CUSTOMER PROFILE
Healthcare system Kaiser Permanente’s Northern California pharmacy call center serves 2.5 million contacts annually with questions ranging from shipment status to drug interaction details. For years, all calls were recorded in NICE Engage, but the quality team was small and review processes were limited and manual. Kaiser Permanente added NICE Enlighten AI for Customer Satisfaction (CSAT) and Real-Time Interaction Guidance to streamline several components of the in-call and post-call experience for customers, agents, and supervisors alike. The added features support the pharmacy’s aggressive service level and handle time targets, have helped boost customer sentiment across the board and provide insights and operational efficiencies with ongoing workflow automation improvements.
01 THE BEFORE
A vault of recordings, but limited insights
The quality assurance team of Kaiser Permanente’s pharmacy operation had comprehensive access to all inbound and outbound call recordings handled by both general agents and licensed pharmacist professionals through NICE Engage. However, the small team could only assess two calls per agent per month using a manual and time-consuming process, involving 17 evaluation form questions that included subjective criteria. Agents also had to manually select a disposition post-call. To avoid delays in call handling, the pharmacy offered agents a limited number of caller reasons to select from, but this in turn limited the insights Kaiser Permanente could draw from disposition tracking.
02 DESIRE TO CHANGE
An upgraded experience encumbered by manual processes
The pharmacy wanted to make several operational and experiential upgrades, all of which required smoother call flow and more efficient review processes. In addition to reducing call volume by identifying and steering more call types to self-service, Kaiser Permanente wanted to bring AHT down to prepandemic levels and evaluate more agent calls more effectively. Under the previous workflow, less than 1% of recorded calls were reviewed. “That’s too small a sample size to detect if the agent is truly meeting goals,” said Joenil Mistal, Kaiser Permanente Senior Managerial Consultant.
The pharmacy also wanted more granular disposition data but recognized that adding more dispositions to the agent post-call drop-down window would sabotage other goals. “We couldn’t put in a list of the 25 or 30 specific disposition codes we care about, because that would be too much for the agents to sort through,” Mistal said. “Reducing five or 10 seconds of handling time is critical for us to ensure that we’re efficient, so we can’t spend that time having agents search a menu.”
03 THE SOLUTION
Comprehensive call evaluation and real-time guidance with NICE solutions
At a NICE user conference, Kaiser Permanente learned about the potential of NICE Enlighten AI for CSAT to automate several points of analysis and review tasks relating to performance and agent soft skills evaluation. “When we learned what was possible, we submitted a business case to leadership and obtained funding,” Mistal said.
NICE Enlighten AI for CSAT now evaluates 100% of pharmacy calls on key soft skill behaviors including active listening, being empathetic, demonstrating ownership, and effective questioning. In-call, NICE Real-Time Interaction Guidance (RTIG) shows real-time sentiment scoring and assists agents during the call to reduce AHT. RTIG provides reminders on workflow changes, automatic links to internal documents, and other configured trigger events based on call topics. RTIG can also be used to push key new developments or points of emphasis to agents during the interaction to have an immediate impact on customer sentiment.
Post-call, NICE Interaction Analytics determines call dispositions, more quickly and with greater precision than the previous manual agent post-call menu could. Team managers have dashboards to monitor team AHT across numerous call intents, and can send out agent alerts based on noteworthy sentiment scoring or other Enlighten findings.
Quality Management gives agents insights into their soft skill behaviors as well as readouts on their average talk time and sentiment scores. “It’s amazing to see the kinds of coaching or other interventions possible now with this level of detail, compared to what is possible when you can only manually review two calls per agent per month,” Mistal said.
04 THE RESULTS
Satisfaction is on the rise as AI insights help callers and agents alike
With automated intent analysis across all calls, Kaiser Permanente’s pharmacy enjoys significantly improved insights into root causes and call drivers. Enlighten AI-driven soft skills analysis has eliminated seven manual review items from the call QA process, leaving coaches to focus on workflow adherence and other sophisticated business considerations. In turn, member satisfaction and retention are improved because key sources of dissatisfaction and frustration were identified and proactively addressed. Customer sentiment is up across all of the pharmacy’s agent teams year-over-year post-implementation. “We’re now able to pinpoint issues in our processes, procedures, and understanding of member needs,” Mistal said.
Between RTIG alerts and sentiment dashboards, agents now have substantially faster and greater access to information related to performance and excellence, and the response has been positive from front-line agents overall, with adoption increasing ten percentage points since launch to 94%. “RTIG has been key to improving our workflow, pushing information quickly to agents so they can quickly and efficiently share answers with our members instead of having to hunt,” Mistal said.
The improvements and insights uncovered through Enlighten AI analysis are credited with helping Kaiser Permanente on its push to reach and maintain a 240-second AHT goal and 80% answer rate within a 30-second service target. “We’re going to be able to sustain our headcount and achieve our service goals,” Mistal said.
05 THE FUTURE
Wider rollout and deeper insights in-store
Kaiser Permanente continues working with contact center union leaders on further adoption and wider implementation of tools, self-monitoring, and setting expectations for self-correction. The pharmacy also plans to find more ways to apply Enlighten AI insight to call evaluations, helping supervisors focus on additional workflow processes and leaving behavioral analysis to automated, objective scoring.