Archive for the ‘Call Center Forecasting’ Category
Client-server architecture
Recently I decided to design my product using the client-server architecture. It was initially designed as standalone application for windows but will continue to grow as bigger application and I would like to have the uniform architecture. My main points for this decision are following:
- Main algorithm of the program is computationally intensive, i can imagine a dedicated machine that runs the server part for calculations (continuously for big problems) and one and multiple machines for viewing produced reports.
- Data storage and data integration. It is possibility to store all data in local database (local for server component) or store it in ACD database. With separate server component this can be more easily administered.
- It is better to separate the GUI from backed implementation from beginning. This can also permit better testing of separate components.
- Separate server and client component can permit different licensing schemes like releasing the GUI as open source or the components can be run on different operating systems (server on Linux and clients on Windows)
I am still in process of making decision on exact implementation details: communication protocol etc. It can be some custom or some existing protocol or in future to use web services integration. At the moment do not want too spend to much time on this. My goal is to release a functional version with minimum number of features (just the right number in order to get the call center forecasting done). I consider that initial feedback is important and releasing early is the way to understand better customer requirements.
Call Center Forecasting
I have started new research project to create accurate model for forecasting call volumes in call centers.
Generally speaking call centers are specialized offices for handling customers requesting assistance. They are often staffing from hundreds to thousands of agents. The call-volume forecasts drives staffing decisions. During the work hours volumes have high variance depending from different factors (promotions, events) and this make difficult to predict them. I plan to apply some newly developed techniques for statistical modeling in finance in hope to create good model for forecasting and implement it as commercial software. Initially it will perform only the “foresting” part but this can evolve in full featured work force management product.
My intentions are to post some research results and discuss call forecasting related problems on my new Call Center Forecasting blog page.
Tags: call center, call center analyst, call center research, call centre, contact center research, customer care, forecasting, work force management
