Last updated on February 1, 2025
Moving from Data to Decisions: Building the Retail Organization of the AI-First Century
In today’s busy retail environment where every transaction is a narrative and customer touches have the capacity for immeasurable value, there are a plethora of organizations that are data rich but intelligence poor. The potential of AI calls, but for a good number of retail leaders, the journey of becoming an AI-First organization is fraught with difficulty. This is not merely a question of technology — it goes to the core of how we think about using data to make decisions in any aspect of a retail operation in a new way.
Modern Retail’s Data Quandary
Imagine stepping into a modern-day retail shop. Associated with this, digital price tags are instantaneously updated, inventory systems work seamlessly in the background and customers seek goods in both the physical and app aisles at the same time. This fusion of the physical space with the digital space results in an unparalleled increase of retail transaction data. Even so, a new study that has been performed by McKinsey about retail analytics shows that only 23% of retailers manage to properly working this data goldmine yielded into it, into actionable information.
This is not moved by the problem of data scarcity — but by the problem of moving data into action. Zara, Target and other retailers at the level of the leaders have not only acquired information — they have purposefully redesigned their businesses to be data driven. And the numbers do not lie: Inventory turns 40% quicker, stockouts were reduced by 35%, and customer satisfaction ratings exceed market expectations.
Transforming the Paradigm: The Data Architecture
As has been often said, traditional retail houses resemble medieval empires – teams operate deeply in isolation, each department hoarding their share of the data. And the modern day retail would require tearing down such structures to allow for the establishment of ecosystems that govern and ensure the free exchange of perspectives and insights.
Let’s understand how Nordstrom has evolved its practices. They were able to shift the perspective of data as a byproduct from the operations instead treated it as an asset which propelled them to construct a single data lake that supports the entire organization’s AI models. This transition was not purely technical; it was also social, and involved redefining how teams work together, how they go about making decisions, and how they measure success.
AI Come First: Trends in Cultivation
There may have been an unprecedented technological evolution, but it was made possible because of people, that truly stood as the catalysts for change. A data oriented culture is a prerequisite for any AI system – including the most intelligent Cortechs – to function. That reality is not lost on CJ. The idea of data driven intuition – the ability to ask correct questions of data and believe in its answers – has roused them deeply, and they need a robust grasp of and belief in it.
Home Depot’s journey is a great case study. Their leadership was sure that to shift to AI-first it was not enough to only install new systems. They rolled out an unusual program that offered both practical implementation and decision making, helping employees from all levels understand not just how to use AI tools, but why they even exist. And the Company was right, over the past three years, there was a 60% growth in the adoption of AI-enabled initiatives across the group and improved quality of decisions in various aspects of the organization.
From Insights to Action: The New Decision Architecture
An AI-first organization does not only compete on the algorithms it builds, as sophisticated as they are, but even more so on the speed and the quality of their decisions. Visionary retailers are building what we call “decision architecture” – concepts that make decision actionable insights available through AI self-service at all functional levels of the organization.
The same goes for Kroger’s recent shift to integration Real Time Decision Support System with AI capability. It has reduced time to make a move by 75%. Store managers are guided by AI recommendations about stuff like amount of people to work or when to run certain promotions with in-depth descriptions for what’s behind all the advices. This candidness nurtures and enhances faith in AI systems.
Risk and Governance – Balancing Innovation
Retailers throws chum to the sharks when they seek drastic governance frameworks in their race to go AI. But governance should not kill innovation, it should foster it. Leading organizations are adopting what we call as ‘adaptive governance’. Policies which are static with respect to technological capability but are always consistent with risk management principles.
Demystifying the Process: Laying the Groundwork for an AI-Driven Business
The evolution to an AI-first retail marketing organization is not a simple template that one can apply over organizations. Successful transformations do have a few similarities or rather a checklist to follow. Here’s how this transformation looks to unfold:
- It begins with a clearly articulated strategy that is devoid of the how – “business goals first, technology second.”
- It incorporates a scalable and secure data architecture
- It takes a people and culture wide approach as opposed to simply systems and tools
- It deploys a holistic view of success relative to strategies and not technical parameters.
Finding the Right Solution
There is no denying that the retail sector continues to transform at an unprecedented rate. Those enterprises who will have successfully endeavored this transformation from retail first to an AI enterprise, cascading benefits in that transformation for their customers will follow. They will have enabled swift decision-making processes and deeper insights into their offerings which in turn will lead sustainable advantages that will far supersede a single technology rollout.
Getting to the AI-first retail strategy is a journey that is quite intricate, but the good news is you will not have to walk this path alone. Blanco has extensive experience with AI transformation in retail and therefore supports organizations in designing and implementing their path to operating in an AI-first mode. Our work integrates skills and knowledge of business, therefore your journey through the transformation brings you value at each step.
Retail will be won by companies that can transform information into decision, insights into actions, and opportunities into results. So, before getting there, are you prepared to start off your journey to operating as an AI-first retail company?
