A 182-year-old Fortune 500 joins the 5% that succeed with AI.
95% of enterprise AI initiatives fail. Here is how a Fortune 500 manufacturer joined the 5% that succeed, turning weeks of analysis into single conversations and unlocking insights no BI tool could touch.
95%
Of AI initiatives fail (MIT). SBD is in the 5%.
0 → 1
Unstructured data insights, previously impossible
Wks → Min
Complex ML analysis replaced by one question
4+
Business domains adopting and expanding
“[Zenlytic by Chord] and the team have been amazing in opening our eyes into the possibilities in this space. Seeing is believing. And we saw. You made us see.”
The Company
A 182-year-old Fortune 500 manufacturer building its AI-powered future from the inside out.
- Stanley Black & Decker: A 182-year-old Fortune 500 global manufacturer and one of the most recognized names in tools, industrial equipment, and security solutions. Billions in annual revenue with operations spanning the globe.
- A modern data and AI organization is charged with identifying business problems AI can solve, designing systems to address them, and driving cultural adoption across a workforce spanning generations and geographies.
- Leadership: Paul G. (Senior AI Architect) leads the AI strategy alongside a team of architects and data leaders building Stanley Black & Decker’s AI-powered future from the inside out.
The Challenge
Solid BI, slow cycles, and an entire category of data no dashboard could see.
- BI was solid, but slow. Power BI was the enterprise standard, but every new report required a full project cycle: resource alignment, developer assignment, support planning, and SME coordination. Unless you had a standby dev team at the snap of your fingers, BI could not keep pace.
- Analysts were trapped in maintenance mode. The more dashboards the team built, the more maintenance they carried, and the less capacity they had to explore new, more valuable metrics. The same KPIs got recycled while bigger questions went unasked.
- An entire category of data was invisible. Product sentiment, customer reviews, recurring defect patterns, qualitative quality signals. These were some of the most important insights in the business, and no Power BI visual could surface them.
- Generic AI tools could not be trusted. ChatGPT, Claude, Gemini: all returned different answers, all probably wrong, because they did not have SBD’s proprietary data at their fingertips. The team needed governed, private, secure AI.
Why Zenlytic by Chord Won
A semantic layer, governed AI, and questions dashboards could never answer.
- The semantic layer was the decisive differentiator: By defining business context and metric definitions in a verified, controlled layer, every Zoë response is grounded in SBD’s data and fully traceable. No hallucinations. No black-box guessing.
- AI that knows your data, privately and securely: Unlike generic AI tools, Zenlytic by Chord brings enterprise-grade AI directly to SBD’s proprietary data in a governed environment. That unlocks endless potential without compromising security.
- Questions dashboards could never answer: During the pilot, Zenlytic by Chord posed a fundamentally different kind of question: What would happen if we moved a manufacturing plant from Location X to Location Y? That single query replaced weeks of custom ML development.
- A partner that expanded the team’s ambition: SBD’s own pilot document was framed around traditional analytics questions. Zenlytic by Chord’s demonstration reframed the entire vision of what AI-powered analytics could achieve.
Key Results
Invisible data made visible. Weeks of work compressed to a single conversation.
- From 0 to 1, unlocking invisible data: Global quality teams can now analyze unstructured product data at scale for the first time: customer sentiment, ratings and reviews, and recurring defect patterns. This is not a faster version of what they did before. It is something they could never do before.
- Weeks of ML development replaced by a single question: A plant relocation scenario requiring inventory data, shipping logistics, cost differentials, and distance calculations became one conversational query with Zoë.
- 4+ business domains and growing: Adoption expanded organically from global quality into warranty, global supply chain, commercial sales, and Material IQ for commodity markets and procurement compliance.
- A 182-year-old culture transformed: In a company where 25+ year tenures are common, teams moved from maintaining familiar BI reports to conversing with an AI analyst. The organization now sees AI as a tool that amplifies what every individual already cares about.
“Actionable, more intelligent insights faster, when you need them, not when someone can develop them.”
“We are fully bought in. We are working hard to enable this for multiple different domains, unlock value, new ways of thinking, not just making old ways of thinking faster.”
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