Added another example with complete files.

[docutils/kirr.git] / sandbox / docbook / examples / report2 / report.rst

.. role:: my-note\r
\r
****************\r
Internal Report\r
****************\r
\r
\r
:author: Paul Tremblay \r
:organization: Zappos \r
:date: 2011-11-29\r
:abstract: \r
\r
        This report sums changes to ZFC not found in the Amazon\r
        report.\r
\r
========================\r
Changes in Productivity\r
========================\r
\r
Overview\r
=========\r
\r
\r
ZFC experienced a decline in productivity in 2011.\r
\r
\r
.. figure:: charts/outbound_rate_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Outbound Rate, 2011\r
\r
   Rate for units processed for outbound. The sharp decline in the shaded\r
   area, at week 38, occurred during the cutover. _`outbound-graph`\r
\r
Looking at last year helps us better understand the decline.\r
\r
.. figure:: charts/outbound_rate_2010_2011.png\r
   :width: 550px\r
   :height: 250px\r
   :alt: Outbound Rate for 2010 and 2011\r
\r
   Rates for outbound processes for 2010 and 2011.\r
\r
There is a 8.32 unit difference, +- 2.58 error (95% confidence\r
interval). That translates to a -25% change, +- 7.9%. The graph shows\r
that the decline started around week 8, labelled “migration” on the\r
first chart. From weeks 6 to 11, Zappos moved all of its merchandise\r
from warehouse 1 to warehouse 2 in order to make warehouse 1 ready for\r
Amazon products. Not only did this migration require extra labor, but\r
ZFC processes non-footwear at a slower rate than footwear. The section\r
on static picking outlines the exact differences for static picking,\r
and also shows that static picking accounts for most of the decline\r
for the outbound process. If WH 2 had not received so much apparel,\r
then most likely the rate would have remained at 35 units/ man hour. \r
\r
The next big decline occurs in mid June, labelled “Testing start.”\r
Testing closed the warehouse at 1:00 AM in the morning, 5 hours before\r
the brief time the warehouse is usually closed between shifts. The\r
early closing time caused a backlog. Not only does a backlog by itself\r
mean goods are processed slower, but it also required ZFC to hire\r
temporary workers. Testing lasted until the week of cutover.\r
\r
\r
Other warehouse disruption also hurt the outbound ate. For example, in\r
early August ZFC tested SLAM shipping stations, and  closed down PANDA\r
lines in order to install the SLAM counterpart. With the PANDA line\r
down, and the SLAM not yet functioning, workers had to manually\r
prepare boxes for shipping. A week before cutover, ZFC tore out two\r
more PANDA stations, again temporarily replacing them with manual\r
stations. Graph shipping-graph_ shows the results on this disruption.\r
Note the decline in week 33, and again in week 37, a week before\r
cutover. Other processes show the sharp decline occurring about a week\r
later. \r
\r
Last, the trends for both years run more or less parallel to each other. The\r
sharp declines, starting at the end of September, results because of Zappos\r
business model. Peak season for Zappos starts at the end of September, when\r
ZFC receives a huge influx of goods, until the end of December, when Zappos\r
ships a large amount of product. In order to handle this extra volume, Zappos\r
hires more workers than it needs, making sure customer's orders never have to\r
wait and Zappos reputation and future profitability suffer. The hiring trend\r
was magnified in 2011, when ZFC hired even more worker than the previous year,\r
because the previous year Zappos had not hired enough help and experienced\r
backlogs. \r
\r
\r
\r
Productivity by Process for Outbound\r
====================================\r
\r
As expected from the overall decline of outbound rates, the rates for\r
individual processes also declined. The following graphs show the rates before\r
and after the cutover.\r
\r
.. figure:: charts/outbound_rate_2011_all.png\r
   :width: 5.73in\r
   :height: 5.21in\r
   :alt: Outbound Rate for Several Processes, 2010\r
\r
\r
Shipping\r
==========\r
\r
Shipping can handle a much larger volume of goods than other stations, and\r
there are fewer shipping stations. Hence the rate is much higer. \r
\r
\r
.. figure:: charts/shipping_rate_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Shipping Rate, 2010\r
\r
   Units shipped per hour over weeks, with a trend line. The first\r
   decline occurred during week 31, at the start of August, when ZFC\r
