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Performance Appraisals Needs In The Call Center Industry

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Home Page > Business > Management > Performance Appraisals Needs In The Call Center Industry

Performance Appraisals Needs In The Call Center Industry

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Posted: Jun 19, 2008 |Comments: 0
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Encouragement is the key to performance. Reward is even greater source of encouragement when it’s beyond just words. Call centers have over the years developed a performance appraisal system that’s including all the components of good communication. Nowhere else does appraisals matter so much as much in call centre business, as its all about customer experience which sells and is at CSR discretion, he can make it most memorable or the worst at the same time.

Technology has turned the way in the favor of call centers and has reduced the hassle of managers and supervisors who had to listen to live calls to evaluate the performance of CSR, now with advanced software recording option; the calls can be replayed for evaluation of the quality and customer satisfaction.

A contact center should first offer quality training to the staff and then expect high performance appraisal, otherwise all the activity is useless. Whether you listen to live calls or recorded streaming, you should have well-defined standards for evaluation of scores and it should be pre-agreed with CSR, this way you can be in better position to motivate and advocate the CSR to improve his performance. Avoid such digital recording vendors who consider the length of call as a parameter of quality call, set your own professional parameters to evaluate the quality of call.

One of the best possible made evaluations models includes all the ingredients of good communication. The appraisals is made on the basis of one of the basic elements of good communication and it is expected from CSR to demonstrate these good practices to get good results towards the end for themselves and for the company.

The honesty level of the CSR can make real difference and in case the CSR is lagging short of words to depict his honest support, customer experience won’t me very appreciable. Next to honesty, performance is evaluated on the basis of the attention that CSR invest in his overall attendance. His reply will reflect his presence and if he is giving hundred percent, favorable comments will be added out of the overall experience. Interest level is also among the factors that are considered during performance evaluation.

Furthermore, duplication should be avoided and CSR should not ask anything twice, this creates really unpleasant impression on the caller. Refraining from making experienced based assumptions is really very important; otherwise the call will not be converted into prospect.

Sense of responsibility, control of CSR on the call, friendliness and professionalism are some other determinants of a quality customer service call on the part of CSR.

Many other factors need to be considered seriously when making call evaluation, other than just call handling and call quality. No one learns communication skills by birth and for the stuff that has not been able to enter main-stream careers, it’s even further a less realistic expectation. Training and skill development of s can yield considerable results towards the end.

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Article Tags:
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Analysis of Communication Networks: Call Centres, Traffic, and Performance

Product Description
This volume consists of the proceedings of the Workshop on Analysis and Simulation of Communication Networks held at The Fields Institute (Toronto). The workshop was divided into two main themes, entitled “Stability and Load Balancing of a Network of Call Centres” and “Traffic and Performance”. The call center industry is large and fast-growing. In order to provide top-notch customer service, it needs good mathematical models. The first part of the vo… More >>

Analysis of Communication Networks: Call Centres, Traffic, and Performance

Be the first to comment - What do you think? Posted by - October 30, 2010 at 9:00 am

Categories: Call Centers Tags: Analysis, call, centres, communication, Network's, performance, Traffic

Call Center Performance Management: 17 Fundamental Tried and Tested Formulas

We, here in this article will talk about how a simple inbound call center evolves into a multi dimensional outsourcing service provider and so does its performance management problem as well. With advanced technology and brightest minds, call centers expand and upgrade themselves to the next level of services and quality. But we need to understand that as call centers, their services and outsourcing trend have changed; their performance management techniques need to be changed as well. To determine the standards and quality of working, we are presenting 18 performance measures in terms of services, quality of work, efficiency and profitability of their services and impact of their support on a business and its growth.

We are analyzing these mentioned performance measures in two aspects of work levels: one for ordinary call center and another contact for multi level support provider contact center.

Performance Management in terms of Service

The most important measures of performance are those associated with service. Some of these measures are the same for both a Outsourced Call Center and contact center, while some will need to change slightly to reflect the new types of transactions.

