| How might data be collected for this target response? | To address the problem, you’ll want to measure both whether data collection is happening and what factors might be competing with it. |
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| Identify several interventions that might help improve response rates. Place them in order with the least-restrictive at the top so that the interventions may be introduced systematically, adding more restrictive / less favorable interventions after the outcomes of less restrictive options have been measured. | 1. Make It Easier to Do the Right Thing Add clear, color-coded tabs or labels for each client. Provide pens, clipboards, and pre-filled sections to reduce friction. Goal: Reduce the effort barrier to collecting data. 2. Pair Data Collection With Positive Reinforcement “Team A had 100% data today—great job staying client-focused!” Public reinforcement boards or token systems tied to team performance. Goal: Increase positive consequences for desired performance. 3. Increase Buy-In With Brief Trainings or Refreshers Use case examples showing how data led to better lives for clients. Goal: Shift culture toward valuing data as a direct client support. 4. Add Scheduled Times or Reminders for Data Entry Use visual reminders (posted signs, sticky notes, phone timers). Goal: Reduce competition from distractions by embedding data into the schedule. 5. Monitor and Give Private, Constructive Feedback “I noticed no data was collected for Client X this morning—let’s problem-solve why.” Goal: Add mild accountability without creating a punitive tone. 6. Tie Data Collection to Performance Evaluations Tracking completion rates weekly Using it as part of staff evaluations or coaching plans Goal: Ensure consequences are consistent with job expectations. 7. Reassign Responsibilities / Revise Team Roles Goal: Preserve quality and integrity of programming when all other options have failed. |