   had to close down PANDA stations to install SLAM lines. The second\r
   decline, in the shaded area, occurred during the cutover. _`shipping-graph`\r
\r
Here are the other processes, compared with the previous year, included for\r
completeness.\r
\r
.. figure:: charts/picking_rate_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Picking, 2010, 2011\r
\r
\r
There is a 31.8 unit difference, +- 7.9 units, from 2010, or a\r
-34% change, +- 8.5%.  Static and carousel picking are\r
combined for convenience. Although carousel picking has a much higher\r
rate, its volume is low enough that it does not change the overall\r
picking rate.\r
\r
.. figure:: charts/multis_rate_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Multis Rate for  2010 and 2011\r
\r
\r
There is a 10 unit difference in multis, +- 5.5 units. That translates\r
to a -13%  +- 8.5%.\r
\r
.. figure:: charts/singles_rate_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Singles Rate for 2010 and 2011\r
\r
\r
\r
There is a 10.3 unit difference, +- 6.8 units. This translates to a\r
-17% change, +- 9%.\r
\r
.. figure:: charts/shipping_rate_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Shipping Rate for 2010 and 2011\r
\r
\r
There is no significant difference for shipping between the two years.\r
\r
Static Picking\r
===============\r
\r
Static picking accounts for most of the decline in rates for outbound,\r
pre cutover.\r
\r
.. figure:: charts/static_picking_2010_2011.png\r
   :alt: Static Picking, 2010, 2011\r
   :width:  5in\r
   :height:  3.5in\r
\r
.. figure:: charts/static_vs_other.png\r
   :alt: Static Picking Compared to Other Processes\r
   :width:  5in\r
   :height:  7in\r
\r
\r
\r
Note how the rates for static picking mirror those for the outbound overall. \r
\r
From Justin Williams’ email\r
\r
\r
     I can definitely shed some light on reduction in efficiency last year in\r
     static picking.  From a direct rate perspective there were three main reasons\r
     for declining performance.  Firstly, we started the year with only footwear In\r
     W2.  Starting in late February we transferred all of the non-footwear from W1\r
     into W2.  This ended in early April.  This transition of inventory resulted in\r
     a change to our picking procedure and our picking teams had to be trained on\r
     how to pick to tote.  Also, Picking non-footwear to tote is less efficient\r
     than picking footwear to conveyor.  Secondly, as we gained inventory from the\r
     move and in preparation for peak, we had to use pick mods that didn't have\r
     conveyance yet.  This required pickers to travel several hundred feet and\r
     through gates to drop product onto takeaway conveyors.  Finally, as we\r
     received non-conveyable product from W1, we had to start up a new department,\r
     Singulate, to take full totes of Multis and individually induct product into\r
     our Multi sorter to Multi lanes.  I believe this department labor was shown\r
     under picking for several months until it was split out separately.  \r
\r
______________________________\r
Footwear Vs Nonfootwear Rates\r
______________________________\r
\r
The decline in footwear resulted largely because it takes longer to\r
process non-footwear than it does footwear. The following graph\r
illustrates this.\r
\r
.. figure:: charts/foot_vs_non_foot_rate_2011.png\r
   :alt: Rates for Picking, 2011, Footwear and Non Footwear\r
   :width:  5in\r
   :height:  7in\r
\r
We can estimate the affect of apparel on the overall static picking\r
rate by determining how much longer it takes to pick to tote. We can\r
achieve this estimate in two ways:\r
\r
1. Estimate the difference from the figures that generated the above\r
   chart. Doing so we find that it takes 1.6 as long.\r
\r
2. Use figures from tests done at ZFC. These tests show that it takes\r
   1.7 as long to pick non footwear to a tote.\r
\r
These two figures can generate two more adjusted lines. Normally, the\r
rate is determined by the units/hours. For static picking, the rate\r
is:\r
\r
.. math:: \r
\r
 (text(units-footwear) + text(units-nonfootwear))/(text(hours-footwear) +\r
 text(hours-nonfootwear))\r
\r
We adjust the rate by taking out the extra time for the non-footwear\r
picking. If it takes 1.6 as long to pick to a tote, then we divide the\r
hours by the same amount. Doing so tells us the rate if all units\r
picked were shoes, instead of apparel and non conveyor items. The\r
