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Analysis of a Virtual Sales System with Call Centers in Two Separate Locations<br />By: Thomas Kaster<br />608-843-0394<br />Tkaster27@gmail.com<br />Note: Due to the proprietary nature of information discussed, company name, location name and personnel names will be labeled generically.<br />Paper Background and Purpose:<br />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 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.<br />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.<br />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.<br />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.  <br />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.<br />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.<br />Considering these factors, the goal of this project is to improve overall sales for this sales operations system. <br />Methodology<br />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   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:<br />,[object Object]
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 Rate1.1Operational Definition for: Health Sales Conversion Rate<br />,[object Object]
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
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.1.2Operational Definition for: Dental / SAB / Life Sales Conversion Rate<br />,[object Object],1.3 Operational Definition for:  Health Sales Issue Rate<br />,[object Object]
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<br />Issue Rate Pros and Cons<br />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 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.<br />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.  <br />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. <br />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.<br />Conversion Rate Pros and Cons<br />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.<br />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.<br />Final Methodology Review:<br />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:<br />,[object Object]
Looking at each location as its own system, and analyzing between group variation, during a nine month timeframe
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.  <br />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.  <br />Discussion and Results<br />Looking at both locations combined as one system<br />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.   <br />Please reference 2.1 for all location issue rate analysis:<br />Data Set<br />N1N2N3N4S1S2S3S4S5Jan0.400.400.440.380.390.380.430.490.38Feb0.350.450.430.400.410.400.420.420.45Mar0.350.500.410.440.410.410.470.440.38Apr0.340.440.400.420.430.420.400.410.40May0.440.460.450.550.450.440.470.470.44Jun0.400.600.500.460.390.460.500.470.41Jul0.420.480.550.440.420.490.510.480.48Aug0.440.490.510.480.450.490.510.470.45Sep0.430.490.440.430.410.450.430.440.43<br />Analysis of 2.1:<br />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.<br />Please reference chart 2.2 for all location conversion rate performance:<br />Data Set<br />N1N2N3N4S1S2S3S4S5Jan0.120.110.120.120.110.130.110.120.13Feb0.150.130.130.130.120.130.120.110.14Mar0.130.130.120.110.120.130.110.110.12Apr0.120.130.120.120.140.130.120.120.14May0.130.150.120.120.160.130.130.120.16Jun0.130.120.130.130.160.120.130.110.16Jul0.130.130.110.130.140.110.110.10.13Aug0.130.130.130.130.120.110.110.10.13Sep0.110.130.140.140.140.110.110.110.13<br />Analysis of 2.2:<br />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.<br />Please reference chart 2.3 for all location dental conversion rate analysis:<br />Data Set<br />N1N2N3N4S1S2S3S4S5Jan0.590.520.630.60.440.440.420.50.53Feb0.560.490.60.580.460.480.450.510.55Mar0.460.530.560.550.450.440.370.50.53Apr0.540.540.610.50.430.440.410.50.49May0.530.530.580.540.540.430.430.480.48Jun0.470.460.530.540.550.440.370.490.45Jul0.580.510.570.530.550.450.420.480.38Aug0.510.510.540.530.570.470.390.490.43Sep0.460.510.580.550.580.450.450.580.48<br />Analysis of 2.3<br />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.<br />Please reference chart 2.4 for all location life conversion rate analysis:<br />Data Set:<br />monthN1N2N3N4S1S2S3S4S5Jan0.310.190.350.240.160.300.170.210.12Feb0.320.160.320.250.160.270.100.190.12Mar0.280.170.340.180.140.230.090.220.12Apr0.210.220.340.260.150.240.120.190.14May0.220.220.390.290.200.220.120.130.12Jun0.230.180.290.290.260.210.080.170.11Jul0.240.190.300.280.300.190.120.130.11Aug0.280.190.250.280.280.170.100.140.11Sep0.140.190.340.290.340.230.130.180.17<br />Analysis of 2.4: <br />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.<br />Please reference 2.5 for supplemental accident benefit (SAB) rider conversion: <br />Data Set<br />monthN1N2N3N4S1S2S3S4S5Jan0.280.190.180.150.130.060.070.100.04Feb0.300.360.200.440.170.060.070.150.06Mar0.620.510.680.580.230.220.160.450.28Apr0.580.620.730.590.470.280.350.570.46May0.790.660.730.690.640.390.530.600.53Jun0.870.660.670.730.630.350.380.600.51Jul0.820.500.710.690.600.430.440.640.51Aug0.880.550.730.790.610.440.360.690.51Sep0.820.580.780.780.640.560.480.710.62<br />Analysis of 2.5:  <br />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.  <br />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:<br />,[object Object]
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.
