Analysis of a Virtual Sales System with Call Centers in Two Separate Locations
By: Thomas Kaster
608-843-0394
Note: Due to the proprietary nature of information discussed, company name, location name
and personnel names will be labeled generically.
Paper Background and Purpose:
The purpose of this research was to analyze a call center sales operation system to identify
opportunities for quality improvement in regards to improved sales and customer service. The system
that is discussed is a direct to consumer, individual health solutions, sales call center. The call center
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has two distinct locations but is considered a virtual call center. Through the utilization of call routing
technology, when a call is received, it is routed to the next available agent in either location.
Calls are driven through mailed marketing materials, e-mail and television advertisements. Consumers
are provided an 800 number to receive further information. A call center specialist, who is licensed to
sell health and life insurance in the caller’s resident state, answers the call. The specialist determines
the eligibility of the caller, identifies what product fits their needs, provides a quote and tries to sell the
quoted plan. If the consumer agrees, a health assessment survey is completed and the survey is
submitted to underwriting to determine eligibility and provide a final offer of coverage.
The main product is an individual health insurance product, which offers a wide array of health care
coverage options including Individual Major Medical or Heath Savings Account (HSA) Qualified
insurance plans that have deductibles ranging from $1000 to $7500. Although the health plans are the
main product, there are three ancillary products which can be added to the health plan. These optional
benefits are strong profit drivers for the division. The ancillary products consist of a term life
insurance product, a comprehensive dental insurance product and an accidental benefit rider.
For the purpose of this paper, the names of the call center locations will be referred to as the North
location and the South location. As mentioned earlier, the call center is considered a virtual call
center. To better understand the dynamics of the operations of this system, it is important to provide
further detail on the definition of virtual. Both locations utilize the same software applications, take
the same calls, and have shared management. All management teams report through the same lines of
leadership. There are also members of the training department in both centers who report to the same
leadership. From a resource and leadership team standpoint, there is no quantitative difference
between the locations.
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Although the locations are virtual, there are several non-quantitative factors that need to be considered.
First, geographically, the centers are on opposite sides of the country. The demographics of each
location are completely different. The North location has primarily Caucasian and the South location
has primarily Hispanic and African American employees. In addition, although the lines of leadership
reporting are the same, the upper management resides in the North location. All these differences
create needs for high levels of diversity understanding as well as communication obstacles. Some of
these needs will be discussed later in the paper.
Unfortunately, like many sales operations, internal competition is a factor. Because of this, there is the
continual debate of who is selling better. From a raw numbers standpoint, counting number of health
policies sold per month, the South location is higher. However, the South Location has approximately
60 sales associates while the North has 45. The South location has 15 more so the number of total
sales will be more. As a result, if one were to look at performance based on sold policies alone, it
would not be an accurate analysis of performance. Other sources of measurement need to be
considered.
Considering these factors, the goal of this project is to improve overall sales for this sales operations
system.
Methodology
As with all sales call centers, a wide array of metrics are readily available to judge performance.
However, for this project it was important to choose the most fitting metrics that would provide
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equitable insight into sales performance. Since we are dealing with a significant difference in the
number of sales individuals in each location, choosing total sales would not be a fair measurement.
As a result I chose the following measurements to evaluate sales performance:
Metric #1: Health Sales Conversion Rate
Metric # 2: Dental Sales Conversion Rate
Metric # 3: Supplemental Accidental Benefit (SAB) Conversion Rate
Metric # 4: Life Insurance Sales Conversion Rate
Metric # 5: Health Sales Issue Rate
1.1 Operational Definition for: Health Sales Conversion Rate
Criterion: Based on the total number of calls that each sales representative receives, Health
Conversion Rate is the percentage of callers that an associate is able to send to underwriting for
a review of the consumers eligibility. During the sales interaction, the representative finds a
suitable plan for the consumer, determines if the consumer is eligible, gains affirmation from
the consumer that they want to continue with the underwriting process, and completes all pre-
underwriting requirements. Pre-underwriting requirements include:
The completion of an initial health assessment survey (application)
Consent to a Medical Information Bureau Recording (MIB)
Receipt of payment information
Test: Based on system driven dispositions and reporting, each sale is analyzed to determine if:
Based on the information available at the time of the sales interaction the consumer was
eligible
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The MIB was completed
The method of payment was received
The health survey was completed
The health survey was forwarded to underwriting
Decision: If the test criterion is met, the sale is qualified as being converted. The number of
calls that were converted divided by the total number of calls received provides the Conversion
Rate.