1. Blocks and Hurdles

Blocks and hurdles are indicated as time when customers are not able to get through the network due to insufficient facilities at work. The busy signal, dropped calls and other situations can be count as such. These obstruct the speed of performance and have adverse affect on quality of services. Also, it has negative effect on customer satisfaction.
Solution: Increase the server capacity. To estimate how many network facilities to be needed by you so that it does not get overloaded.

2. Abandon Ratio

The dropped calls do impact the retention and revenue generation of call centers. They understand that making your customer wait in queue to receive a call is not going to take you anywhere. Nonetheless, it cannot be eliminated properly. There are number of factors that affect this factor such as caller’s patience, the time of call and other alternatives of getting in touch like email or dropping a number to call back.

3. Self-Service

Now, when market is expanding and customer base of organizations are growing, their partner call centers are adopting new measures to attend them. Most of them are adapting self-service facilities that help customers to choose their operations and help menu by themselves.
In a contact center, the performance can be tracked by observing how many times help menu was accessed and how many times a live agent was called upon?

4. Service Level

Service level consists of determining the most average speed of processing a request. Some of Call Center Outsourcing Services and contact centers measure the response time taken by the customers as well.

5. Maximum Delay in Queue

Another measure of speed is to calculate the longest time a customer was made to wait. This is also referred as worst case.

Quality Measures

6. First Resolution Rate

The first call resolution is called one and done in call centers which is very critical and significant for the performance levels of a call center. The factors contributing in this performance measure are the team that handled the query, time of call and nature of query.

7. Rate of Transfer

The seamless nature of a process of a call center can be determined by the rate of transfer. How much part of the work was handled over or transferred to another team or person, also counts.

8. Communications Skills

How well versed customer support executives are and how they behave with customer can either bog down your reputation or soar it above the clouds. This quality measure can be monitored through observance, reviewing the performance and proper reporting channels.

9. Procedures Adherence

This helps to integrate value and customer satisfaction together. Your agents should be willing to stick to workflow and shifting of process. Also, they should feel obliged to call scripts because they are trademark of your call center and brand awareness tactic for your client.

Efficiency Performance Measures

10. Agent Occupancy

Agent occupancy is the time that an agent takes to attend the customer as compared to the times he is not taking the calls. This is an important measure to check and oversee how your agents are utilizing the working hours.

11. Staff Attrition

It is the time when your staff is not present to handle the flow of calls. It could be due to meeting times, break times or other non productive issues. It is an important measure as you can easily calculate that how many people you will need in a session so that no call would go missed.

12. Efficiency of Schedule

It is about just hitting the mark. Not less and not more, just the right number of people working for you. Understaffing or overstaffing both is extremely dangerous curves for an organization.

13. Adherence to Schedule

This performance measure is a calculation of number of working hours per schedule. It ascertains the productivity of a team and its agents.

14. System Availability

An agent is incapable of doing anything if his system is slow. The overall performance of an agent can be marred by a slow system. For instance, IVR is much used and coveted technique of every call center. It eases down the workload of agents by 50 percent, in case IVR is not functioning properly, an agent would have to devote time to understand the nature of the query and answering it accordingly.

Profitability Measures

15. Rate of Conversion

The success of call center depends on the growth of organization they work for. How many of leads have been translated into sales, is the measure of their real success and actual performance.

16. Up-Selling and Cross-Selling

How much value has you agents added to your clients. This value added services adds as an advantage along with generated revenue in the kitty of your client.

17. Costing as per one Call

This is a critical and bottom line measure to calculate the efficiency and workload stamina of a call center. How much effort, facility, money and labor you have put in one call and what you are getting back out of it can be a real eye opener shot for any call center which boasts about success.