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.  <br />Please reference adjusted chart 2.6 for supplemental accident benefit (SAB) rider conversion analysis.<br />Data Set<br />N1N2N3N4S1S2S3S4S5Mar0.620.510.680.580.230.220.160.450.28Apr0.580.620.730.590.470.280.350.570.46May0.790.660.730.690.640.390.530.60.53Jun0.870.660.670.730.630.350.380.60.51Jul0.820.610.710.690.60.430.440.640.51Aug0.880.640.730.790.610.440.360.690.51Sep0.820.640.780.780.640.560.480.710.62<br />Analysis of 2.6:<br />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.  <br />Final analysis looking at both locations as the complete system<br />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.  <br />Looking at each location as its own system<br />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.<br />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.  <br />Please reference 3.1.1 and 3.1.2 for the issue rate side by side analysis in each location:<br />Analysis of 3.1.1 and 3.1.2:<br />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. <br />Please reference 3.2.1 and 3.2.2 for health conversion rate side by side analysis for each location:<br />  <br />Analysis of 3.2.1 and 3.2.2:<br /> 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.  <br />Please reference 3.3.1 and 3.3.2 for dental conversion rate side by side comparison each location:<br />Analysis of 3.3.1 and 3.3.2: <br />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.<br />Please reference 3.4.1 and 3.4.2 for life conversion rate side by side analysis for each location:  <br />Analysis of 3.4.1 and 3.4.2:<br />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.   <br />Please reference 3.6.1 and 3.6.2 for SAB conversion rate Side by Side analysis for each location: <br />Analysis of 3.6.1 and 3.6.2<br />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.<br />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.  <br />When comparing averages the North is converting SAB at 70% compared to South’s 48%, a 22% difference.  <br />Summary of between group variation analysis of performance metrics <br />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.   <br />For further analysis, within group variation (Supervisor to Supervisor) was needed.  <br />Within subgroup variation analysis of performance metrics (Supervisor to Supervisor) <br />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, 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:<br />Please reference 4.1 for dental conversion rate analysis by supervisor:<br />Data Set:<br />Jan FebMarAprMayJunJulAugSepN10.590.560.460.540.530.470.580.510.46N20.520.490.530.540.530.460.510.510.51N30.630.60.560.610.580.530.570.540.58N40.60.580.550.50.540.540.530.530.55S50.440.460.450.430.540.550.550.570.58S60.440.480.440.440.430.440.450.470.45S70.420.450.370.410.430.370.420.390.45S80.50.510.50.50.480.490.480.490.58S90.530.550.530.490.480.450.380.430.48<br />Analysis of 4.1<br />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.   <br />Please reference chart 4.2 for life conversion rate analysis by supervisor:<br />DatasetJanFebMarAprMayJunJulAugSepN10.310.320.280.210.220.230.240.280.14N20.190.160.170.220.220.180.190.190.19N30.350.320.340.340.390.290.300.250.34N40.240.250.180.260.290.290.280.280.29S50.160.160.140.150.200.260.300.280.34S60.300.270.230.240.220.210.190.170.23S70.170.100.090.120.120.080.120.100.13S80.210.190.220.190.130.170.130.140.18S90.120.120.120.140.120.110.110.110.17<br />Analysis of 4.2<br />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.<br />Please reference chart 4.3 for SAB conversion rate analysis by supervisor:<br />Data Set<br />MarAprMayJunJulAugSepN10.620.580.790.870.820.880.82N20.510.620.660.660.610.640.64N30.680.730.730.670.710.730.78N40.580.590.690.730.690.790.78S50.230.470.640.630.60.610.64S60.220.280.390.350.430.440.56S70.160.350.530.380.440.360.48S80.450.570.60.60.640.690.71S90.280.460.530.510.510.510.62<br />Analysis of 4.3 <br />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.<br />Summary of all Control Chart Analysis<br />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.  <br />Why is the South location not selling ancillary products as well as the North?<br />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.  <br />Please reference cause and effect diagram 5.1: <br /> Analysis and discussion of figure 5.1<br />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.  <br />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.  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.  <br />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. <br /> 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.     <br />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. <br />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.   <br />Short summary of modified training for new hires<br />The modified ancillary products sales training for new hires consisted of the below basic concepts:<br />Dental Insurance, Life Insurance and Supplemental Accident Benefit (SAB) are offered on every application, with no exception.<br />The offer should not be in the form of closed ended question.<br />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.<br />There is much discussion and the purpose and reasoning of each concept above; however, it is out of the scope of this paper.<br />Final analysis of ancillary product conversion performance<br />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. <br />,[object Object],Were two of the three ancillary products offered using modified training techniques<br />Was one of the three ancillary products offered using modified training techniques<br />Were all three offered not using new techniques<br />Were two of the three offered not using new techniques<br />Was one offered not using new techniques<br />Were none offered <br />The check sheets offered the following data:<br /> South Call Review  All 3 with newIIIII52 of 3 with newIIII 41 of 3 with newIIIIIIIII9All 3 not using newIIIIIIIIIIIIIIIIII182 of 3 not using newIIIIIIIIIIIII 131 of three not using newIIIIIIIIIIIIIIIIIIIIII22None offeredIIIIIIIIIIIIIIIIIIIIIIIIIIIII29 total100 North Call Review  All 3 with newIIIIIIIIIIIIIIIIIIIIIIIIIIIII292 of 3 with newIIIIIIIIIIIIIIIIIIIIIIIIIII 271 of 3 with newIIIIIIIIIIIIII14All 3 not using newIIIIIIII82 of 3 not using newIIIIII61 of three not using newIIIIIIIIII10None offeredIIIIII6 total100<br />Please see 7.1 and 7.2 for Pareto chart results:<br />Analysis of Pareto Charts 7.1 and 7.2<br />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.<br />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.  <br />Summary of all analysis<br />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. <br />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.<br />Final Recommendations<br />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:<br />,[object Object],Ancillary product sales training workshop for all North location representatives.<br />Ancillary product sales training workshop for all North Supervisors and Managers.<br />Ancillary product sales training workshop for all South locations representatives who have tenure of greater than 12 months.<br />Ancillary product sales training workshop for all North supervisors and managers.<br />
Using Quality Tools and Concepts to Improve Sales
Using Quality Tools and Concepts to Improve Sales
Using Quality Tools and Concepts to Improve Sales
Using Quality Tools and Concepts to Improve Sales
Using Quality Tools and Concepts to Improve Sales

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