1.2 Operational Definition for: Dental / SAB / Life Sales Conversion Rate
Criterion: Dental Insurance, SAB and Life Insurance are all additional riders that can be
added to each health policy. None of the three are stand-alone policies, meaning that in order
to receive the optional benefits, the consumer must first qualify for the health policy. During
the sales interaction, the representative can propose to add these additional riders. If the
consumer agrees, the conversion for Dental, SAB or Life is calculated by dividing the total
numbers of applications where each ancillary product is added by the number of applications
submitted to underwriting (see 1.1: Operational Definition for: Health Sales Conversion Rate).
1.3 Operational Definition for: Health Sales Issue Rate
Criterion: Once a sales interaction has been completed and underwriting has reviewed the
application materials, a decision is made on the eligibility of the consumer. If the final
decision is to offer coverage, a contract is given to the consumer for review. The consumer
then needs to review, agree to and sign the contract. Once the signed offer is received, then
billing and enrollment will issue the policy. Within 24 hours, the first month’s premium is
withdrawn, and the consumer is considered a member. Once the consumer is a member, the
sale is considered issued.
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Test: Base on auto-generated tracking from our application management system, each step is
recorded when completed. Once the following system noted steps are recorded the application
is considered issued:
The application is converted to underwriting
UW has reviewed the medical history and provided an offer
The consumer receives the offer
The consumer accepts the offer, signs and returns the documents
The signed documents are received by the underwriting department and processed to
the billing and enrollment department
Twenty-four hours later, the applicant is listed as a member in Billing and Enrollment
Decision: If the test criteria are met, the policy qualifies as being issued. The issue rate is
calculated by dividing the number of issued policies by the number of applications converted
to underwriting.
Discussion on Metrics Chosen
Issue Rate Pros and Cons
Looking at this process as a complete system, the interested caller would be considered the input. All
activities including the sale and underwriting would be steps in the throughput, and the output is
members. Considering this, the most telling metric is issue rate, because when an applicant is issued,
they are members. However, although a sales representative has some control over their issue rate,
they do not have total control. For example, if a member is eligible based on a preliminary eligibility
review during the sales process but is deemed ineligible upon underwriting review, a declined
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application could not have been avoided. Or, if the consumer does not like the final offer, or decides
later that they can’t afford or do not want the plan the sales representatives has no control.
On the other hand, the sales representative can impact their issue rate by being detailed and upfront
with the consumer in regards to potential ratings and riders, based on information gained in the initial
eligibility review. Another factor that may affect issue rate is benefit review. During the sales
interaction, representatives can be tempted to down play significant benefit details that the consumers
may not like or value. If this sort of tampering happens, the consumers have a higher tendency to not
accept the offer after they review the plan details, post underwriting. This practice is a concern
because it drives up operational expenses by spending underwriting dollars on non-interested
consumers.
It should be noted that for this study, the issue rate was only available for Health policies. For SAB,
Dental and Life Policies, the conversion rate was the only available metric.
It should also be noted that the depth of the performance numbers were limited to each supervisor’s
team performance and not at the sales representative level. Each team consists of 15 associates. Each
associate’s numbers are averaged to give the supervisor’s overall team performance.
Conversion Rate Pros and Cons
The conversion rate is a valuable metric for evaluating the effectiveness of a sales representative. If
the representative is communicating effectively, keeping the consumer engaged, analyzing their needs,
asking all eligible callers to buy, and overcoming objections, they should have a strong conversion
rate. If the consumers are offering the ancillary products diligently and effectively, they should have a
strong conversion rate for SAB, Dental and Life.
