Employee Adoption and Change Management
whole pizzas to half pizzas and adjusting packaging from two-slice and single-slice containers would impact demand. By piloting this approach across a set of stores, they were able to analyze whether smaller package sizes encouraged more sales of different varieties, created a “halo effect” on other items in the assortment, or changed overall pur- chasing behavior. These kinds of experiments, even on a small scale, demonstrate how demand forecasting data can be leveraged to uncover new opportunities and guide operational decisions. Data Management and Sourcing Data, the foundational requirement for AI, was a consistent topic of discussion, with participants seeking guidance on how to manage and source it effectively. Robert Hampton , VGN’s director of strategic growth and initiatives, specifically asked for advice on overcoming the fear that “my data’s not clean enough.” Brask advised retailers to focus on gathering at least two years of histor- ical sales data from POS transaction logs (TLOGs) as the primary foundation for AI, even if the data is incomplete. He clarified that AI can effectively bridge many data gaps, detect SKU rationalization changes, and learn from previous item demands to generate updated forecasts.
An important distinction made by Brask was that while sales data is the core, external data like weather and promotions can often be layered in by AI providers, reducing the burden on the customer’s internal systems. Weber reinforced this, noting that supplemental data streams, such as weather patterns or local events by ZIP code, are now “much more accessible” and affordable, allowing AI to “build the picture of my business without me having the data.” This accessibility makes robust AI implementation feasible for medium-sized businesses without requiring extensive internal data infrastructure beyond basic sales history.
A critical and human-centric aspect of AI integra- tion is its impact on the workforce and the inevita- ble resistance to change. Eva probed this directly, asking about employee feedback on AI systems: if they find it intuitive, easier or if it makes their jobs more interesting. Weber responded positively, not- ing that AI-driven systems are often more intuitive and easier to use, akin to opening an app without formal training. He observed that guided AI tasks reduce “attack[s]” or surprises for associates, mak- ing their jobs feel easier and leading to increased
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