A distribution chain mobile application for Movit Products Limited.
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This study is about our final year Information Systems project that focused on developing a distribution chain mobile application for Movit Products Limited .This was based on the fact that there were difficulties in duty collection, demand projection discrepancies that made it difficult to estimate the quantity to supply, restricted entry of new smaller customers since there locations were unknown and their demand too could not be projected therefore need for an automated system to improve on the drawbacks in the current system. The main objective of the study was to develop a distribution chain mobile application in order to reduce on the many drawbacks in the current manual system. In order to achieve the above objective, a number of data collection methods were used to collect requirements of the system and they included questionnaires and observations. Data Flow Diagrams and Entity Relationship Diagrams were used to carry out system analysis and design. The distribution chain mobile application was developed that allows large orders to be made to Movit by its customers, we recommended that Movit Products Limited adopts this automated distribution chain system to ensure efficient ordering and delivery of products and also demand forecasting. Testing of the application was done using ionic labs Android emulator and android devices. The distribution chain mobile application was implemented using the based on the IONIC V3 framework that uses the following front-end technologies like HTML, SCSS, Type Script and the back-end technologies were MSQL and PHP. The Validation of the application catered for inputs that are entered by the user, stores it, processes tasks and outputs result to the both customers and Movit Products Limited. It is secure in that the users must first register with the application such that no fake orders can be made. In conclusion, Movit Products Limited should take advantage of using the system for easy handling customer orders and demand forecasting.