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One drawback of using conversion rates as a sole performance measure is that it can easily be
tampered with. When sales incentives are based on having high conversion, conversion numbers do
indeed go up, despite no change to the system. As mentioned in issue rate discussion, sales
representatives can do many things in their sales presentation that can cause increased conversion.
Increased conversion due to misleading the consumer or poor eligibility review, causes increased
overhead in underwriting. If a consumer who has been mislead becomes a member, and uses the
coverage only to find out that they had a waiting period or a higher than expected deductible, the cost
of that unhappy customer is immeasurable. The potential tampering of this metric does not rest solely
on the sales representatives hands. Each supervisor listens to at least two sales calls per person per
week and coaches then accordingly. Consequently, a supervisor can have a great deal of influence and
cause tampering on a team level scale.
Final Methodology Review:
To gauge performance and analyze opportunities for review, each of the above metrics were placed
into control charts. The control charts were organized the in following ways:
1. Looking at both the North and South locations as one complete system and analyzing the
between group variation, during a nine month timeframe
2. Looking at each location as its own system, and analyzing between group variation, during a
nine month timeframe
3. Looking at each supervisor’s team performance to analyze within-group variation, during a
nine month timeframe.
Other quality tools used, included a cause and effect diagram and a PDCA quality cycle and Pareto
charts and diagrams.
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With regards to PDCA quality circles and due to the nature of the project (and the need for a director
level approval of the proposed recommendations) this analysis was limited to the end of the “Do”
stage, where recommendations for improvement were provided.
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Discussion and Results
Looking at both locations combined as one system
The first step in the analysis was to determine if the complete system (North and South Locations
Combined) was in statistical control for each performance metric.
Please reference 2.1 for all location issue rate analysis:
Data Set
N1 N2 N3 N4 S1 S2 S3 S4 S5Jan 0.40 0.40 0.44 0.38 0.39 0.38 0.43 0.49 0.38Feb 0.35 0.45 0.43 0.40 0.41 0.40 0.42 0.42 0.45Mar 0.35 0.50 0.41 0.44 0.41 0.41 0.47 0.44 0.38Apr 0.34 0.44 0.40 0.42 0.43 0.42 0.40 0.41 0.40May 0.44 0.46 0.45 0.55 0.45 0.44 0.47 0.47 0.44Jun 0.40 0.60 0.50 0.46 0.39 0.46 0.50 0.47 0.41Jul 0.42 0.48 0.55 0.44 0.42 0.49 0.51 0.48 0.48Aug 0.44 0.49 0.51 0.48 0.45 0.49 0.51 0.47 0.45Sep 0.43 0.49 0.44 0.43 0.41 0.45 0.43 0.44 0.43
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Analysis of 2.1:
The Health Issue Rate for the entire system is in statistical control. The system is averaging 42% and
can range from 33% to 52% in any given month.
Please reference chart 2.2 for all location conversion rate performance:
Data Set
N1 N2 N3 N4 S1 S2 S3 S4 S5Jan 0.12 0.11 0.12 0.12 0.11 0.13 0.11 0.12 0.13Feb 0.15 0.13 0.13 0.13 0.12 0.13 0.12 0.11 0.14Mar 0.13 0.13 0.12 0.11 0.12 0.13 0.11 0.11 0.12Apr 0.12 0.13 0.12 0.12 0.14 0.13 0.12 0.12 0.14May 0.13 0.15 0.12 0.12 0.16 0.13 0.13 0.12 0.16Jun 0.13 0.12 0.13 0.13 0.16 0.12 0.13 0.11 0.16Jul 0.13 0.13 0.11 0.13 0.14 0.11 0.11 0.1 0.13Aug 0.13 0.13 0.13 0.13 0.12 0.11 0.11 0.1 0.13Sep 0.11 0.13 0.14 0.14 0.14 0.11 0.11 0.11 0.13
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Analysis of 2.2:
The Health Conversion Rate for the entire system is in statistical control. The system is averaging 12%
and Can Range from 9% to 14% in any given month.
