What is proposed is taking a broader analysis for the ten that goes out the door just to sit on the flight line until delivered. Delivery is where the cash is transacted. Delivery means all work and testing are done. In order to get a true number of 10 a month it would be better to toe the line at the delivery point rather than how long it took to assemble in the factory. Boeing should develop a 90 day moving average number which captures the true productivity until the actual delivery date, rather than cutting short of that number by counting what comes out the factory door at the end of the month. That number does not include all the shenanigans issues when sitting out doors How does this moving average number work? It works by thinking about real events that actually impede or advance the progress towards the day Boeing would receive money or deliver the aircraft. Boeing's true target is delivering ten 787's every month to customers. To get there they analyze progress using a 90 day moving average of actual deliveries.
In order to explain this concept it is better to understand the back log. There are three basic categories that need inclusion in the inventory analysis. I don't care if 10 airplanes a month are moved out the door more or less. Nobody has been paid yet.
Boeing had 40 or more aircraft sit outside for several years from the three - five a month rate. All had or has to go through the EMC (change incorporation center) before delivery. Therefore, those aircraft built at five month had acquired an immense sit time with no payment with more money poured into the hull of each aircraft over time. Appropriately, these should not be counted as a true monthly production number during that time.
Aircraft coming out the big aircraft doors sit on the ground during systems checks, upgrades and receiving corrections before test flown. They may sit on the flight line for up to 60 days before being worthy of delivery.
Customers are not ready for delivery, even if aircraft are certified for delivery. A customer may have money issues, training issues remaining unresolved, or just not ready to task the 787, so the airplane just sits for up to 30 days after test flights have been completed.
Boeing can build 10 a month and fill its parking lots with aircraft, but the job is not complete until it delivers. Therefore, the 90 day moving average takes all three major categories into consideration as part of meeting a 10 per month production goal.
Here is how a more accurate reflection is constructed. Count the raw deliveries each month. Average on a 3 month moving number, using the current month delivery number and adding two prior months, providing an average count based on deliveries not the actual productions coming out the door. Those out the door aircraft are not finished yet until delivered. This method asborbs all the anomalies of production and delivery.
If January had 8 delivered, it included all the above conditions even though production moved 12 out the factory door. In February, some of those january 12 are delivered after passing testing, and a few of those twelve remain in February inventory, because those "ready" made it through all the post assembly stop points, and finally, where customers who are ready to take it on for delivery, 9 787's sitting in a completion stage, were delivered because the customers were ready. So count February as 9.
Finally, March comes. 10 units go through the factory door and 12 are delivered from the standing inventory. Add 8 + 9 + 12= 29 is divided by 3 (months 90 days) resulting 9.67 unit completion from a moving average for March. This accounts for all the bumps and jumps during that 90 day period. Making a moving average for April is simple. If April delivers 11 787 then the production moving average would include February for 9, March for 12 and April for 11. The moving average for April is formulated as such (9+12+11= 32)/3 for a moving average production level for April of 10.6. Taking in the 3 considerations into account and averaging over a period of time smooths out the lumpy monthly performances in production and testing. It then matches that true output with customers delivery schedule by assigning a financial value on that output which is a handy number for stock-holders.
Later I will provide actual numbers for 2014 and demonstrate how this moving average calculation removes the clutter and confusion from those watching the production floor to the financial floor of the stock market over a year.