Marlon Dumas, co-founder and chief product officer of Apromore, delivered his company’s perspective and answers to the top 5 process mining buyer questions for the Process Mining Battleground taking place on July 31.
Dumas touched on the value of process mining in customer-focused processes, the urgency to deliver time to value, the company’s no-code platform, and, finally, how artificial intelligence (AI) and generative AI play into the company’s product plans.
Below are highlights of his discussion with Aaron Back:
Prevalent Customer Use Cases and Industries
01:17 — “We innovate in the direction of customer-facing processes,” Dumas explains. It’s not specific to one industry; it’s across many industries. Dumas shares examples from banking, insurance, and utilities.
02:40 — Apromore enhances customer-facing processes by improving how it manages touchpoints through AI to identify which areas are causing friction for customers.
03:11 — By reducing touchpoints from the customer service perspective, it helps deliver the outcome of a satisfied customer.
How Apromore Supports Shifting Priorities and Macroeconomic Conditions
04:41 — Dumas says that a key theme, and customer priority, in 2023 is time to value. “It’s about being able to bring value out of analytics in general and process mining in particular in a matter of weeks, not months,” he says.
05:02 — How does Apromore enable a business team to identify friction in its customer touchpoints? For well over 10 years, the company has invested in no-code process mining. “Being able to have a fully point-and-click interface that allows business users themselves to do the process mining analysis, to identify improvement opportunities” has been a focal point of Apromore.
06:48 — Process mining brings the self-service aspect to the table for business teams. Dumas considers this element part of the definition of process mining.
07:42 — From the start, the no-code foundation has been its greatest differentiator. “Whatever we offer is packaged in a way that can be used by business users, by business teams themselves,” Dumas explains.
08:06 — Apromore teams test the technology themselves to be able to train business users in 12 hours. They use AI techniques to continue improving the tools.
08:35 — By integrating AI into its tools, Apromore enables business users to identify problems themselves. “We really get measured by the ‘aha moments’ that our business users are having.” With more “aha moments,” the company is able to see which touchpoints are and aren’t working, and how much value it’s delivering.
09:00 — Another major differentiator is that Apromore not only uses data to look at the past but also to drive change. The company has invested in digital process twin technology to build detailed simulation models to better understand the business user experience and make adjustments accordingly.
10:30 — Another major differentiator is its big investment in AI-driven predictive process monitoring. This involves using data from the past to train machine learning models that are used by operations managers to make decisions and gain better insight.
Making It Easier to Adopt Process Mining
12:00 — During the pandemic, Apromore re-architected its product and rebuilt it on Elastic MapReduce. This enabled the company to be in the cloud and scale instantly. Now, customers can grow the number of users dynamically up or down. The tools can grow with the value it’s bringing to customers.
14:00 — That scalability allows Apromore to be flexible and scale with shifting customer needs.
AI’s Role in the Product Roadmap
14:48 — Apromore does not see many use cases for generative AI in terms of generating code from a prompt. “We are doing things a little bit different as far as generative AI is concerned. We are not looking at generative code anyway; it doesn’t make sense for us because we are a no-code solution,” Dumas shares.
15:44 — Rather, Apromore views generative AI as “a vehicle for automated process improvement.” The company uses generative AI to look at existing processes, or processes it discovers from its data, then makes changes to improve the processes from those insights.
16:08 — “We take the ideas that it’s generating and we feed them into our digital process mining technology, and we start testing them and we see which ideas can be implemented,” Dumas describes. Then a subject matter expert can determine what changes are feasible and refine those to determine a shortlist of improvement opportunities.