creates a plan based on a recipe • Purchasing inputs that won’t be made by the group • Making what was ordered, based on the plan, and coordinating P2P • Shipping or delivering the products • Receiving payment for the products • Distributing the income received to people who contributed, using a democratically decided value equation
the group has decided to create something without a customer order, for example some tools they need. Or some groups usually make to inventory. For example, if the tomatoes are ripe, it is time to make a large batch of salsa, which will be sold or traded after it is made. We call this a work order instead of a customer order. In this example it is a customer order for a 3D printed part. This group usually makes to order because each order for 3D printed parts is different.
there is a recipe for the product that was ordered, it is used to generate a plan. This plan has one order item, with two processes planned to create the product. The process to print the part is dependent on completion of the design. Some recipes are very exact, when the manufacturing information is known. Some are more general. In either case, the plan can always be changed to fit the circumstances, either by changing the details, or re-scheduling a set of dependent processes forward.
can be purchased by the group or by individuals, who will get credit for this as a contribution. This is the logged purchase of the polymer consumed to make the part, paid for by a member of the group. It is now in inventory. Some will be used for this part and some for other work in the future. If an input is already in inventory, purchasing it will not be planned.
purchased through cash contributions by two people in this simple example. In the real Sensorica case, it was many more. The contributors get paid back over time as the printer makes money. All of the resource and cash flows are transparent to everybody. When everyone is paid back, the printer will become part of the commons. The community funded a piece of equipment...
All the inputs are logged transparently. People can coordinate their work through views and notifications. The group can decide whether to log work contributions for credit, or to give credit for the deliverables without logging the hours of work. Each output is logged too. If an output of this process is needed for the next process, it is now available. Some resources are consumed by the process and no longer visible in inventory. Others, like equipment, are merely used. Inputs like designs or ideas can be cited so the creators get credit for their contributions to those inputs.
is shipped or delivered, that is logged, and it goes out of inventory. When the payment is received, it is also logged. Payment could be in a standard currency or a crypto-currency or some other resource.
the value equation agreed upon by this fictitious team. In this example, a percentage is set aside for fixed lab costs, and also a percentage for people who do support work for the network in general. The rest goes to the people who produced the product that was sold, based on their work and financial contributions. Another network might split by percentage by work function, for example growing, harvesting, and drying herbs. Or translating, editing, publishing a translated work based on word count. These examples use deliverables rather than time as contributions.
This gives an explanation of how the distribution will be created for this order for the 3D printed part. It allows people to experiment with defining their value equations, and see how things will work before agreeing on the rules and actually distributing income.
are the aggregated results of this value equation’s rules applied to the work and financial contributions made by the group, both to fulfill the order and to support the production work. Everyone’s contributions were traced back through the value flow so everyone can get rewarded. A final note: The functions and options that the software supports were created to fit the needs of the networks that have used the NRP thus far. As others start using the software, we are sure that more ideas will be introduced. We will be happy to continue to refine the software to fit the needs of other networks. The Mikorizal team