equation for the lines then become:\r
\r
.. math::\r
\r
  (text(units-footwear) + text(units-nonfootwear))/(text(hours-footwear) +\r
  text(hours-nonfootwear)/1.6)\r
\r
\r
.. math::\r
\r
 (text(units-footwear) + text(units-nonfootwear))/(text(hours-footwear) +\r
 text(hours-nonfootwear)/1.7)\r
\r
We can generate a third line to test the accuracy of the other two.\r
Starting at week 8, we see a sharp decline in the static picking rate.\r
Nothing else explains this drop except the massive amount of apparel\r
moved to the warehouse. The drop showed that it took 1.3 times as long\r
to process all product. In order to adjust this line, we can multiply\r
the rate from week 8 by 1.3. \r
\r
If our adjustments are correct, we should see all three lines match\r
up. In fact, this is the case.\r
\r
\r
.. figure:: charts/static_picking_2010_2011_adj2.png\r
   :alt: Static Picking with Adjusted Lines, 2011\r
   :width:  5in\r
   :height:  7in\r
\r
We cannot adjust the year past the cutover by determining the amount\r
of footwear and multiplying that by 1.6 or 1.7 because there is no\r
data for non footwear for this time period. The Amazon WMS does not\r
allow us to track footwear vs. non footwear. However, we can apply\r
the adjustment of the third method above, of multiplying the entire\r
rate by 1.3. Doing so yields a sensible adjustment:\r
\r
.. figure:: charts/static_picking_2010_2011_adj4.png\r
   :alt: Static Picking with Adjusted Lines, 2011, 2012\r
   :width:  5in\r
   :height:  7in\r
\r
\r
Note how at the start of the year, static picking was at a rate of 62\r
units. If we adjust the rate, we end at around the same place. For the\r
first 3 weeks of 2012, the rates are 55, 55.5, and 55 units/man hour.\r
If we apply the same adjustments, the rates are approximately 71,\r
higher than last year.\r
\r
\r
The adjustment constant of 1.3 may be somewhat generous. If we take\r
the average of the all the adjustment lines from above, we come up\r
with a 1.2 adjustment line. In that case, the graph looks like this:\r
\r
.. figure:: charts/static_picking_2010_2011_adj5.png\r
   :alt: Static Picking with Adjusted Lines, 2011, 2012\r
   :width:  5in\r
   :height:  7in\r
\r
That puts ZFC at 65 units for the start of 2012 (after adjustment)\r
exactly the rate of the preceding year.\r
\r
\r
\r
Productivity by Process for Inbound\r
====================================\r
\r
\r
.. figure:: charts/inbound_rate_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Inbound Rate for 2011\r
\r
   Units processed per hour over weeks, with a trend line, averaged\r
   across inbound processes, for the period before and after cutover.\r
\r
\r
.. figure:: charts/inbound_rate_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Inbound Rate for 2010 and 2011\r
\r
There is a 9.1 unit change, +- 3.74 from 2010. That translates to -20%, +-\r
8.3%. \r
\r
\r
Receive \r
========\r
\r
\r
.. figure::  charts/receive_rate_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Receive Rates for 2010 and 2011.\r
\r
There is a 25.03 unit difference, +- 9.50 from 2010. That translates\r
to -19% change, +- 7%. Unlike other processes, the rate diverges more\r
sharply after the cutover.  If we take weeks 1-38 as the first\r
interval, and 42-52 as the second interval, we find a 49.6 unit\r
difference, +- 9.91. That translates to -41% change, +- 8%. The\r
indirect labor accounts for much of this change.\r
\r
.. figure::  charts/receive_rate_indirect_total_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Indirect to Total Hours, 2010, 2011. \r
\r
\r
The Amazon WMS introduced inefficiency to the receive process in\r
requiring an extra step of converting the PO on the side of the box to\r
an Amazon PO. Whereas formerly a ZFC team member only had to scan the\r
side of the box before putting it on a conveyor belt, now he must\r
apply and scan a case sticker, and then associate the case sticker to\r
an Amazon PO by means of PO wrapper tool provided by Amazon. In some\r
cases this involves scanning a code on a separate sheets of paper.\r
These extra steps have increased the amount of indirect labor. \r
\r
In order to figure out the extra hours, we can look at the indirect\r
hours as a percentage of the direct hours. \r
\r
.. figure:: charts/receive_direct_indirect.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Indirect vs. Direct Hours, Receive, 2010, 2011.\r
\r
We can adjust the lines in two ways:\r
\r