Please reference chart 2.3 for all location dental conversion rate analysis:
Data Set
N1 N2 N3 N4 S1 S2 S3 S4 S5Jan 0.59 0.52 0.63 0.6 0.44 0.44 0.42 0.5 0.53Feb 0.56 0.49 0.6 0.58 0.46 0.48 0.45 0.51 0.55Mar 0.46 0.53 0.56 0.55 0.45 0.44 0.37 0.5 0.53Apr 0.54 0.54 0.61 0.5 0.43 0.44 0.41 0.5 0.49May 0.53 0.53 0.58 0.54 0.54 0.43 0.43 0.48 0.48Jun 0.47 0.46 0.53 0.54 0.55 0.44 0.37 0.49 0.45Jul 0.58 0.51 0.57 0.53 0.55 0.45 0.42 0.48 0.38Aug 0.51 0.51 0.54 0.53 0.57 0.47 0.39 0.49 0.43Sep 0.46 0.51 0.58 0.55 0.58 0.45 0.45 0.58 0.48
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Analysis of 2.3
The Dental Conversion Rate for the entire system is in statistical control. The system is averaging
48% and can range from 37% to 60% in any given month.
Please reference chart 2.4 for all location life conversion rate analysis:
Data Set:
month N1 N2 N3 N4 S1 S2 S3 S4 S5Jan 0.31 0.19 0.35 0.24 0.16 0.30 0.17 0.21 0.12Feb 0.32 0.16 0.32 0.25 0.16 0.27 0.10 0.19 0.12Mar 0.28 0.17 0.34 0.18 0.14 0.23 0.09 0.22 0.12Apr 0.21 0.22 0.34 0.26 0.15 0.24 0.12 0.19 0.14May 0.22 0.22 0.39 0.29 0.20 0.22 0.12 0.13 0.12Jun 0.23 0.18 0.29 0.29 0.26 0.21 0.08 0.17 0.11Jul 0.24 0.19 0.30 0.28 0.30 0.19 0.12 0.13 0.11Aug 0.28 0.19 0.25 0.28 0.28 0.17 0.10 0.14 0.11Sep 0.14 0.19 0.34 0.29 0.34 0.23 0.13 0.18 0.17
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Analysis of 2.4:
The Life Conversion Rate for the entire system is in statistical control. The system is averaging 20%
and can range from 11% to 29% in any given month.
Please reference 2.5 for supplemental accident benefit (SAB) rider conversion:
Data Set
month N1 N2 N3 N4 S1 S2 S3 S4 S5Jan 0.28 0.19 0.18 0.15 0.13 0.06 0.07 0.10 0.04Feb 0.30 0.36 0.20 0.44 0.17 0.06 0.07 0.15 0.06Mar 0.62 0.51 0.68 0.58 0.23 0.22 0.16 0.45 0.28Apr 0.58 0.62 0.73 0.59 0.47 0.28 0.35 0.57 0.46May 0.79 0.66 0.73 0.69 0.64 0.39 0.53 0.60 0.53Jun 0.87 0.66 0.67 0.73 0.63 0.35 0.38 0.60 0.51Jul 0.82 0.50 0.71 0.69 0.60 0.43 0.44 0.64 0.51Aug 0.88 0.55 0.73 0.79 0.61 0.44 0.36 0.69 0.51Sep 0.82 0.58 0.78 0.78 0.64 0.56 0.48 0.71 0.62
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Analysis of 2.5:
In regards to the Supplemental Accidental Benefit Rider, the system was not in statistical control. As
a result further analysis was needed to determine what happened with point one and point two which
represent January and February in this nine month time period.
