The Future of Better and Faster Decision Making

Author: 8th and Walton

As a retailer or supplier, do you spend hours pouring over spreadsheets of consumer data? Making decisions about your business can get messy in the numbers. Recently, we’ve learned how the team at IRI makes data collection easier through their Liquid Data® Technology. Now we’re going deeper into their process to see how they make the next step seamless as well: decision making.

The Future of Better and Faster Decision MakingLynda Gammell is EVP for Augmented Decision Making and Data Cloud Management Programs at IRI. We had the opportunity to speak with her about augmented decision making (ADM), what it means for retailers and suppliers, and how it can be applied to the current business process. As she explains, making the technology do the exhaustive data research and analysis will empower teams to improve their businesses.

What Is Augmented Decision Making?

For those new to this area of research and analytics, we started by asking Lynda about ADM. She detailed not only the benefits of ADM, but why it is becoming essential for tomorrow’s leaders.

“The future of market research lies with leaders who are focused on automating and democratizing insights,” she explains, “augmenting human decision making with AI (artificial intelligence) and ML (machine learning) based prescriptive actions and ultimately, automated decision-execution engines and platforms.

“ADM is the process of using technology and analytics, combined with a business process, to let the machine do the work of combing through massive amounts of data and seeing patterns. Then, making recommendations and using these capabilities to drive change in organizations and business processes. With the help of AI and ML, the trend lines come together without human bias or judgment.”

ADM for Today’s Walmart Supplier

For the growing supplier, it sometimes isn’t a matter of choosing the right options. When faced with so much data, the struggle can be just knowing your options based on the numbers! Lynda explains how ADM is helping with this part of the analytics process.

Employees stand to benefit greatly from ADM.“It’s really about transforming insights into reliable, scalable, defendable and relevant recommended decision actions prioritized based on the highest value opportunities,” Lynda illustrates. “ADM is part of a journey to move from the current world of insights to increasing decision automation against all business processes undertaken by retailers, suppliers and media players.”

On the surface, ADM seems to build on the intelligence of the systems. However, Lynda goes on to show how ADM is actually empowering the user. Employees stand to benefit greatly from this applied technology.

“People should expect to see a transformation that allows self-service for more users, and provides actionable, measurable and faster decisions and significantly improves speed to make decisions through greater automation,” she says. “ADM will enable the transformation of today’s insights teams to become the leaders in the application of advanced capabilities. This includes ML and AI to enable more users access to decisions, rather than centralized teams that create and report insights.”

Where ADM Is Making a Difference

One of great parts about our conversations with IRI is getting down to practical use of the technology. The application is interesting, but suppliers have the same question: How will this help me each day? Lynda details a practical use of ADM and where it’s making a huge difference in store clustering.

A practical use of ADM making a huge difference is in store clustering.“In today’s world, a user manually creates clusters of stores based on attributes, measures, and manual methods,” she explains. “In the near future, the user will select strategies to leverage clusters against a business process and is then provided with an optimized recommended clusters to use to support that business process.

“The underlying ML/AI engine is applying the business decision logic of the strategy against the context of the user’s selected products and geographic regions. It optimizes the right clustering algorithms to create the store groups to support the desired outcomes. IRI offers an initial level of these capabilities today across a variety of solutions that different processes. We will continuously evolve and enhance capabilities to address each step of the decision process over the coming months.”

(To hear our entire interview with Lynda Gammell, click here for the 8th & Walton Conference Call podcast.)

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