1. Calculate what the indirect hours should have been based on earlier\r
   in the year. Earlier in the year the indirect labor amounted to\r
   .455 |multiply| the direct labor (with the error margin added in). \r
   The total hours for after the cutover then becomes direct hours +\r
   .455 |multiply| indirect hours.\r
\r
2. Calculate what the indirect hours should have been based on last\r
   year for the same time period. Last year the indirect labor\r
   amounted to .365 |multiply| of the direct labor (adjusted for\r
   error). The total hours for after the cutover then becomes direct hours +\r
   .365 |multiply| indirect hours.\r
\r
The table below summarizes the results of these adjustments. \r
\r
\r
.. class:: receive-hours\r
.. csv-table:: Receive hours, adjusted \r
     :file: tables/receive_rate_adj.csv\r
     :header-rows: 1\r
\r
The adjustments show that the indirect labor amounted to 12,381, or\r
19,222 extra hours. The second number is probably  more accurate, since\r
it is based on the previous year. Given that the peak season requires\r
a huge increase in direct labor, we should see the percentage of\r
indirect labor decline, and  hence have reason for thinking the\r
indirect labor amounts to only .365 of th direct. Using the second\r
figure, we can find the cost of the Amazon inefficiency:\r
\r
19,222 |multiply| $16.10 = $309,474.00\r
\r
\r
\r
Putaway\r
========\r
\r
\r
.. figure:: charts/putaway_rate_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Static and Carousel putaway for 2010 and 2011.\r
\r
\r
There is a -35.6 unit difference from 2011, +- 12.7 units. That\r
amounts to -24% difference +-15%. \r
\r
\r
\r
Returns\r
=========\r
\r
\r
.. figure:: charts/return_rate_2010_2011.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Return Rates for 2010 and 2011 \r
\r
   There is a 7 unit difference, +- 1.97. That translates to -23%, +- 7%.\r
\r
Like the receive process, the returns process shows a sharp divergence\r
from the previous year. The divergence starts at week 25.  The change\r
occurred for several reasons. In order to meet increasing demand, ZFC\r
increased the size of its warehouse. During the build, ZFC eliminated\r
the inbound line, the trash line, and the outbound line from the\r
return process. Instead of having return items directly conveyed on a\r
belt to the unpack station, workers had to put them on a palettes, and\r
then move the entire palette. Likewise, team members also had to\r
return items to storage by moving them on palettes.  Similarly, trash\r
was moved by a manual process. These changes required more manual\r
labor and hurt rates. Both these changes occurred at the beginning of\r
July, and can by the steep decline in graph returns-graph_. \r
\r
In addition, the returns department moved to its own building, one\r
half mile away. Instead of simply placing items on a conveyor belt to\r
transport them to storage, workers now had to put them on a palette,\r
and have the palette driven to warehouse 2. This extra step also\r
requires more labor, hurting efficiency rates. \r
\r
\r
.. figure:: charts/return_rate_2011_2.png\r
   :height: 3.6in\r
   :width: 5.73in\r
   :alt: Return Rates for 2010 \r
\r
   Units Processed per hour over weeks, for returns, in 2011.\r
   _`returns-graph`\r
\r
The percentage of indirect labor also increased at the same time.\r
\r
.. figure:: charts/return_percent_indirect.png\r
   :height: 3.6in\r
   :width: 5.73in\r
   :alt: Percentage of Indirect to Total Labor, Returns\r
\r
This change occurred largely in part because returns categorized many\r
processes as indirect that formerly were categorized as direct.\r
\r
\r
\r
\r
Indirect vs. Direct Hours\r
==========================\r
\r
Since early 2011, Zappos has tracked direct and indirect hours. ZFC counts a\r
direct hour as labor that directly contributes to a process. For example, when\r
an employee picks an item off a shelf and puts it on a conveyor belt, the time\r
counts towards direct labor. In contrast, the labor required to make sure the\r
scanning guns operate correctly count as indirect labor. \r
\r
Not surprisingly, the percentage of indirect to direct labor increased in\r
2011. ZFC expected this change because of the extra labor needed to move goods\r
to a new warehouse, as well as implement thorough testing of Amazon's\r
software. The chart below shows how as the percentage of indirect to direct\r
hours increased, the outbound rate decreased.\r
\r