Based on training and operational records, the system was changed, or improved, which increased
SAB Conversion Rate. In early February, it was determined through analysis, that there was an
opportunity to increase the adoption of this rider by our consumers. Based on this the following steps
were taken:
1. An increased emphasis of offering SAB was communicated to sales reps through team
meetings with their managers and supervisors.
2. Additional training was provided to help sales reps better understand the value of the SAB
rider, how it can help their consumers and how they can sell and position the product.
3. Continual support and reinforcement was provided to associates from improved reporting and
support from their front line supervisors.
Due to the increased training and awareness, by early March, SAB conversion improved significantly.
For analysis purposes, January and February were taken out of control chart data to analyze the status
of the system from the change in March through September.
Please reference adjusted chart 2.6 for supplemental accident benefit (SAB) rider conversion
analysis.
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Data Set
N1 N2 N3 N4 S1 S2 S3 S4 S5Mar 0.62 0.51 0.68 0.58 0.23 0.22 0.16 0.45 0.28Apr 0.58 0.62 0.73 0.59 0.47 0.28 0.35 0.57 0.46May 0.79 0.66 0.73 0.69 0.64 0.39 0.53 0.6 0.53Jun 0.87 0.66 0.67 0.73 0.63 0.35 0.38 0.6 0.51Jul 0.82 0.61 0.71 0.69 0.6 0.43 0.44 0.64 0.51Aug 0.88 0.64 0.73 0.79 0.61 0.44 0.36 0.69 0.51Sep 0.82 0.64 0.78 0.78 0.64 0.56 0.48 0.71 0.62
Analysis of 2.6:
After taking into consideration the system change in late February, and withholding January and
February numbers from the control chart, one can conclude that SAB Conversion is in statistical
control for the complete system. The system averages 55% and can range from 34% to 75% in any
given month.
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Final analysis looking at both locations as the complete system
Based on the above data and analysis, and after adjusting for changes in the system, one can conclude that for all performance measurement metrics, the system as a whole is in statistical control.
Looking at each location as its own system
As mentioned earlier, although the sales operations of this division are considered virtual, there are
regional, leadership, communication and personnel differences that can impact overall performance of
a location. Because of this, it is logical to look at each location as if it were its own system.
For the below analysis, the performance numbers for each location were separated and placed into
separate control chart. From there, a side by side analysis was completed comparing each location’s
performance in the chosen metrics.
Please reference 3.1.1 and 3.1.2 for the issue rate side by side analysis in each location:
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Analysis of 3.1.1 and 3.1.2:
Based on the above graph, both locations are in statistical control for the issue rate. The North
location is averaging 44% and can range from 37% to 52% in any given month. The South location
also averages at 44% but ranges from 48% to 40% in any given month. One point of interest is the
South location has a lower standard deviation of only 29% compared to the North’s standard deviation
of 47%. The lower standard deviation may mean the South is more consistent in their conversion rate
and the North has higher peaks and valleys. Regardless, the side by side comparison of issue rate does
not indicate any major concerns.
Please reference 3.2.1 and 3.2.2 for health conversion rate side by side analysis for each location:
Analysis of 3.2.1 and 3.2.2:
In regards to health conversion rate, both locations are in statistical control. The North location
averages a 13% health conversion rate ranging from 11% to 14% in any given month. The South
location averages 12% and can range from 10% to 14% on any given month. When comparing the
averages from each location, the difference is only one percent. One percent is not significant enough
to take action.
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Please reference 3.3.1 and 3.3.2 for dental conversion rate side by side comparison each location:
Analysis of 3.3.1 and 3.3.2:
For Dental conversion, both locations are in statistical control. However, for Dental conversion the
North location averages 7% higher than the South location. The North is averaging a 54% Dental
conversion verses South’s 47%. The 7% difference may be significant. More analysis will follow.
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Please reference 3.4.1 and 3.4.2 for life conversion rate side by side analysis for each location:
Analysis of 3.4.1 and 3.4.2:
With regards to Life conversion, both locations are each in statistical control. However, like Dental
conversion, the South location is averaging lower. For Life conversion, the North is averaging 26%
and the South is 17% producing a 9% difference.
