CUSTOMER PROFILE
ABOUT
Northwestern Mutual is a financial services company providing life, disability income and long-term care insurance, annuities, brokerage and investment advisory services (such as for wealth and asset income protection, and education, retirement, estate and business planning), trust services, and discretionary portfolio management solutions. The mutual company, founded in 1859 in Wisconsin, has 4.5 million clients, served by more than 6,400 financial advisors at more than 300 offices across the United States. Northwestern Mutual is the largest direct provider of individual life insurance in the United States, as well as one of the “Top 5 U.S. Independent Broker- Dealers.” In 2017, the company paid $4.1B in claims and in 2018, it is expected to pay approximately $5.3B in dividends. With more than $1.6 trillion in life insurance in force today, Northwestern Mutual maintains among the highest financial strength ratings of all life insurers.
To provide service to clients and the field force, Northwestern Mutual currently employs more than 1,000 Client Services Representatives (CSRs) handling more than 3 million calls per year, with contact centers based in Wisconsin and Florida.
The company currently uses 150 CSR licenses for speech analytics. As a result of the positive experience to date, the company plans to expand the technology to additional contact centers, adding 200 CSR licenses. The company has also extended its contract with Nexidia’s Managed Analytics Services, based on positive initial results.
INDUSTRY
Financial Services
LOCATION
Nationwide in the United States
BUSINESS NEED
- Greater CSR efficiency
- Data accuracy
- Employee engagement
- Trend analysis
THE IMPACT
- 100% call recording and analysis for the Billing & Payments contact center
- AHT reduced by 6 seconds per call, for 1.2 million calls per year (based on analysis of 1 month of data)
- Estimated 40% improvement in reporting efficiency (data normalization efforts removed)
- Time to value in 4 months
THE CHALLENGE
Northwestern Mutual strives to provide quality service to clients and the field force. Prior to using Nexidia, the company used manual call logs and categorization at its contact centers. CSRs disliked the requirement, and found the manual recording tedious. There were also significant challenges with the manual process:
- Learning how the company categorizes calls was time-consuming, with some newer CSRs struggling to pick the right option out of an extensive list.
- The manual process took time away from answering incoming client and field calls.
- Calls were assigned to one category, regardless of its complexity.
- CSR subjectivity meant that the same call could be classified differently.
- CSRs tended to default to common call types.
The subjective, manual and time-sensitive system was vulnerable to human error, and it was difficult to validate the data. Managers had limited options for checking data. Some managers asked CSRs to take notes during client interactions so they could apply text filters in Excel to verify how often certain types of calls were handled. This added to the manual workload of the already busy teams.
These issues also made it hard to identify trends in the client experience or CSR service delivery.
THE SOLUTION
Northwestern Mutual wanted a solution that was less dependent on subjectivity and increased accuracy and speed. This would facilitate useful call analysis, allow CSRs to be more productive and ensure consistent results across the company’s contact centers.
Based on their requirements, Northwestern Mutual decided to integrate Nexidia Analytics into its call center workflows. The company saw the sophisticated speech analytics underpinning the solution as the most effective method of automating call categorization and tallying within the Billing & Payments contact center.
DISCOVERING WHAT’S WRONG AND MAKING IT RIGHT
The Nexidia Managed Analytics Services (MAS) team wrote dozens of queries to capture the reasons people were calling the Northwestern Mutual Billing & Payments contact center. These reasons include billing issues and questions, requests to cancel, policy changes, letters and communications, error messages, technology problems, escalations, and so on. At least 70 such call reasons have been defined for a single contact center, with more added regularly.
The MAS team’s work revealed gaps in the company’s manual call categorization process. According to Nexidia Analytics, callers average about two reasons per call; yet, CSRs were limited to just a single call reason category from a defined list. Therefore, assuming CSRs made wholly accurate selections in the past, at best the outcome could only be about 50% accurate.
Instead of manual dropdown call categorization lists, Nexidia Analytics captures each call and uses sophisticated speech analytics to determine the nature of the interaction. Now, Northwestern Mutual has a dedicated speech analytics team to provide detailed on-demand assessments and in-depth reports on customer behavior. This higher level of insight lends itself to a more robust analysis of contact center activities.
NICE is helping drive the effectiveness of Northwestern Mutual’s contact centers. They are going from anecdotes and estimates to data and ROI.
NEXIDIA ANALYTICS IS A WIN-WIN
The implementation of Nexidia Analytics, with a time to value of just four months, has provided positive results for Northwestern Mutual. For example, the NICE solution automatically categorizes and tallies interaction events. Eliminating a manual task allows the CSR to instead focus on providing the best customer service possible. This automation produced a reduction in handle time, by eliminating 20% of the post-call work, enabling CSRs to provide more focus on the client experience. The time savings per call is an average of six seconds, on a total of about 1.2 million calls each year. This is the equivalent of adding two full-time employees.
Along with cost-effectiveness, Nexidia Analytics ensures that the collection of data is accurate, impartial and covers 100% of the contact center calls. Accuracy in call categorization went from about 30% to 70%, while the stored data is more structured and clear. This facilitates more sophisticated queries, providing dozens of ways to identify trends.
As a result, there has been an estimated 40% improvement in efficiency in reporting, with managers, coaches and analysts no longer needing to do additional analysis. For example, the solution automatically identifies emerging trends in call volume through reporting, which significantly cuts down on manual spreadsheet manipulation. Moreover, new queries can be added to the tool on an ongoing basis, which can reprocess months of call recordings.
INSPIRING AND SUPPORTING MORE ENHANCEMENTS
Northwestern Mutual is actively exploring options for the implementation of NICE Quality Central. The Nexidia-driven call categorization would support that solution by helping coaches, trainers and managers automatically find a call on a given topic.
Nexidia Analytics has also complemented other priorities at Northwestern Mutual for improving the client experience. For example, the company is deploying a natural language IVR for the first time and gaining a comprehensive understanding of the call topics driving transfers.
What began as a single solution for analytics in the contact center has become part of a shift to data-driven improvements that will benefit the clients, field and employees of Northwestern Mutual.