.. figure:: charts/indirect_out_vs_outbound_percent.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Indirect Labor Compared to Outbound Rate\r
\r
   Indirect labor and outbound rate over time. Each line represents a\r
   percentage based on the first week of 2011. While indirect to direct labor\r
   increased to over 160% compared to the fist week, outbound rate decreased\r
   to under 60% compared to the first week.\r
\r
The percentage of indirect to direct labor increased at about 3% a\r
month, starting at approximately 25% and peaking at approximately\r
55% right after the cutover, though without the spike, the percentage\r
would have reached a maximum of approximately 44%. Since the cutover,\r
the percentage has declined. This doesn't indicate so much that ZFC\r
decreased its indirect labor as that it increased its direct labor for\r
peak season.\r
\r
At the same time, the increase in indirect labor does not explain the decrease\r
in throughput rate, as the following graph shows. \r
\r
.. figure:: charts/direct_vs_total_outbound2_arrows.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Direct vs. Total Rate\r
\r
   Rate of all processes, with indirect hours, and with indirect hours\r
   removed.\r
\r
The overall line shows the number of units processed per man hour. The\r
direct line shows the units processed per direct man hour, or the\r
total hours required minus the indirect hours required. Since rate is\r
determined by units divided by hours, the direct rate will always be\r
higher, since it reduces the size of the denominator. The arrows shows\r
the affect of indirect labor. If the indirect hours are zero, the two\r
lines meet. As the indirect labor increases, the arrows get longer,\r
and the overall rate declines.\r
\r
For the sake of examining the affect of the indirect hours on the\r
overall rate, we want to look at the trends (or slope) of the lines\r
compared to each other. If indirect hours accounted for the decline in\r
rate, we should see an improvement in the direct trend once these\r
indirect hours are removed. Instead of sloping down, the trend for\r
direct rates should slope up, or, at least not slope down as sharply.\r
In fact, the graph shows that the rates with and without indirect\r
hours run parallel to each other. Put another way, indirect hours were\r
used effectively. \r
\r
We can also compare the indirect to total labor for years 2010 and\r
2011. Note that there is no difference.\r
\r
.. figure:: charts/indirect_out_vs_total_2010_2011.png\r
   :alt: Percentage of Indirect to Total Labor\r
   :height: 3in\r
\r
   Percentage of indirect to direct labor. There is only .7% difference\r
   between the two years.\r
\r
Last, we can compare the direct rates of both years, and the total\r
rates of both years. Again, there is no difference\r
\r
.. figure:: charts/direct_vs_total_2010_2011.png\r
   :alt: Throughput, 2010, 2011, with indirect removed.\r
   :width:  5in\r
   :height:  7in\r
\r
The picture for inbound looks much the same, with a slight difference. \r
\r
.. figure:: charts/direct_vs_inbound_total_2010_2011.png\r
   :alt: Direct Labor vs. Total\r
   :width:  5in\r
   :height:  7in\r
\r
Direct rate and total rate are relatively close to each other.\r
However, the throughput (overall) rate diverges from the direct rate,\r
indicating that indirect hours had an impact on the overall rate. In\r
fact, the percentage of indirect to total hours increase drastically\r
in 2011.\r
\r
\r
.. figure:: charts/indirect_inbound_2010_2011.png\r
   :alt: Percentage of Indirect to Total Labor\r
   :width:  5in\r
   :height:  7in\r
\r
\r
This change occurred in large part because ZFC recategorized the\r
indirect and direct labor. For example, returns counted as direct\r
labor the banding process, but later in the year, categorized this\r
process as indirect. \r
\r
\r
\r
Problem Solving\r
=================\r
\r
Hours for problems increased for problem solving from 2010.\r
\r
.. figure:: charts/problem_solve_2010_2011.png\r
   :alt: Total Hours for Problem Solving, 2010, 2011\r
   :width:  5in\r
   :height:  3.5in\r
\r
\r
With 95% significance, there is a 1.5% increase for weeks 38-52 from\r
2010 to 2011. With 95% significance, there is a 1.4% increase from\r
weeks 1-37 to weeks 38-52 for 2011. \r
\r
There is no statistical significant change for weeks 1-37 for years\r
2010 and 2011.\r
\r
The total hours for 2011 are 2,335,137. Multiply this by .015 to get \r