Please reference 3.6.1 and 3.6.2 for SAB conversion rate Side by Side analysis for each location:
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Analysis of 3.6.1 and 3.6.2
Note: In the analysis of SAB conversion that included both locations as one system, the final analysis
looked at metrics from March through September. It was determined that in February, the system was
changed which improved the system starting in March.
When analyzing SAB conversion for each location, one can see the North’s SAB conversion is in
statistical control and South is not. Further analysis to determine why the South location was out of
statistical control in March revealed the awareness and training campaign did not happen until March.
As a result, the sales representatives did not have the knowledge and tools they needed to improve.
When comparing averages the North is converting SAB at 70% compared to South’s 48%, a 22%
difference.
Summary of between group variation analysis of performance metrics
Based on between group variation analysis, the differences between locations for health conversion
and issue rates are negligible. When analyzing the sales performance of the ancillary products, a
significant profit center for the division, the performance in the South location has lower average
performance than the North location.
For further analysis, within group variation (Supervisor to Supervisor) was needed.
Within subgroup variation analysis of performance metrics (Supervisor to Supervisor)
As indicated in the between group variation analysis, the conversion rates for the ancillary products,
Dental, Life and SAB, indicated an opportunity for further analysis. To do further analysis, the data
was restacked so each supervisor’s team performance was analyzed compared to the other supervisors.
In the analysis, N1 through N4, in the data set, and points one through four in the control charts,
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represent the North supervisors. S5 through S9 in the dataset and points five through nine in the
control charts, represent the South supervisors. See results below:
Please reference 4.1 for dental conversion rate analysis by supervisor:
Data Set:
Jan Feb Mar Apr May Jun Jul Aug SepN1 0.59 0.56 0.46 0.54 0.53 0.47 0.58 0.51 0.46N2 0.52 0.49 0.53 0.54 0.53 0.46 0.51 0.51 0.51N3 0.63 0.6 0.56 0.61 0.58 0.53 0.57 0.54 0.58N4 0.6 0.58 0.55 0.5 0.54 0.54 0.53 0.53 0.55S5 0.44 0.46 0.45 0.43 0.54 0.55 0.55 0.57 0.58S6 0.44 0.48 0.44 0.44 0.43 0.44 0.45 0.47 0.45S7 0.42 0.45 0.37 0.41 0.43 0.37 0.42 0.39 0.45S8 0.5 0.51 0.5 0.5 0.48 0.49 0.48 0.49 0.58S9 0.53 0.55 0.53 0.49 0.48 0.45 0.38 0.43 0.48
Analysis of 4.1
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Based on control chart 4.1, supervisor teams for N3 and N4 are out of statistical control on the high
end and supervisor teams S6 and S7 are out of statistical control on the low end for Dental Conversion.
Please reference chart 4.2 for life conversion rate analysis by supervisor:
DatasetJan Feb Mar Apr May Jun Jul Aug Sep
N1 0.31 0.32 0.28 0.21 0.22 0.23 0.24 0.28 0.14N2 0.19 0.16 0.17 0.22 0.22 0.18 0.19 0.19 0.19N3 0.35 0.32 0.34 0.34 0.39 0.29 0.30 0.25 0.34N4 0.24 0.25 0.18 0.26 0.29 0.29 0.28 0.28 0.29S5 0.16 0.16 0.14 0.15 0.20 0.26 0.30 0.28 0.34S6 0.30 0.27 0.23 0.24 0.22 0.21 0.19 0.17 0.23S7 0.17 0.10 0.09 0.12 0.12 0.08 0.12 0.10 0.13S8 0.21 0.19 0.22 0.19 0.13 0.17 0.13 0.14 0.18S9 0.12 0.12 0.12 0.14 0.12 0.11 0.11 0.11 0.17
Analysis of 4.2
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Based on control chart 4.2, supervisor teams for N3 and N4 are out of statistical control on the high
side and supervisor team S7, S8 and S9 are out of statistical control on the low side. In summary,
when analyzing the performance of Life conversion, the North supervisors are averaging higher than
the South. To determine the next steps for improvement further research is needed to see what N3 and
N4 are doing to achieve higher dental conversion and what S7, S8 and S9 are not doing.
