Case Study
A new CVR system for AECI Much Asphalt
We’ve been working with AECI Much Asphalt for a few years now – maintaining their business software. It was only six months ago that they came to us with a proposal for a new CVR system. Up until this point, the multi-national asphalt experts had been using a manual spreadsheet system, which was becoming unwieldy as the company expanded.
AECI Much Asphalt is still based in South Africa, but it operates across Africa, Europe, South East Asia, North America and Australia. They’re a product and service supplier to a wide range of industries, including mining, infrastructure, water treatment and more. Using a manual system was no longer viable.
The challenge of scoping the CVR system
One of the biggest challenges that we faced when scoping out the new CVR system was getting to grips with how the company’s current spreadsheet system worked. They used a series of complex calculations where one field could be linked to many other sections of the statistics and could be used in additional calculations. Often, these calculations were interdependent, creating a scenario where one input could affect many different calculations that could only be completed once other fields relying on other inputs were completed, resulting in an almost infinite loop.
It took some time, but once the full trail of calculations was mapped, we were able to develop the CVR system fairly quickly. After six months, the system went live and AECI Much Asphalt began the process of migrating from their manual system.
The future of our partnership with AECI Much Asphalt
The development of the CVR system has only strengthened our relationship with AECI Much Asphalt. We’ve been maintaining their Windows-based software for several years, but the company has found that having software installed on each device in the company is slowing them down. Our next project together is a full system rewrite to convert their current software into a fully web-based application. That’s sure to be a highly interesting case study in the future.
- Advanced reporting tools: Various powerful reporting tools provide valuable insights into student performance and progress.
Thanks to the iterative development approach, we know that each enhancement we add to the system will get the opportunity to be tested thoroughly before going live. W&RSETA can also continue to operate seamlessly as we work on new areas of the solution. Coming up, we’ll be integrating a machine learning tool (AI). This will allow the system to predict student success and improve decision making in the bursary selection process.