Be the first to comment - What do you think? Posted by - October 12, 2010 at 12:56 pm

Categories: Call Center Help Tags: call, center, Formulas, Fundamental, management, performance, Tested, tried

New BPM Partners Project Self-audit Tool Provides Fast Free Planning Support for Performance Management

New BPM Partners Project Self-audit Tool Provides Fast Free Planning Support for Performance Management
STAMFORD, CT–(Marketwire – 10/07/10) – BPM Partners, the leading independent authority on business performance management (BPM) solutions, today announced the addition of a free new self-audit tool, the Business Performance Management Project Self-audit (BPM PSA), to BPM Central, the company’s online resource center. The BPM PSA provides an assessment that can be used as part of internal …

Read more on Marketwire via Yahoo! Finance

Be the first to comment - What do you think? Posted by - October 7, 2010 at 12:16 pm

Categories: Call Center Systems Tags: fast, Free, management, Partners, performance, Planning, project, Provides, Selfaudit, support, Tool

Poor health habits linked to subpar work performance

Poor health habits linked to subpar work performance
TUESDAY, Sept. 28 (HealthDay News) — People who engage in unhealthy habits such as smoking, eating a poor diet and not getting enough exercise turn out to be less productive on the job, new Dutch research shows.

Employee Scheduling Software Improves Call Center Performance

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Call center managers know what it takes to run a successful call center and provide the best service for their customers. Unfortunately, many are not using employee scheduling software to eliminate inefficient manual systems. By automating key areas, such as forecasting call volumes and scheduling agents, call center managers can dramatically improve performance.

Employee Scheduling Software Lets You Automate Common Tasks

Employee scheduling software automates the entire agent scheduling process, enabling you to make better decisions in real-time. Your Excel spreadsheets will find their way to the bottom of the recycling bin when you implement an employee scheduling software solution.

Wouldn’t you like to:

Reduce overall costs by removing manual processes, accurately forecasting call volumes, and optimizing employee schedules from agent availability to skill levels to exception planning?

Improve productivity and customer satisfaction by consistently matching the right agents with the right skills to the right calls?

Use historical data to make faster and more informed forecasting and scheduling decisions?

Easily manage your employees across multiple centers and time zones?

Employee scheduling software enables you to do all of this and much more. And, since it’s Web-based, an automated workforce management solution is available anytime, anywhere, to give you complete control and the confidence that your call center is always operating at peak performance.

Employee Scheduling Software Improves Performance

Ultimately, a call center can be boiled down to one common factor: Performance. How well are we forecasting and scheduling? How well are employees performing? Are we meeting service levels? Are customers happy?

Employee scheduling software answers all of these questions. It provides better performance while also reducing costs. By streamlining tasks, leveraging easy-to-use tools, and generating plans for your call center’s long-term needs, employee scheduling software enables you to optimize your workforce at a fraction of the cost of traditional systems while also increasing profitability.

Use employee scheduling software to:

Significantly boost service levels

Improve both customer and employee satisfaction

Effortlessly manage and monitor schedules to use your agents more strategically

Precisely forecast average handling times, cost per call, agent utilization, first call resolution rate, and other key performance indicators

Employee scheduling software makes predicting performance possible. It gives you the power to transform a static call center into a dynamic center that relies on real-time data to streamline and comprehensively improve operations.

Be the first to comment - What do you think? Posted by - September 29, 2010 at 1:03 pm

Categories: Call Center Management Tags: call, center, Employee, improves, performance, scheduling, software

Analysis Of Performance In Contact Centre Using Qta

Analysis of Performance in Contact Centre Using QTA

Introduction

A centralized customer-service office that provides tele-services, where they answer incoming calls from customers via telephone contact for business organizations is called a contact centre or customer contact centre. Diverse range of businesses like large, medium and small organizations are establishing contact centre. Departmental stores, mail order catalogue firms, utility companies, insurance companies, airlines, banks, emergency road service operators and many others are linked with contact centre to get connected with their customers through telephones.

