While subscription-based businesses have obvious benefits, such as a larger LTV, they also bring their own set of unique challenges. For Universal Yums, these are amplified by the fact that each month’s box is unique, which requires careful planning far in advance of fulfillment. Universal Yums came to Fulfil looking for a solution to 3 Primary Challenges:
- No Single Source of Truth for Operational Data
- Paper-based Pick/Pack/Ship was slowing Universal Yums down
- Lagging data on Inventory Management
No 1 - No Single Source of Truth for Operational Data
The Universal Yums team were operating out of a series of disconnected point solutions that all performed a specific activity, but weren’t integrated to share critical data between systems. This meant that any time the team would need information from different systems, it would require a manual, painful workflow involving exporting data from multiple sources, and consolidating it into a static spreadsheet.
As a specific example of this, the team’s financial information was spread across 3 different systems that were not integrated. This resulting export/import workflow was tedious and time consuming for Matt and his financial team to spend hours completing on a monthly basis.
“Accounting wise - I used to have to dump a ton of data from different systems to try and reconcile things together. The end of month reconciliations were a nightmare.”
The nature of a unique monthly subscription box means that the Purchasing team needs to place all Purchase Orders at least 6 months in advance of when the box gets shipped to a customer. To accomplish this, a careful Demand Planning workflow has to be followed which relies on accurate input data. Prior to Fulfil, not only did Universal Yums lack a single source of truth, but the separate systems often had conflicting information..
Finally, even when the Purchase Orders were able to be placed, the Purchasing and Finance departments did not have a place to store, and subsequently enforce, payment terms with suppliers. With 100s of suppliers around the world, and 1000s of open purchase orders to keep track of at any time, manually tracking this information was incredibly difficult.
The lack of a single source of truth for operational data had an extensive impact on Universal Yums across multiple departments, and they needed a solution.
No 2 - Paper-based Pick/Pack/Ship was slowing Universal Yums down
The Universal Yums picking team needs to balance two very unique workflows - the high volume, monthly subscription box that comes in a wave, as well as the lower volume, but more frequent, Yum Shop orders. Each requires a different methodology to complete, and careful checks and balances to ensure the right product gets sent to the right customer.
However, the Warehouse team was stuck using a paper-based picking system which significantly impacted the productivity of the Pickers. Not only was it difficult to work with the paper-based workflow, but the lack of scanning as a control throughout the process resulted in a higher volume of mis-picks.
“Prior to Fulfil, Picking in the warehouse was a slow process that bogged us down - it was costing about 15% of our revenue for the pick/pack process alone.”
No 3 - Lagging data on Inventory Management
Effectively tracking the specific inventory movements for subscription boxes from:
Receiving → Overstock → Pickable Bins → Packing → Shipping
is an extremely difficult process, especially when dealing with a high volume of unique subscription boxes that contain a large number of sub-components.
In reality, these boxes follow a pre-production workflow, which means that inventory should be subtracted on a live basis as the boxes are individually assembled according to their bills of materials (BOMs). However, the previous software did not have the support for Production BOMs, which meant that they were forced to do periodic bulk adjustments for large sections of inventory, rather than keeping a real-time inventory log. This meant that their team never had live visibility into their inventory numbers, and couldn’t fully trust the data that was in their system.