Lookup NU author(s): Dr Shirley Coleman
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Villa Soft Drinks Ltd, established in 1884, manufactures and bottles spring waters and carbonates for both the growing adult soft drinks market and the more traditional soft drinks market. The company employs just over 100 people split between the manufacturing site in Sunderland and the head office and distribution centre in Washington. One of the fundamental problems affecting the day-to-day running of Villa, and most companies, is communication. There is a lack of awareness of the impact that changes in one department have an other departments (e.g. if production efficiency is increased by 10%, what impact will this have on warehousing?). Villa had recently identified key performance indicators (KPIs) to monitor all aspects of manufacturing performance on a regular basis. This enabled the current production situation to be evaluated and helped familiarize staff with charts and measurements. The use of Pareto analysis and problem solving techniques helped to boost efficiency and utilization. Key performance indicators were then developed in most other departments and are monitored and displayed regularly The KPIs can be used further to improve transparency across the company by incorporating them in an interactive, interpretative tool to aid communication and understanding at all levels of the company, Individual departmental flow diagrams will be linked together to represent how the company operates. The diagrams will include both material flow and information flow. These data will then be organized in a software package and the end result will be a fully integrated simulation of the company in which any variable can be altered to demonstrate the effect this has on other departments and therefore the company as a whole. This will be an extremely valuable tool for the company as it will have many different applications, such as calculating manning requirements, identifying potential cycle time reductions and optimizing warehouse space.
Author(s): Bruce D, Coleman SY
Publication type: Article
Publication status: Published
Journal: Journal of Applied Statistics
Print publication date: 02/08/2010
ISSN (print): 0266-4763
ISSN (electronic): 1360-0532
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