Please reference chart 4.3 for SAB conversion rate analysis by supervisor:
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Data Set
Mar Apr May Jun Jul Aug SepN1 0.62 0.58 0.79 0.87 0.82 0.88 0.82N2 0.51 0.62 0.66 0.66 0.61 0.64 0.64N3 0.68 0.73 0.73 0.67 0.71 0.73 0.78N4 0.58 0.59 0.69 0.73 0.69 0.79 0.78S5 0.23 0.47 0.64 0.63 0.6 0.61 0.64S6 0.22 0.28 0.39 0.35 0.43 0.44 0.56S7 0.16 0.35 0.53 0.38 0.44 0.36 0.48S8 0.45 0.57 0.6 0.6 0.64 0.69 0.71S9 0.28 0.46 0.53 0.51 0.51 0.51 0.62
Analysis of 4.3
Based on control chart 4.3, supervisor team N1, N3 and N4 are out of statistical control on the high
side and teams S6, S7, S8 and S9 are out of statistical control on the low side. In summary, three out
of four North supervisor teams are exceeding the limitations of the process in regards to SAB
conversion. In comparison, three out of five South supervisor teams are below the system limitations
in regards to SAB conversions.
Summary of all Control Chart Analysis
In summary, based on analysis of all sales performance analysis metrics, one can conclude the South
location is lacking in their ability to sell the three ancillary products of Dental and Life Insurance and
the Supplemental Accidental Benefit Rider. Considering the ancillary products are a profit center for
this division, determining the reason for the discrepancy, and finding ways to improve the
performance of the South location will increase overall profit.
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Why is the South location not selling ancillary products as well as the North?
To help diagnose why the South location is not selling ancillary products as well as the North the
following cause and effect diagram was constructed.
Please reference cause and effect diagram 5.1:
Analysis and discussion of figure 5.1
Based on the analysis of figure 5.1 three areas were identified that interrelate which may be a cause for
the deficiency in ancillary sales production. Please reference the areas highlighted in yellow in figure
5.1.
Starting with the environment, the South job market is extremely competitive in regards to call center
jobs. As a result, in the 2008 calendar year the South office hired only 16 new sales representatives.
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Conversely, the North location’s geographic area was able to recruit more effectively and hired 29
new sales associates. Basically, 65% of the North location’s sale representatives have been hired in
the last 12 months compared to 26% in the South location.
After reviewing training documentation and records, it was found that early in 2008 new hire training
was drastically modified, in an effort to make new hires more productive post training. Part of this
modification included a new strategy, expectation, and emphasis on how ancillary products were
offered and sold. In the training, new hires were given ample opportunity to practice and apply the
concepts. As a result of the improved training, the new hires were able to effectively cross offer and
sell our ancillary products immediately.
The new strategy and expectations were provided to veteran reps through self learning materials and
team meeting discussion groups. There was no formal training or change management measurement
implemented to insure that veteran reps would correctly apply the methods and expectations. In
addition, veteran reps did not have ample opportunity to practice using the new strategies.
Again referencing figure 5.1, none of the South or North management team attended the modified
training for ancillary product sales. Although many provided feedback and input into the development
of the materials, none sat through the training. For the North group, leadership not attending the
training may not have as large an impact on ancillary sales conversion, because 65% of their staff
received the modified training. For the South location, supervisors and managers not attending the
training may have had a much larger impact, because 74% of their staff consisted of veteran reps that
had not had the new training. The new concepts were reportedly facilitated, for veteran reps, through
supervisors in team meetings in both locations. Due to the fact the supervisors had not been formally
trained on the new materials, the effectiveness of the facilitation is in question.
