changes as a threat due to processing issues on their current software in which information is slow to submit and data changes take a while to be updated on the system. Organization A sees opportunities in the future for more community infographics and analysis tools to aid in building more interconnectedness within their community.  

Once you have done your planning it is now time to begin developing or editing your data quality plan. The data quality plan is where you define your data goals and activities necessary to sustain your data integrity. In this section, we will discuss some of the areas to consider including in a data quality plan.  Keep in mind,  all data quality plans should be adapted for the scope of your organization. In this section, we will discuss 5 areas of the data quality plan to get you started.

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