Robotic-led Quotation Generation Process for a global IT and Communication Service Provider
About Client
Our client is a leading global IT and Communication Service Provider that provides range of fixed telephony, data transmission, unified communication, and other value-added services to consumers, businesses, and other telecommunications operators worldwide. With worldwide experts, best-of-breed partners and open-source integration the company is also enabling digital business transformation both effective and affordable for global enterprises.
Challenge
Annually the client processed very high no of quotation request manually. The operations team received these requests and then process it in scanned PDF format in the admin system application. This led to long/inaccurate quoting times and manual effort especially with multinational locations, complicated pricing schemes and dispersed data. The team doing these processes experienced a high-level of frustration due to the repetitive nature of the task and the need to replicate their efforts across multiple applications.
Our Solution
PureSoftware RPA team aims to revolutionize the way business interacts, communicates and engages with customers. The team deployed viable quotation bot (Q-BOT) that performed the validation of each business rule across multiple data points and the results were presented to the team (Validation activity for quotation process were embedded as business rules in the bot). It communicated with pricing engine, product map and client engagement system to ensure highest level of customer experience. Further, the information received is clubbed into PDF based on the standard template. Thus, client was successful in delivering fast and error-free quotation response.
Benefits
Reduced cycle time by 70% as processing load was shifted to bot that delivers quicker
Reduction in processing time: Automated system saved 10 minutes per quote
Savings of 5000 min a day and around 21000 hours in a year
Cost saving of $600K per year due to significant reduction in manual effort and team size