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In summary the cause derived from figure 5.1 was that a major reason why the South location was
lacking in ancillary sales performance was because a large portion of their staff did not have sufficient
training and development.
Short summary of modified training for new hires
The modified ancillary products sales training for new hires consisted of the below basic concepts:
1. Dental Insurance, Life Insurance and Supplemental Accident Benefit (SAB) are offered on
every application, with no exception.
2. The offer should not be in the form of closed ended question.
3. The offer needs to focus on providing detail on the main value and benefits of each product
first and then ask the consumer if they are interested.
There is much discussion and the purpose and reasoning of each concept above; however, it is out of
the scope of this paper.
Final analysis of ancillary product conversion performance
The final analysis of the performance of each location’s ancillary product performance focused on
listening to actual calls. For compliance and auditing purposes, all calls coming in and out of the call
centers are digitally recorded. Utilizing this technology, 100 random calls in each location were
audited. The calls were recorded on a check sheet and then placed into a Pareto diagram. The
following details were audited on each call.
1. Were all three ancillary products offered using modified training techniques
2. Were two of the three ancillary products offered using modified training techniques
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3. Was one of the three ancillary products offered using modified training techniques
4. Were all three offered not using new techniques
5. Were two of the three offered not using new techniques
6. Was one offered not using new techniques
7. Were none offered
The check sheets offered the following data:
South Call Review All 3 with new IIIII 52 of 3 with new IIII 41 of 3 with new IIIIIIIII 9All 3 not using new IIIIIIIIIIIIIIIIII 182 of 3 not using new IIIIIIIIIIIII 131 of three not using new IIIIIIIIIIIIIIIIIIIIII 22None offered IIIIIIIIIIIIIIIIIIIIIIIIIIIII 29 total 100
North Call Review All 3 with new IIIIIIIIIIIIIIIIIIIIIIIIIIIII 292 of 3 with new IIIIIIIIIIIIIIIIIIIIIIIIIII 271 of 3 with new IIIIIIIIIIIIII 14All 3 not using new IIIIIIII 82 of 3 not using new IIIIII 61 of three not using new IIIIIIIIII 10None offered IIIIII 6 total 100
Please see 7.1 and 7.2 for Pareto chart results:
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Analysis of Pareto Charts 7.1 and 7.2
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From charts 7.1 (South Call Analysis) and 7.2 (North Call Analysis), it is evident the new ancillary
product selling techniques are not being utilized in the South location. Per 7.1, in 29% of calls the
ancillary products were not even mentioned. In 69% of the calls either no ancillary products were
offered or if they were offered, the outdated method was used.
Per 7.2, the complete opposite performance was recorded in the North location. In 29% of calls all
three ancillary products were offered using the new technique. In 70% of calls the new strategy was
used for at least one ancillary product sales attempt.
Summary of all analysis
Based on all the analysis, data and quality tools provided, it is evident the south location is lacking in
ancillary sales ability. This responsibility of this deficiency does not rest on the sales associates, their
supervisors or even their management. The successes of the North location in regards to cross
offering ancillary products can not be entirely attributed to the performance of the supervisors or
managers as well.
From looking at each location as a separate system, there is a strong indication the employee recruiting
market may be a factor. The division in performance exists due to the fact the overwhelming majority
of 2008 recruiting and hiring was done in the North location, combined with the enhanced and
modified ancillary sales training, for new hires.
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Final Recommendations
In an effort to increase overall profitability, through the sales of Dental and Life Insurance and the
Supplemental Accident Benefit Rider, additional training is recommended:
1. Training calibration needs to be completed between sales trainers in North and South locations
to insure consistency in the content and delivery of ancillary product sales training.
2. Ancillary product sales training workshop for all North location representatives.
3. Ancillary product sales training workshop for all North Supervisors and Managers.
4. Ancillary product sales training workshop for all South locations representatives who have
tenure of greater than 12 months.
5. Ancillary product sales training workshop for all North supervisors and managers.
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