October 30th, 2024

Copabo Indústria, a Brazilian leader in industrial product distribution, has teamed up with Slimstock to launch a major supply chain transformation initiative. By adopting Slimstock’s AI-powered planning platform, Slim4, Copabo aims to optimise its working capital investment in stock and enhance operational efficiency.  

Founded in 1968, Copabo began as a specialist retailer of rubber and plastic products. Since then, the business has grown to become a dominant player in the industrial maintenance solutions market, forging partnerships with global giants. Specialising in maintenance, repair, and operations (MRO) solutions and PPE, Copabo serves a wide range of industries, providing conveyor belts, industrial hoses, bearings, and more.

Dedicated to delivering high-quality products, innovative solutions, and lasting value to customers, employees, and shareholders, Copabo identified an opportunity to fuel continued growth by transforming its end-to-end supply chain.

 

Strengthen the operations

With the implementation of Slimstock’s AI-enable supply planning solution, Copabo aims to:

  • Automate routine planning workflows to create efficiency gains.
  • Leverage advanced data insights to track critical KPIs and enhance visibility.
  • Elevate forecasting capabilities to mitigate the impact of market volatility.

The partnership with Slimstock will allow Copabo to gain greater visibility throughout its supply chain, centralise key parameters, and improve demand planning across its multiple warehouses. By reducing the reliance on spreadsheets, Slim4 will streamline KPI tracking, improving lead time management while empowering the planning team at Copabo to drive the efficiency improvements required to support future growth.

Ednei Kupper, Commercial Director, expressed his confidence in Slimstock’s platform: “I have high expectations, having had a positive experience with Slim4 in the past. I’m familiar with the valuable benefits it offers, and we anticipate a swift return on investment thanks to its robust analytical insights.”