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Using AI-infused process intelligence to optimize a global sales incentive program
IBM Process Mining + IBM watsonx Assistant
The IBM Global Sales Incentives (GSI) team is responsible for helping the IBM global sales team achieve strategic business results aligned to IBM’s growth strategy. To support this mission, the GSI team provides an incentives program that is personalized to each seller. One component of the program’s digital experience is AskIncentives, a chatbot powered by IBM® watsonx™ Assistant that answers incentive-related questions.
Sellers, sale managers and executives use AskIncentives to get answers to questions on incentives, commissions, and sales plays. They also use it to clarify sales target information. In a typical year, the bot receives tens of thousands of questions. In the year 2021, for example, it received over 278,000 questions, while in the year 2022 it received over 340,000 questions. In the years 2021 and 2022, it was able to answer 92% and 93% of these questions respectively. When the bot could not answer a question, an inquiry was submitted to the GSI team and manually reviewed by an incentive analyst. Unfortunately, the review process that followed an escalation like this could take quite a bit of time. The extended time it took to close inquiries caused some frustration among the sellers.
As a result, the GSI team decided to implement the IBM Process Mining solution and optimize the inquiry process. It also sought to utilize the data analyzed by Process Mining to expand the AskIncentives chatbot’s capabilities, thereby offering a more personalized experience to sellers and achieving a higher answer rate. The team’s goal was to enable the bot to answer more questions, thus ensuring that only the genuinely complex questions would need to be reviewed by an incentive analyst.
The GSI team partnered with the Software Elite and Enterprise Operations and Services digital strategy teams at IBM to identify critical areas to prioritize during the transformation. Three focus areas emerged:
- Understand—based on performance data—how long it actually takes the GSI team to close an inquiry that has been assigned to an incentive analyst.
- Conduct a holistic evaluation of the inquiry process workflow to improve efficiency and increase end-user satisfaction.
- Develop a better understanding of the type of questions sellers typically submit to AskIncentives and use this to finetune the bot.
Over the course of three months, the teams used Process Mining’s specialized data mining algorithms to identify trends, patterns and details contained in history logs recorded by the AskIncentives bot and the GSI team’s inquiry tracking tool. The solution provided meaningful insights and visualizations, while delivering strategic recommendations, such as:
- The average time taken to close the inquiry was significantly higher than the current service level agreement (SLA) of five days, in some cases it was over double that.
- 28% of inquiries went into hold status.
- There were too many root cause categories sellers could choose from when submitting an inquiry. The broad range of options led to incorrect categorization which prolonged the resolution timeline.
Creating an experience that better supports sellers
Using the data and the insights collected by Process Mining, the GSI team expanded the capabilities of the AskIncentives chatbot and began delivering a better experience to sellers. The team implemented multiple enhancements to the bot which included:
- Adding new content to the knowledge base the bot uses to generate answers, so that the bot can answer a wider range of questions.
- Consolidating the number of root cause categories, in order to streamline root cause analysis and inquiry routing.
- Revising the process for assigning tickets to each incentive analyst, in order to drive faster inquiry resolution times.
- Designing to bot to provide personalized profile data, such as measurements, territory, quota, last payment, and achievement, right when users start interacting with it.
Once these enhancements were implemented, the team observed the following outcomes:
- 82.5% improvement in the time required to resolve a query. The average of the monthly average time to resolve an inquiry in the 12 months before the rollout was 9.78 days. The average of the monthly average in the 12 months that followed was 1.71 days.
- In the first 9 months following the process enhancements being rolled out, from January to September 2023, the AskIncentives chatbot answered 96% of the 326,525 questions it received.
As they reflect on the process improvements and the positive feedback from sellers resulting from the Process Mining implementation, the GSI team aims to direct their focus to generative AI (genAI) going forward. In the months to come, they plan to test new ways to answer more complex questions and potentially offer an even more personalized end-user experience to the sellers using IBM watsonx and IBM Watson Discovery.
The IBM Global Sales Incentives (GSI) team is responsible for motivating sellers to deliver revenue and business results aligned to IBM strategy. To improve results, the team provides the best in class digitized and personal end-to-end incentives experience augmented by an intelligent workflow.
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Produced in the United States of America. January 2024.
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