35027 hours. Multiply 35027 times $16.10 an hour to get a cost of \r
$563,935.00\r
\r
Note: if you take away the peak for weeks 38-41, there is still a .96%\r
increase from 2010 to 2011.  That is still a $360,918 increase\r
\r
\r
.. put this earlier\r
\r
\r
======\r
Costs\r
======\r
\r
Outbound\r
=========\r
\r
The cost of the cutover can be estimate  by examining the hours and\r
units as the year progresses and setting the first week in January as\r
our baseline. As ZFC increases the units it processes, it should\r
increase the hours in direct proportion. So if week 10 shows a 25%\r
increase, the hours should also increase to 25%. In fact, this is the\r
case for 2010.\r
\r
.. figure:: charts/units_hours_2010.png\r
   :alt: Outbound Units and Hours, 2010\r
   :width:  5in\r
   :height:  7in\r
\r
Note how the two lines practically lie on top of each other until week\r
38. At week 38, the line for hours starts to diverge, and continues\r
to diverge drastically, reaching a peak at week 50. The divergence\r
occurs because of the ZFC business model of increasing labor beyond\r
base need in order to ensure excellent customer service. \r
\r
Year 2011 looks slightly different.\r
\r
.. figure:: charts/units_hours_2011.png\r
   :alt: Outbound Units and Hours, 2011\r
   :width:  5in\r
   :height:  7in\r
\r
Again, the lines *nearly* lie on top of each other until week 38.\r
However, the slight space between the lines represents the affect of\r
the cutover. Starting in June, the hours increased greater than the units.\r
This divergence represents inefficiency, or cost. If the units\r
increased 25%, but the hours increased 30%, then ZFC used an extra 5%\r
in labor. We can calculate the actual number of hours by multiplying\r
the extra percent by the hours in January. \r
\r
In addition, we have to adjust for weeks 38 through 41. These weeks\r
clearly fall within the cutover, but also fall within the peak period.\r
Simply subtracting the two lines for this period will exaggerate the\r
cost, since, given the ZFC business model, hours are expected to be\r
higher. Instead, the previous year serves a baseline. For weeks 38, 39, 40,\r
and 41 in 2010, the hours were higher by 18%, 19%, 39%, and 47%. For\r
the same weeks in 2011, the differences were 241%, 431%, 375%, and\r
298%.  Subtracting the weeks in 2010 from 2011 yields a corrected\r
amount:\r
\r
241% - 18% = 233%\r
\r
431% - 19% = 412%\r
\r
375% - 39% = 336%\r
\r
298% - 47% = 251%\r
\r
The following table summarizes the extra hours, for weeks 25 through\r
42, the period affected by the cutover.\r
\r
.. class:: cutover-costs\r
.. csv-table:: Extra Hours, Outbound \r
     :file: tables/extra_hours_outbound.csv\r
     :header-rows: 1\r
\r
There were 86,583 extra hours. 86,583 |multiply| $16.10 amounts to $1,393,983.  \r
\r
The following graph magnifies the critical area to show the extra\r
hours. The gray area represents the extra costs.\r
\r
.. figure:: charts/outbound_costs.png\r
   :alt: Costs for Outbound\r
   :width:  5in\r
   :height:  7in\r
\r
\r
Inbound\r
=========\r
\r
Costs can be calculated the same way for inbound, with a slight change.\r
Since returns suffered inefficiencies not related to the Amazon WMS,\r
these will be taken out of the calculations.\r
\r
.. figure:: charts/units_hours_inbound_2010.png\r
   :alt: Inbound Units and Hours, 2010\r
   :width:  5in\r
   :height:  7in\r
\r
2010 shows that hours did not always increase in direct proportion to\r
the increase in units. However, the average for the weeks before\r
cutover show that if anything, ZFC increased its efficiency (increased\r
processing units more than hours), so can can safely assume the same\r
for 2011, since any mistake will underestimate costs.\r
\r
.. figure:: charts/units_hours_inbound_2011.png\r
   :alt: Inbound Units and Hours, 2011\r
   :width:  5in\r
   :height:  7in\r
\r
The following table summarizes the extra hours, for weeks 25 through\r
42, the period affected by the cutover.\r
\r
.. class:: cutover-costs\r
.. csv-table:: Extra Hours, Outbound \r
     :file: tables/extra_hours_inbound.csv\r
     :header-rows: 1\r
\r
The costs are found by the area under the curve. The extra hours are\r
65,900. 71,544 |multiply| $16.10 amounts to $1,060,989.00\r
\r
\r
The following graph magnifies the critical area to show the extra\r
hours. The gray area represents the extra costs.\r
\r
.. figure:: charts/inbound_cost.png\r
   :alt: Inbound Units and Hours, 2010\r
   :width:  5in\r
