Using Quality Tools and Concepts to Improve Sales

Analysis of a Virtual Sales System with Call Centers in Two Separate Locations

By: Thomas Kaster

608-843-0394

[email protected]

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


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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


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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:


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:


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:


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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Using Quality Tools and Concepts to Improve Sales

Documents

sales performance

improved sales

sales representative

overall sales

sales associates

sales interaction

virtual sales system

sales operations system