36%
Improvement in Near-Term Forecast Accuracy
12%
in Staff Savings
39%
Savings for Authorizations
Overview
This home services company has provided various home warranty, repair, and maintenance services for over 35 years. With a network of more than 40,000 independent skilled service technicians, they help their customers solve problems every day – and their contact centers provide support 24/7/365. They faced workforce management challenges, so they partnered with Insite.
Challenges
Due to the nature of their business, customer usage can significantly increase during weather and climate changes. As a result, they struggle to forecast accurately and predict volumes, creating capacity and scheduling gaps. The outcome delivers poor Service Lead results for customers when they need the product/service the most. To overcome this challenge, they requested an evaluation of their current forecasting methods to identify improvement opportunities and build improvements into the forecasting approach.
“Great collaboration and clear progress— we’re on the right path to making meaningful improvements to our reports. The team’s expertise and openness to feedback have made a real difference in driving these enhancements forward.”
- Travis E.
Solutions
Through two intense days, Insite completed an evaluation. We met with 15 individuals and collected over 50 reports to immerse ourselves in their business operations. Leveraging the information we gained while on site, we then worked remotely to draw numerous correlations between internal and external factors on call volume.
Using these data points, we developed a forecast to plan the work volume minutes required to meet call volume demand. Testing against known data points, we refined the forecasting.
Listed below are our findings:
Although the initial correlation linking weather events to claims was marginally correct, there was a much higher correlation between original claims to calls.
As we reviewed claims by state, we found it was not a simple curve based on temperature. Instead, the correlation linked claim volume to a specific “event” caused by average temperature increases each week. We used this method to forecast the weeks following an “event.”
When temperatures rose, customers were more prone to call and make a claim while staying on the phone longer, leading to a 40% increase in workload through AHT and call volume.
Results
Based on these findings, we were able to provide this call center with an accurate forecasting tool and make the following recommendations:
Establish “New Claims” and monitor against claims that are reworked.
Utilize the improved forecasting model and update data weekly.
Implement weather monitoring weekly, leveraging known call patterns to make near-term planning adjustments.
Conclusions
This home warranty provider faced challenges forecasting customer demand because usage would jump significantly with weather changes. This made it hard to schedule staff and led to poor customer service.
Insite analyzed their operations and found a strong correlation between new claims and calls, particularly associated with weekly temperature increases. This led to a huge workload spike. By implementing Insite’s new forecasting model, the provider achieved a improvement in forecast accuracy and significant savings on staff and authorizations. The result is a consistent customer experience and cost savings.
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