Why has the number of pharmacies actively using CoverMyMeds's Real-Time Prescription Benefit (RTPB) tool decreased by 20% since the latest software update?

Introduction

The recent 20% decrease in pharmacies actively using CoverMyMeds's Real-Time Prescription Benefit (RTPB) tool following a software update is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our product and users.

I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into product understanding, metric breakdown, and hypothesis formation. We'll then conduct a thorough root cause analysis, propose validation methods, and outline a comprehensive resolution plan.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this might be related to the software update. Can you confirm when exactly the update was rolled out and if it was a phased rollout or all at once?

Why it matters: This helps pinpoint the exact timeframe of the issue and whether it correlates directly with the update. Expected answer: The update was rolled out two weeks ago, all at once. Impact on approach: If it aligns perfectly, we'll focus more on technical issues; if not, we'll consider broader factors.

• Considering user segments, I'm curious if this decrease is uniform across all pharmacy types. Have you noticed any patterns in terms of which pharmacies are most affected?

Why it matters: This could reveal whether the issue is more prevalent in certain user segments, helping us narrow down potential causes. Expected answer: Independent pharmacies seem more affected than large chains. Impact on approach: If there's a clear pattern, we'll tailor our investigation and solutions to the most impacted segments.

• Regarding performance metrics, I'm wondering if there have been any changes in other related metrics, such as prescription processing time or error rates?

Why it matters: This helps us understand if the issue is isolated to usage or if it's part of a broader performance problem. Expected answer: There's been a slight increase in processing time but no significant change in error rates. Impact on approach: If other metrics are affected, we'll need to consider more systemic issues; if not, we'll focus on usage-specific factors.

• Thinking about user feedback, have there been any notable changes in the volume or nature of support tickets or user complaints since the update?

Why it matters: This provides insight into whether users are actively experiencing problems or silently disengaging. Expected answer: There's been a 30% increase in support tickets related to difficulty accessing the tool. Impact on approach: If there's a spike in complaints, we'll prioritize investigating those specific issues; if not, we'll look more at silent usability problems.