Customer enquiries regarding phone service billings, and the reporting of faulty services, ordering new features and benefits, changing customer profile and cancellation of services etc., in telecommunication service providers are done through contact centre. Staffing involves the major cost for a contact centre. The percentage of cost distributed in the contact centre is at the rate of 65 percent for staffing, 25 percent for networking and communication and remaining 10 percent for maintenance. Ongoing training programmes are often conducted by the contact centre due to more resignation of jobs which in turn increases the cost for the contact centre. This drastic resignation of jobs among employees is because of the poor contact centre management which increases the stress level of the employees. The quantitative model which is generally analytical helps to tackle the cost resulting from staffing levels. The standard queuing model is used to examine the quantitative aspect of the performance of a contact centre.

, The case of one of the Malaysian telecommunication service providers is taken in this study and the performance is evaluated and staffing level suggestions are given. In the past, the previous week’s call volume and pattern were used to measure the performance of the contact centre. But in this study, performance of the contact centre and staff planning is evaluated using scientific approach. Performance of the contact centre is investigated in the context of the Erlang C model (classical M/M/s model) and Erlang A model (extended M/M/s + M model) and the results are compared. Service quality is another aspect of performance, service quality goal of the contact centre is to answer 80 percent of the incoming calls without making the customers wait for more than 20 seconds) i.e. known as the 80/20 rule.

Telecommunication Service Provider’s Contact Centre

The contact centre operates 7 days a week, 24 hours a day and handles inbound and outbound calls, faxes, e-services and mail. Since two-third of the calls handled is incoming calls, this study is limited to incoming calls from the post paid customers through telephone without considering Interactive Voice Response (IVR).

The three stages of the incoming calls are,

Interactive Voice Response (IVR)

Queue stage and

Service stage.

Some calls directly move to service stage skipping the queue stage. The customer call is first connected to the Interactive Voice Response (also called Voice Response Unit or VRU) which enables the customer to complete the self-service transactions. Self-service transaction means asking the customer to press five in the telephone keypad for balance enquiry. The customer may end the call if he/she doesn’t want to speak to an agent or a Customer Service Representative (CSR). To talk with the agent the customer may be asked to press a specified number and the customer gets connected to the agent immediately or joins the tele queue till the agent is available. The call is recorded as received when it exits IVR and joins the tele queue. Some impatient callers leave the queue abruptly and they are categorized as abandonment calls. The calls that reach the agent and served are reported as answered. The tele queues are normally served on the first come first served (FCFS) basis. The contact centre by-pass few calls directly to the next available agent. They are categorized as priority customers. For example, the customers who spend more than RM 500 per month are priority customers.

Performance Models Results

a) Erlang C or M/M/s

In this study, Erlang C or M/M/s queuing model is used to analyze the performance of the contact centre. Erlang C or M/M/s model assumes Poisson arrival and exponential service time. The contact centre has a total of 60 customer service agents called servers and receives a total of 954 calls in an hour at the rate of 15.9 calls per minute and a service rate of 16.2 calls per hours. Since the queue capacity and the population are infinite, the customers are served on first come first served (FCFS) basis. To prevent the queue from

growing indefinitely, the utilization factor should be below 1. The contact centre with 60 servers has 0.981 utilization factor (?). The fraction of time each server is busy in a queuing system is calculated by the utilization factor.

Erlang C model measures the performance indicator of the contact centre using Queuing Toolpak 4.0. The effect of the different number of servers on the performance indicators is analyzed first since the main objective is to equip the contact centre with the right number of servers.

When the number of servers is 59 the contact centre will be operating at full capacity because the utilization factor is found to be 1. Performance indicators were not available when the contact centre uses servers below 59, stating that the system is not stable. The relationship between the utilization factor and the number of servers is negative linear in nature. Increase in the number of servers decreases the utilization factor. This relaxes the contact centre environment by reducing the workload.

