Know how a data management project can help: Improve program design Demonstrate effectiveness Highlight the best work being done Compete for funding, and Mobilize public support.
Learn about: Identifying expected outcomes, and defining objectives and incremental indicators of success consistent with your mission.
Understand the elements and stages of a data management planning process Be familiar with common barriers and costs associated with data management
Learn how quality data can influence and inform the strategic planning process. Explore options for tracking and using data efficiently at reasonable cost.
City of Pittsfield Neighborhood evaluation ◦ Combining & analyzing data from multiple sources DIAL/SELF (Greenfield, MA) Transitional Living Program housing outcomes ◦ Sorting and interpreting data from a single collection source (Lets go to visit source tables in Excel then come back to PowerPoint to review graphs)
Bring key people together at each stage of planning process Administration, program directors and supervisor participation is critical in early stages, but direct care staff can be helpful too (ask questions!)
Initial planning stages require a deep understanding of the resources (funding, technology/equipment, and staff time) required to plan, implement and maintain a data management project/data driven culture.
It may be worthwhile to invest in a consultant or devote substantial administrative time to produce useful estimates of the time and cost involved in implementing and maintaining a data driven culture
Understand the purpose of your project - what will this data do for your organization? Identify data priorities Plan to start small and efficiently – you can grow as you learn and achieve - look for the intersection of what data you can easily obtain and what you would want to know in an ideal world! (go to flip chart )
As you move into more detailed planning, direct care staff input becomes extremely important. Involve staff in a formal way and carefully assess what support they will need to succeed! Design formal systems for Training, Support and Accountability
Reports/data you already need for funders Identify information for internal evaluation and improvement (even if it isn’t currently required by funders) Develop a functional draft of outcomes, objectives and indicators (your dataset) prior to shopping for a database or building a data collection system
OObjectives = desired participant changes or achievements IIndicators = measurable events OOutcomes = level of achievement
Inputs resources Outputs actions Outcomes achievements Basic Logic Model Inputs resources Outputs actions Indicators events Objectives expectations Outcomes achievements ImProve Outcomes SM Model *Identify tracking method
Extension of logic models Based on incremental change Means of prioritizing information Method of categorizing information
Levels of Learning Mastery ◦ Knowledge/Comprehension (learn about it) ◦ Application (use it, try it out) ◦ Synthesis (integrate with other knowledge)
S pecific M easurable A chievable R elevant T imely
Use active verbs to describe indicators Look for achievement opportunities at levels that are relevant to the services, time frame or intervention level of your program Indicators reflect participant capacity for positive change and choices that indicate forward movement
Web/Cloud Based ◦ Require reliable, high speed internet connection(s) ◦ Each user has own license – can access from anywhere ◦ Easy to monitor data entry ◦ Evaluate capability and cost of compilation, sorting and reporting ◦ Carefully evaluate ownership of data and “worst-case scenarios” (e.g., you or the provider go out of business?) PC-Based ◦ You own software and data that is on your computer ◦ Speed depends on speed of machine ◦ May require additional software to run the database ◦ Can be difficult to synchronize data from multiple sources. ◦ Ease of data retrieval depends a lot on initial design and software used.
1. Surveys: Useful to capture information from participants You have to ask the right question(s). That takes planning and some experimentation to gather aggregateable data. Results can be compiled in Excel – but consider using Survey Monkey where you can get reports and export to excel. 2. Microsoft Access: Good for demographic data and tracking objectives and indicator completion – data that changes or needs to be cross-referenced. Inexpensive, but requires expertise to develop functional applications Easy to retrieve data through queries
3. Daily Logs (paper or software ) ◦ Most useful if data is aggregated and entered into a database or spreadsheet regularly (daily, weekly or monthly) ◦ Like surveys, the right questions have to be asked to get useful, accessible information ◦ With proper planning, could be used to track a variety of participant achievements. 4. Exit interviews! ◦ Build some of the questions to have aggregateable answers (e.g., multiple choice, name at least one xxx, etc.)