The success of AI-optimizedrevenue growth managementrelies on the business data and the speed at which it can be actioned on.
According to Kyle Chu, director of FP&A and business intelligence at PopSockets, and Sunny Yurasek, head of advanced analytics and RGM forWells Enterprises, the unlock will be in achieving a true real-time response rate using AI-enabled data practices within RGM.
“What we’re trying to stay ahead of is making the data available for decision-making as quickly as we can,” said Yurasek during the recent Consumer Goods Sales & <a href="https://bitcomme.com/youtube-marketing-success-playbook/” title=”YouTube marketing success playbook”>Marketing Tech Summit. “But until that is fundamentally solved, I think real-time is a ‘high in the sky’ goal.
It’s a journey hampered by a lack of fundamental data development. Data might be everywhere, but you cannot simply skip the governance, the months of harmonization, the relationships
“Our data scientists are asking very specific questions like, ‘How would you want me to allocate these hundreds of cases? What are the rules? What’s the context with this customer?” she said.
Chu, who is in the process of managing legacy tech debt, said he really takes data democratization to heart and has focused on making better decisions withdata empowered by AIby formatting the data, governing it across the organization, and empowering everyone on the front lines and sales reps with the information.
But context matters.
“How do we look at the context layer that governs our definition of success? Chu posed. “What are the processes that we’re trying to improve?”
What he is currently working on is getting semantic models to talk to each other and really building the context layer of what success means for the organization, particularly within the intersection of data and financial planning.
“I think there is an element of RGM that has to have some intersectionality with return on ad spend, return on investments … because the ultimate goal is to drive revenue, but what if it doesn’t do it to the extent that you hope? How do you modulate that and how do you get AI to help within those processes as well?” said Chu.
Having a definition of success to aim for is extremely important
“I don’t think there’s a golden standard [of measurement] at this point, but defining that and everybody understanding how to measure it becomes something useful for the RGM function to strive toward, for the partners and organization to strive toward,” she said.
Also:Industry Report Says Cross-Functional Misalignment Remains Top RGM Barrier
The pair agreed that establishing strong measurement practices will also help keep employees accountable even when tasks are delegated to AI.
This is particularly important in instances where the outcome of an AI-driven suggestion doesn’t match up with the goal. Yurasek said that when the RGM platform spits out a recommendation with retailer implications, the person owning the retail relationship has to manage the outcome, no matter what it is.
Keeping humans in the loop will remain essential.
A large network like Wells — which has an omnichannel business that sells into Target, Walmart, Amazon and more, and owns a DTC website as well — produces “mounds of data,” This makes it difficult to analyze everything SKU by SKU as a human. But only humans are able to look at the AI rationale and make a decision contrary to the data based on their intuition and knowledge
“You can analyze what you see, but you cannot analyze what you don’t see,” said Yurasek. “And I think that’s where humans are so important.”