   :height:  7in\r
\r
\r
The costs for both inbound and outbound is $2,454,972.00\r
\r
\r
\r
\r
Predicted Costs for 2012\r
========================\r
\r
ZFC conducted a study to determine the effect of some of the\r
processes. The following graph and table summarize these estimates.\r
\r
.. figure:: charts/total_costs.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Predicted Costs for Several Processes\r
\r
   Predicted costs for several processes.\r
\r
.. class:: projected-summary\r
.. csv-table:: Summary of Projected Costs, 2012 \r
     :file: tables/projected_summary_costs.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Summary of predicted costs for 2012, for some processes.\r
\r
\r
_________\r
Returns\r
_________\r
\r
Because ZFC does not know all the details of the FCSW return process, it cannot completely\r
predict the costs. However, it does know the indirect labor costs caused by two additional\r
steps. Under FCSW, unloading cartons from the trailer requires that the tracking number\r
be scanned. In addition, return items must be released to the conveyor, either directly on\r
in a tote, requiring a bar code be scanned.\r
\r
The following two tables estimate the change in labor rate and the change in costs caused\r
by the transition to FCSW.\r
\r
.. figure:\: num 12\r
\r
\r
.. figure:: charts/projected_rate_returns.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Predicted Rates for Returns\r
\r
   Predicted rates for returns.\r
\r
\r
\r
\r
\r
____________\r
Receiving\r
____________\r
\r
As with returns, FC does not know all the details for the receiving process and cannot\r
completely predict changes. However, FC can predict impact for labor for the additional\r
step of retrieving a valid identification number to associate incoming cartons with an\r
Inbound Shipment Delivery (ISD). FCSW acquires this number in one of two ways:\r
\r
1. FCWS scans the SSCC18 bar code or manual identification of the Amazon PO on\r
   the carton. \r
\r
2. If a vendor does not send an AISN (or does not include an SSCC18 on the\r
   carton); and if the vendor still uses legacy ZZZ-PO codes, the legacy\r
   ZZZ-PO must be entered or scanned using an additional tool that translates\r
   the original ZZZ-PO into the appropriate Amazon PO. This number is printed\r
   to a label, which is then applied to the carton. \r
\r
The following two tables estimate the change in labor rate and the change in costs caused\r
by the transition to FCSW.\r
\r
.. figure:: charts/projected_rate_receive.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Predicted Receiving Rates \r
\r
   Predicted receiving rates per hour for Zappos vs. Zappos FCSW for 2012\r
\r
\r
\r
________________\r
Static Picking\r
________________\r
\r
There will be some efficiency gains in the static picking process due to an\r
increase in pick density, as the current FIFO (First In First Out)\r
requirement does not exist in FCSW. Based upon analysis that was performed in\r
the static area of quad 3 (in W2) that compared pick rates from the end of\r
February (when areas were less dense) with rates at the end of April (when\r
areas were more dense) along with reviewing the current pick rates in SDF6, FC\r
estimates FCSW will improve picking rates by 4%.\r
\r
The following two tables estimate the change in labor rate and the change in costs caused\r
by the transition to FCSW.\r
\r
.. figure:: charts/projected_rate_static_pick.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: Projected Rate for Static Picking, Pre- and Post-Cutover.\r
\r
   Predicted static picking rates per hour for Zappos vs. Zappos FCSW for 2012\r
\r
\r
\r
______________________________\r
Receiving Exception Handling\r
______________________________\r
\r
There will not be any efficiency gains from the exception process itself, but there will\r
be an overall cost savings due to a reduction in volume of goods moved through the\r
exception handling process. Currently, three types of exceptions go through exception\r
handling process:\r
\r
FCSW physically handles only the last of these exceptions, catalog related information\r
defects, while treating the other two as RPIs to be routed to putaway and stored in\r
unsellable locations until auto-resolved by the appropriate buying teams.\r
\r
Below is an illustration of this change in volume as well as the cost associated with this\r
change in the process.\r
\r
\r
.. figure:: charts/projected_exceptions_vol.png\r
