Discovering the most efficient way to automate your business processes can be a daunting task. However, with IBM Business Automation, you can take the first step towards streamlining your operations. By combining process mining, robotic process automation, core automation, and AI, IBM Business Automation can help your organization reduce costs, minimize inefficiencies, and ultimately, enhance customer satisfaction. In this blog, we will explore the power of IBM Business Automation by taking a deep dive into a refund approval scenario. In the current process, all refund requests are handled manually, leading to delays, human error, and poor customer service. By leveraging automation, the aim is to achieve an 80% straight-through processing workflow, minimizing the need for human intervention, and maximizing efficiency. So, let’s explore how IBM Business Automation can transform your business and take your operations to the next level.
Let’s delve deeper into the current refund approval process. When a customer realizes their order has not been delivered several days after the expected delivery date, they fill out an online form to request a refund. This request then lands in a general “customer support” inbox where a person reviews it, determines its priority, and manually enters data into the correct systems. The request is then routed to the appropriate team for further processing.
A decision service then evaluates the refund request based on factors such as timeframe, loyalty status, and amount. The evaluation determines the flow of the request through various people and systems, which can be inconsistent based on the individuals involved. In some cases, additional documentation, such as a copy of the invoice, may also be required.
If the refund request is approved, the information is manually entered into the billing system before the refund can be issued. An email is then manually composed and sent to the customer to notify them of the approval, before the request is finally closed off.
Overall, this manual process can take an average of 7days to complete, and it often results in time delays, inconsistent decision-making, and an increased likelihood of errors. These issues can lead to a negative impact on customer satisfaction levels, which may ultimately affect the business’s bottom line.
To achieve the goal of 80% straight-through processing for refund requests, we will need to explore different business automation solutions that can be applied to the current process. These solutions can help us digitize and automate the refund approval workflow, reducing inefficiencies and delays caused by manual processes. In this section, we will discuss some of the automation tools and technologies that can be used, such as robotic process automation, document processing, intelligent
chatbots, predictive decisions. By leveraging these automation solutions, we can streamline the refund approval process, increase efficiency, and ultimately provide a better customer experience.
Implementing Robotic Process Automation (RPA)
Implementing Robotic Process Automation (RPA) is a powerful solution to automate routine human tasks and achieve significant benefits without the need for IT involvement. RPA bots can be used to automate repetitive tasks, reduce cycle time, and eliminate copy-and-paste and data-entry errors, ultimately reducing rework and delays. By adding RPA bots for accounting and customer support, businesses can achieve even greater efficiency and accuracy in their processes.
For instance, in our Refund Approvals Scenario, RPA bots can automate the entering of data into the billing system (in accounting) and select and fill out emails by template for customer support. These bots can complete previously manual tasks in mere seconds, drastically reducing the processing time from request to refund.
With the implementation of RPA bots, businesses can improve straight-through processing by up to 30% and reduce the average processing time from 7 days to 4.
Adding Content Analysis
By incorporating content analysis, we can capture, classify, and extract data from documents to speed up data extraction and minimize data entry errors.
In this scenario, a new document processing system is added to automatically process incoming documents, such as invoices attached to customer refund requests. Previously, the company had difficulty automating this step due to various invoice formats acquired through acquisition. However, the new system can classify different invoice layouts and extract required data using machine learning. As the system learns over time, it can understand and recognize new labels and fields.
By automatically capturing invoice data for refund requests that haven an attached invoice , the system can improve straight-through processing from 30% to 50% and reduce average processing time from 4 days to 3.
Building Intelligent Chatbots
To further improve customer service, the company can implement an intelligent refund chatbot with built-in natural language processing and AI. Unlike typical chatbots, this chatbot is highly targeted and uses a conversational style to gather specific data needed for business operations and perform specific automated interactions. The chatbot is trained using a knowledge base and can understand customer input, score confidence levels for each intent, and learn over time.
In our scenario, the chatbot would be used to discover information pertaining to the refund. The chatbot would also use native RPA commands to query the company’s systems during conversations, validate and gather the required data, and create the refund request in the workflow system. This eliminates the need for manual data entry and improves accuracy.
By providing real-time automated assistance to customers who have questions or need help, the company can improve straight-through processing from 50% to 60% and reduce the average processing time from 3 days to 2.
Maximizing Decision Automation
Finally, the company can fully automate additional decision types. By combining decision services with machine learning-based predictive analytics for the customer’s propensity to churn and future lifetime revenue, the company can adjust refund decisions to be more tailored while providing better and faster customer service. This approach increases the consistency and auditability of decisions for improved reliability and allows the company to rapidly adapt to changing business conditions. Additionally, the integration of predictive analytics amplifies the value of traditional business rules. With this strategy, the company can achieve its goal of 80% straight-through processing, reducing the average time from request to refund to less than a day.
In conclusion, by implementing IBM Business Automation, businesses can streamline their operations and achieve greater efficiency, accuracy, and customer satisfaction. By automating the refund approval process, businesses can reduce costs, minimize inefficiencies, and provide a better customer experience. In the refund approval scenario we explored, the combination of RPA, document processing, intelligent chatbots, and predictive decisions enabled the company to achieve an 80% straight-through processing workflow, significantly reducing the need for human intervention and maximizing efficiency. As businesses face increasing pressure to optimize their operations, IBM Business Automation offers a powerful solution to stay competitive and meet customer demands.
Find out more about IBM Business Automation on our “Monthly Solution Spotlight” page www.DataSkill.com/spotlight