The relationship between the utilization factor and average time in queue (queue in seconds) are examined next. The waiting time for a call remains close to 0 seconds until the utilization of capacity reaches 80 percent; beyond 80 percent, the waiting time in queue increases rapidly. This can be tackled in three ways,

1. Number of servers can be increased.

2. Time spent in each can be reduced or

3. Number of calls arriving at the contact centre can be controlled.

Negative relationship is found between the number of servers and the probability of an arriving call that has to wait to be served. Probability is 0 of having to wait to be served when the number of servers in the contact centre is 80. In other words, no calls wait in queue when the number of servers in the contact centre is 81. Different number of servers leaves different impact on the service provided. In the beginning, performance indicator increases when the number of server’s increases, but after reaching an optimal point, the impact of the additional servers reduces tremendously. The service time, which is the amount of time spent on each call and the server utilization rate influences the service rate of the contact centre. Calculating the number of servers required for various service times is very important because service time varies according to the complexity of the calls received. This can be calculated using Erlang C or M/M/s queuing model for service time ranging from 120 seconds to 360 seconds. When the agent utilization rate is low, more servers are required for the same amount of service time. For example, while 136 servers and 70 percent agent utilization are required for answering the call which takes 6 minutes, 106 servers is required for 90 percent agent utilization; the difference between 70 and 90 percent is 30 servers. This indicates the weakness of the contact centre; the contact centre operates with 60 servers by utilizing the full capacity leaving a lot of room for improvement in the level of service provided to customers.

b) M/M/s + M or Erlang A model

Here, M/M/s + M or Erlang A model is used to evaluate the performance indicator of the contact centre. Abandonment factor is included in this model. Average wait in queue in seconds is calculated by the percentage of abandonment calls. This helps to derive the average caller’s patience (ACP). Average caller’s patience is represented by the symbol

(?-1). On Monday, 7th February 2005, 21 percent of total calls received are abandoned during 11 am to 12 noon and average wait in queue at the contact centre is 32.4 seconds. Based on this, ACP is assumed to be exponential distribution and ACP at the contact centre is 154.28 seconds or 2 minutes and 34 seconds. Thus, in addition to Poisson arrival and exponential service time M/M/s + M or Erlang A model assumes exponentially distributed patience time.

For example, the average caller’s patience is 2 minutes and 34 seconds when the number of servers is 60, the arrival rate is 954 calls per hour and the average service time equals 3 minutes and 42 seconds. Abandonment feature is not available in queuing toolpak 4.0, so, the 4callcenters version 2.23 is used to measure the performance indicator of the contact centre. Linear relationship is found between the percentage of abandoned calls and average time in the queue in seconds for calls arriving at the contact centre. Percentage of abandonment calls increases when the average waiting time increases.

Average time in the queue is 123 seconds and 80 percent of the calls will be abandoned when the server equals 12. From the report of 4callcenters it was gathered that performance indicators were not made available and that the contact centre was tremendously overloaded, when the servers were reduced below 12. Violation of the assumption that the utilization rate is below 1 is the important factor to note in this model.

Negative exponential relationship is found between the number of servers and the number of abandoned calls. The relationship between the following parameters of percentage of abandoned calls, percentage of answered calls, percentage of utilization and varying number of servers is tested. Percentage of abandoned calls decreases until it reaches 0 when the number of servers is increase and after 71 it remains at 0. In response to the increase in the number of servers, the percentage of calls answered increases steadily. The percentage of calls answered remains at 100 percent at 71 servers and onwards. According to this, all the calls are answered if the contact centre starts using 71 servers.

M/M/s (Erlang C) and M/M/s + M model (Erlang A) Comparisons

Shorter waiting time and shorter queue is produced by Erlang A and lower utilization rate is enjoyed by the agents. The main objective of the contact centre is to answer 80 percent of the incoming calls within 20 seconds. It is found in Erlang C that 64 servers were required to answer the incoming calls within 20 seconds on average. In Erlang C, only with 65 servers, we can achieve the goal of contact centre i.e. answering 80 percent of the incoming calls within 20 seconds. Erlang A requires only 53 servers to reduce the time in queue to 20 seconds and below. To achieve 80/20 Erlang A requires 60 servers which is less than Erlang C. When comparing to achieve both the objective of 80/20 and 80 percent agent utilization rate at least 73 servers are used in Erlang A model when compared to 74 in the Erlang C model.

