Innovation • 18 Nov 2020

Intelligent RPA use-case: Customer Service

Enhance the customer complaints process to avoid unnecessary compensation payments and penalties

For one of our customers active in FMCG, we optimized the process to handle complaints they received from their customers (retailers). Why? The retailers add new complaints about deliveries, stock levels, product issues,... in a specific retailer portal. As this portal is not integrated into the SAP system of our customer, it was a very daunting and time-consuming task to verify each specific complaint. The customer service employees needed to check multiple systems to look up the required data and compare it to the actual complaint details. Additionally, there is a time limitation to review the complaints. After a specific period of time, a compensation or penalty should be paid.

Challenge:

  • Large amount of penalties
  • Multiple systems: customer adds penalties in own portal
  • Time limitation to review the complaints
  • Key users should be notified of the result
  • Evaluation needs to be updated in the customer portal
  • Expensive process to have employees do the time-consuming verifications

Intelligent RPA solution:

  • Reduction in cycle time
  • Bot updates penalties in the customer portal based on analyzed penalties 
  • Increase in compliance
  • Decrease in overall costs
  • Increase in service quality

Result:

In the past, our customer used to pay the penalties in most cases as it was cheaper than let people execute this verification process manually, of course, this was far from an ideal solution.

That's where the ROI of an Intelligent RPA solution comes in! By enhancing this process and letting the IRPA bots run 24/7, all complaints are checked on time resulting in a correct complaint follow-up. This is a huge win-win: a big increase in compliance, a big decrease in overall costs.

A time-consuming, error-prone task is now fully automated and verifications are executed on time. This has a major positive impact on service quality. 

Time to market:
6 bots x 3 weeks

Time-saving:
> 300 days/year

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CS department