Client
Our client is an Australian-owned pork processing and distribution business operating for over 25 years. Our client provides premium pork products to their customers across New South Wales and Queensland.
Purpose
Our client relied on a set of Excel files combined with email-extracted RTF files (word document) as the base to manage their operational data. This system has potential issues of:
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The Excel files are not working as intended, e.g. some buttons are no longer functioning
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Execution of calculation is not user-friendly: e.g. user needs to execute calculation under Developer mode
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Increased complexity: with the growth of the business, the logic implemented in Excel has become more complicated and difficult to maintain
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Key-person Risk: only a few staff know how to maintain the Excel files
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Human Error Risk: there is a lot of manual manipulation and pasting of data from different sources
Client management would like to retire the current Excel system and is looking for a solution that can manage the operation data in a robust and reliable tool.
Approach
Forecast proposed an Online Operating Information System to replace the existing Excel-based system. The solution adopted the typical 3 layers architecture with front, application and database. Some highlights of our approach are:
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Adapted Amazon Amplify framework for quick frontend development
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Applied Object-relational mapping (ORM) design pattern
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Serverless backend architecture
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Agile delivery
Forecast works closely with the client to understand their existing operation process and then took a user-centric agile delivery approach to lift the current Excel-based system into an eCommerce-ready online tool.
Outcome
The project is planned to be carried out in several phases. The first phase is to replicate the current Excel-based operation system. The client is satisfied with the outcome of the first phase. The online Operating Information System provides a more robust and reliable way to manage key operational information. It paved way for the next phases to allow optimisation of the process.