Erlang C requires more server than Erlang A to achieve the goal of the contact centre i.e. answering all the incoming calls within 20 seconds. Over staffing is required in the model which ignores abandonment factor and under staffing is required in the models which include the abandonment factor. Table 4 confirms the above statement. Agent utilization plays an important role in influencing the number of servers required, even while taking the abandonment factor into consideration and while comparing, there is only a very small difference in number of servers required.

Erlang C does not take the abandonment rate into consideration, so abandonment rate is unique to Erlang A. Erlang A seems to be stable at all times(except when below 12 servers are used) but Erlang C becomes unstable when the utilization factor hits 100 percent and more. The agent’s occupancy rate decreases for both the models when the number of servers increases, to achieve certain level of agent occupancy; number of servers required differs for both the models. For example Erlang A needs 65 servers and Erlang C requires 67 servers to achieve 90 of agent occupancy. Adding 2 or 3 servers in Erlang C model would result in Erlang A, since in operating contact centers personnel cost are the major operational costs.

Conclusion

In this study, we built a queuing model to measure the performance of one of Malaysia’s leading telecommunication service provider to assist its staffing levels, to achieve progress in service quality while keeping costs down. The data used to build a performance model in the context of two models i.e. the Erlang C and the Erlang A are the data collected in the contact centre between 11 am to 12 pm on Monday, 7th February 2005. Erlang C model shows the result that with the current number of 60 servers is not performing the standard required. Only 24 percent calls are answered within 20 seconds but the goal is to achieve 80 percent of the calls within 20 seconds. The average number of calls in the queue was 44 and 2 minutes and 44 seconds are spent by each calls waiting in the queue. To improve the service to the required standard of 80/20, 65 servers are needed in Erlang C model in which abandonment factor is also not included, this leads to under or over staffing resulting in economical consequences.

Thus, Erlang A model including the abandonment factor is used to measure the performance of the contact centre. Average caller’s patience (? ?1) is the addition parameter in Erlang A model. Compared to Erlang C, Erlang A performs better with 60 servers. The average time in queue (7.27) is also quicker, the queue is shorter (1.9 calls), and the agent utilization rate is lower in Erlang A model. Arrival rate, service rate and number of servers are widely explained and the inter-relationship between them is analyzed in this study. Overstaffing of 5 servers to achieve the goal of the contact centre is indicated by the Erlang C model. The conclusion is limited to peak hour of Monday since the data collected is in the peak hour between 11am to 12pm on a Monday. In future the contact centre may go for the changes mentioned below.

The mean service rate which is currently at 16.2 customers per hour can be increased by creative design change with the application of technology.

The callers to have a clear idea of the purpose of the call and to enable the servers more questions can be added in IVR, this enables the servers to focus on the problem solving rather than spending time on understanding the problem.

Number of arrivals can be reduced.

To encourage the callers to call after office hours, off-peak hour promotions activities can be taken by the contact centre, but this should not increase the cost and it should improve customer satisfaction.

To thus reduce the burden on the customer service representatives, more customers can be encouraged to use the IVR.

Last, but not the least, employing a team of analyst to mange the ample data available in the contact centre to reap the benefit from this data is very important

Be the first to comment - What do you think? Posted by - September 11, 2010 at 9:01 am

Categories: Call Centers Tags: Analysis, centre, Contact, performance, using

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Posts Tagged ‘performance’

Performance Appraisals Needs In The Call Center Industry

Analysis of Communication Networks: Call Centres, Traffic, and Performance

Call Center Performance Management: 17 Fundamental Tried and Tested Formulas

New BPM Partners Project Self-audit Tool Provides Fast Free Planning Support for Performance Management

Poor health habits linked to subpar work performance

Employee Scheduling Software Improves Call Center Performance

Analysis Of Performance In Contact Centre Using Qta

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