For a small company that sells only 1 product in 1 market with 1 warehouse, and works with only 1 production factory sourcing its materials from 1 supplier, it is a simple task to allocate demand for the product to the factory and corresponding supplier since no other options are available. However, the allocation decision becomes significantly more complicated in the case of a company that sells 5,000 products in 50 markets operating with 20 warehouses, and works with 100 production factories that source their materials from 300 suppliers located in different countries.
Today, brand companies that design and sell their own products need to meet their customers’ demand by using their available production and material resources. Each resource brings constraints such as capabilities, capacities, costs, etc. The decision to place an order or release a forecast is too often based on incomplete information, leading to inefficiencies on the brand company side as well as on the factory and supplier side. As a result, millions of unnecessary cost occur every year across the full supply chain.
Datacrag Limited will bring profound value to the brand companies’ overall inventory turnover performance, which is one of the most pivotal metrics that determines every major brand companies’ operational efficiency therefore profitability. An optimized demand to supply planning platform will significantly improve the visibility and agility of an extended long supply chain typical to many brand companies as they source mainly from East Asia supply base to markets in North America and Europe.
The business idea of Plan © is to provide a demand and supply planning software that will help brand companies to know which resource should be used for what product at what moment under which circumstances while considering all the nodes from its resource network. By doing so, it will give the companies high confidence in their allocation decisions and will replace a sequential long-duration workflow which constitutes the major part of information lead-times with an automated instant process. The figure below illustrates and example of the multi-node network based resource allocation process where each node (e.g. factory node, supplier node…) is considered in the decision making.
The main features are:
- Significant landed cost and lead-time reduction through optimal demand allocation and shorter decision processes
- Identification and prioritization of eligible resources
- Integration of external factors that affect the quality of an allocation decision (e.g. tax agreements between exporting and importing countries, production efficiencies, shipment time etc.)
- Constraining the demand with real capacity for finished goods and materials (Rough Cut Capacity Planning)
- Decision traceability through the storage of all historical resource allocations
- Comparison of what was forecasted to what has really been ordered
- Comprehensive “what-if scenario” simulations
- For the application, the software is specifically shaped for brand companies that plan at color/size level and use product classifications such as “model” and “style”. Example industries are
- Footwear, Apparel, Handbags, Toys and Accessories.