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→Throughput: clarify derived values
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(→Throughput: clarify derived values) |
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* Example: If $100,000 worth of products sits in warehouse for 30 days, this creates 3,000,000 inventory-euro-days | * Example: If $100,000 worth of products sits in warehouse for 30 days, this creates 3,000,000 inventory-euro-days | ||
* Lower IDD indicates higher effectiveness. The ultimate goal would be 0 IDD. | * Lower IDD indicates higher effectiveness. The ultimate goal would be 0 IDD. | ||
Because almost all of our work is being done by people on laptops, we calculate the inventory based on the hours invested into a project, times an hourly rate. The hourly is set in advance and can vary per person. The primary determinant of your hourly rate is your experience level, as we generally expect a senior engineer to be more productive than a junior engineer, and thus their work to lock up greater value while sitting on the shelf. This implicitly means it becomes more important to get your work into production faster, as you gain more experience. | |||
==Reliability== | ==Reliability== | ||
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* Average revenue, trailing four quarters. | * Average revenue, trailing four quarters. | ||
In essence, these all measure the same thing; in theory, only the daily revenue matters. As we are a smaller company, though, we don't send hundreds of invoices per year or get invoices paid to us every working day. For example, we could get 1.000 on Monday, nothing on Tuesday, and 3.000 on Wednesday. That doesn't necessarily imply that Monday was a good day, Wednesday was a great day, and that we failed in our work on Tuesday. | |||
Effectiveness and Reliability go up and down each day in semi-predictable amounts because they mostly directly result from the work you're doing and not doing as a team. But Throughput can be very "spiky". That makes graphs harder to read and interpret. We use the revenue per quarter and average four quarters trailing revenue to smooth out the graphs. | |||
=A sidenote on quality= | =A sidenote on quality= | ||