Smart Product Advisor Rules Engine Reduces Maintenance Efforts By 38%

The Challenge

The client is a Fortune 500 manufacturing and technology company with a range of products and services in process management, climate technologies, network power, storage solutions, professional tools, and more. The client wanted to develop a self-service-based product advisor through which their customers could select and configure products for purchase. The previous process was time-intensive and required considerable collaboration between customers and sales representatives. Yet, this back-and-forth was deemed necessary as customers were hesitant to select the best-fit products on their own. Given the variety in the catalog, most customers preferred reaching out to the client’s sales representatives to find best-fit products that matched their requirements.

The product selection process was rigorous, involving complex rules, calculations, and iterations before customers could pick the most suitable products. Digitization of this process required a deep understanding of the complete user process, necessitating business users to spend hours with the technical team. In addition, testing the rules was complex as it impacted existing systems.

The Solution

Rather than head down the route of a laborious and costly technology solution, SLK developed a no-code/low code framework that ran server-side business rules. This gave the client the freedom to build complex rules using a simple drag-and-drop flow chart editor without needing a single line of code. The Rule Engine supported a variety of rules, including basic ones, excel formulas, mathematical formulas using Latex format, database rules, and more. The client could update the rules as required, rather than having to scout for a developer or an ongoing maintenance expense. This also ensured that business users could create rules on the fly without waiting months for the technology solution to be tweaked.

The Rule Engine also enabled testing of the rules independent of any application. By passing data through APIs instead of a full-fledged integration, the client could ensure the rules worked as they should before inserting them into the customer process.