Among other reasons we’ve talked about, many retailers are looking at AI-powered pricing solutions because they feel confined by strict sets of pricing rules and policies, often put in place many years ago—long before modern data science was even a concept.
On the heels of our very well-received co-presentation with Phillips CSCO Ivanka Janssen on AI at last month’s Gartner Supply Chain Symposium in Orlando, I had the pleasure of facilitating our June 30 virtual roundtable—'Align Inventory to Consumer Demand’.
Retail and CPG companies struggle to balance investments that remediate short-term pains and improve long-term resiliency. Disillusionment over prior investment payoffs, plus being in constant crisis mode, has supply chain executives focusing on fundamentalssuch as efficiency improvements and cost containment.
Retailers are already facing their next inventory crisis—too much stock on hand, with too few buyers.
When retailers come to us to look at our AI-driven lifecycle pricing solutions, the first people we talk with—the “point persons” responsible for overseeing pricing decisions—are usually quick to grasp the real benefits. They’re eternally striving for that ideal markdown “sweet spot” for every SKU—accelerating sell-through while preserving—if not squandering—margin. But without a unified, data-driven markdown strategy, they’re often the first to concede their haphazard, decentralized markdowns are “a mess”.
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