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MN1105: Matrix enterprises design, manufactures, sell and support computer network: Quantitative Methods Assignment. UOL, UK
| University | University of London (UOL) |
| Subject | MN1105: Quantitative Methods |
Task 1: Performance Analysis of call centre agents
Matrix enterprises design, manufactures, sell and support computer network equipment. They have successfully entered the European market using UK as the headquarters. In the enterprise network market, it has a network of 40 distributors across UK, Germany, France and Spain, annually selling 10,000 network switches to business customers.
It has also built up a small business, home use market and is selling 500,000 SOHO routers and repeaters annually through retail and direct channels in the UK. In the retail channels(similar to Tesco, PC World), the first line support related to sales and return is managed by the retailers. Matrix provides support on technical issues. With the direct channels (similar to eBay, Amazon and own web shop), Matrix provides all the support to customer interactions.
You have been presented with a dataset containing information about the calls handled by call centre agents in one month. The call centre receives the call from customers who then either resolve them or divert to sales team or technical support. Each call has been allocated a specific Issue code and resolution code. The worksheet titled Glossary has further information
about the codes.
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a) Your task is to analyse the dataset and make interpretations on the performance of the call centre agents and develop a summary report to the management highlighting the conclusions you can draw from the analysis.
Data analysis should be undertaken by calculating the following statistic indicators (at least) for each agent based on the number of calls they handled.
- Mean
- Standard Error
- Median
- Mode
- Standard Deviation
- Sample Variance
- Kurtosis
- Skewness
- Range
- Minimum
- Maximum
- Sum
- Count
Apart from the above, pivot tables, histograms and other relevant charts should be used. Analysis of the data should help you to answer questions like…
1. Which call centre agent is the best and least performing and why do you think so?
2. Can we see any patterns/trends in the number of calls handled by the call centre? E.g. Easter
3. What can we understand from the contextual information such as type of calls, customer number, date, time etc?
4. Are there any problems / issues faced by the organization that can be identified? E.g. lot of queries around product failures?
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Answer