   :height: 2.6in\r
   :width: 5.73in\r
   :alt: predicted Exceptions Handling Volume\r
\r
   Predicted exception handling volume for Zappos vs. Zappos FCSW for 2012\r
\r
\r
_____________________________\r
Remaining Analysis Summary\r
_____________________________\r
\r
Currently, ZFC does not have enough details about FCSW to effectively\r
determine process gains or losses for the following: static putaway; carousel\r
putaway; tote picking;carousel picking; singulate (induction); multi binning;\r
multi packing; and Panda / SLAM, truck load. The physical steps for these\r
processes appear similar as they exist today, but as ZFC better understands\r
these operations under FCSW, and confirms and finalizes procedures, it can\r
conduct the appropriate analysis.\r
\r
\r
.. class:: appendix\r
\r
====================================\r
Tables of Projected Rates and Costs\r
====================================\r
\r
\r
.. class:: projected-costs\r
.. csv-table:: Projected Rates and Costs for Returns\r
     :file: tables/projected_rates_returns.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for Projected Rates and Costs for Returns, 2012.\r
\r
.. class:: projected-costs\r
.. csv-table:: Projected Rates and Costs for Receiving\r
     :file: tables/projected_rates_receive.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for Projected Rates and Costs for Receiving, 2012.\r
\r
.. class:: projected-costs\r
.. csv-table:: Projected Rates and Costs for Static Picking\r
     :file: tables/projected_rates_static_picking.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for Projected Rates and Costs for Static Picking, 2012.\r
\r
.. class:: projected-exceptions\r
.. csv-table:: Projected Volume for Exceptions Handling\r
     :file: tables/projected_exceptions_volume.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for Projected Volume for Exceptions, 2012.\r
\r
\r
.. class:: appendix\r
\r
====================================================\r
Tables of Rates of Productivity Pre and Post Cutover\r
====================================================\r
\r
\r
.. class:: long-metrics\r
.. csv-table:: Carousel Picking 2010-2011\r
     :file: tables/carousel_picking.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for Carousel picking, 2010-2011.\r
\r
.. class:: long-metrics\r
.. csv-table:: Static Picking 2010-2011\r
     :file: tables/static_picking.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for Static picking, 2010-2011.\r
\r
.. class:: long-metrics\r
.. csv-table:: Singulate 2010-2011\r
     :file: tables/singulate.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the singulation process, 2010-2011. The singulation process did\r
    not exist before week 24 of 2011.\r
\r
.. class:: long-metrics\r
.. csv-table:: Multis 2010-2011\r
     :file: tables/multis.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the multis process, 2010-2011. \r
\r
.. class:: long-metrics\r
.. csv-table:: Singles 2010-2011\r
     :file: tables/singles.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the singles process, 2010-2011. \r
\r
.. class:: long-metrics\r
.. csv-table:: Shipping 2010-2011\r
     :file: tables/shipping.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the shipping process, 2010-2011. \r
\r
.. class:: long-metrics\r
.. csv-table:: Outbound 2010-2011\r
     :file: tables/outbound.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the outbound process, 2010-2011. \r
\r
.. class:: long-metrics\r
.. csv-table:: Receive 2010-2011\r
     :file: tables/receive.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the receive process, 2010-2011. \r
\r
.. class:: long-metrics\r
.. csv-table:: Carousel Putaway 2010-2011\r
     :file: tables/carousel_putaway.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the carousel putaway process, 2010-2011. \r
\r
.. class:: long-metrics\r
.. csv-table:: Static Putaway 2010-2011\r
     :file: tables/static_putaway.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the static putaway process, 2010-2011. \r
\r
.. class:: long-metrics\r
.. csv-table:: Returns 2010-2011\r
     :file: tables/returns.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for the returns process, 2010-2011. \r
\r
.. class:: long-metrics\r
.. csv-table:: Inbound 2010-2011\r
     :file: tables/returns.csv\r
     :header-rows: 1\r
\r
.. container:: caption\r
\r
    Data for all inbound processes, 2010-2011. \r
\r
\r
.. |multiply| unicode:: U+02715 \r