Ron manages a sourcing agency whose customers are branded chain retailers.  He obtains his supplies from multiple manufacturers. His business is complex, managing the matching of his customers’ requirements with suppliers’ production capability and inventory.  His main goal is to get his customers the right product, in the right quantity and at the right time. In addition, he wants to exceed customer expectations.

Ron has a good team: Debra, the designer and Shane, the Sourcing Manager. Together, they need to be hands-on for all the styles delivered by a particular supplier across all customers. They must keep a history of all the styles purchased by a particular brand across all suppliers. Debra’s job is to present the design, development and production capability to customers by understanding each customer’s choices over the years. On the other hand, Shane needs to approach the right suppliers based on his understanding of their respective manufacturing capabilities on the parameters of styling, price and capacity.

Currently Debra’s team grapples with the vast collection of images stored across folders ‘owned’ by individuals. They spend several days collecting and emailing the images to one another. The file sizes are huge – often the images are zipped or shared within a common folder or a common FTP. The whole process at the design end takes valuable work time and reaches the sourcing team at the last possible moment. The sourcing team must rush to review the requirements and forward them to appropriate vendors. This rush causes errors and oversights and the quality of customer service is compromised due to lack of time.

Shane’s sourcing team coordinates with vendors for capacity allocation, sampling, production planning and dispatches. They update sampling status to designers and production status to the end customer.  These updates are contained within spreadsheets. They need to spend many additional hours if they have to manually embed images of samples within the sheets or power point presentations. Accumulated data is also used for classifying suppliers based on style complexity, order size, lead times, etc. Shane’s team is constantly challenged by the length of time required to associate styling capability with suppliers.  All the time spent in manually collating data adds up, slowing internal and external response times.

Can Kanvas help Debra and Shane? Yes, and significantly. Kanvas will enable them to collate, sort and share effortlessly, so they can focus on business targets, with a swift response time to customers!

Debra can create a “style library’”, managed by brand, season and category. She will be able to maintain consistency in the quality and look of design ranges delivered over years. The data comprising fabric usage, ordered quantity and FOB can help her envisage the order value at the design stage without requiring any spread sheet work.

At the other end, Kanvas can enable Shane’s team to identify the best vendor for a particular style, quantity and target price in a matter of minutes by analyzing their past data within Kanvas. All they have to do is search the styles of the vendor for previous seasons. They can even search with respect to a particular customer, division and sub brand.

Using Kanvas, Shane’s team can create a status board of styles at the supplier to be updated in real time with delivery dates.  They can collaborate with design team and regional sourcing teams using Kanvas. And all of this using the actual style images!

Kanvas can help Ron’s team access the data in real time on a single platform. Kanvas improves the quality of processes, enables the entire company to save valuable work time and collaborate more efficiently, thus helping Ron reduce costs and improve his business margins. And with significant saving in order processing time, his company can exceed service expectations from both customers and suppliers.