Goldman Sachs Research
Tracking U.S. Supply Chain Congestion
GS Supply Chain Congestion Scale: May 1st: Scale Teeter-Totters Back to '2' from '1' Amid Weekly Volatility
1 May 2023 | 4:00PM EDT | Research | Equity| By Jordan Alliger and others
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Data available on request.
Scale is based solely off weekly metrics to give more granularity on high frequency data indications; see Appendix for scale that combines weekly and monthly metrics
Source: Goldman Sachs Global Investment Research
Our weekly bottleneck scale rose back to a '2' this week following last week's tick down to '1'; this week, the absolute level of our congestion index ticked up ~9% w/w (Exhibit 1). The number of container ships waiting to dock and unload goods along the West Coast remained at zero for the 22nd consecutive week, but East Coast backlogs increased from 4 to 7 (note that we slightly overweight ship backlogs when calculating the index; Exhibit 6). West Coast intermodal rail performance was mixed on the back of decelerating BNSF intermodal traffic (-20% YoY) and higher BNSF dwell (13.6 hours versus 7.3 hours last week), though UNP traffic was better (-3.6% YoY versus -8.0% last week) as dwell went slightly lower (12.2 hours versus 14.3 hours last week). Overall, chassis dwell time at the ports did tick up ~6% w/w, partly contributing to this week's scale ticking back up to '2'; ocean container rates also rose from ~$1k per forty foot equivalent unit to ~$1.7k, further contributing to the scale uptick.
While this week's tick back up to '2' is disappointing, it somewhat reflects weekly bottleneck volatility; we still think we can exit April with a combined bottleneck scale implying supply chains in line with levels seen prior to March 2020 (give or take a few percentage points).

Exhibit 1: Our weekly composite increased (+9.3% w/w) in the most recent week

GS Weekly Bottleneck Index, Feb 2020 - Apr 2023
1. Our weekly composite increased (+9.3% w/w) in the most recent week. Data available on request.
Source: Goldman Sachs Global Investment Research

Exhibit 2: Our average bottleneck score for April is 1.7 - down significantly from the Dec21/Jan22 peak, and nearly in line with pre-pandemic levels

GS Weekly Congestion Scale, Scored by Month*
2. Our average bottleneck score for April is 1.7 - down significantly from the Dec21/Jan22 peak, and nearly in line with pre-pandemic levels. Data available on request.
*Numbers reflect the average weekly score seen in each respective month
Source: Goldman Sachs Global Investment Research
As a reminder (and to help reiterate why and how we construct the index), please refer to the Appendix following Exhibit 17. Additionally, for further clarity on tracked congestion metrics, please refer to the glossary following Exhibit 19.

Transport Subsectors to Watch as Congestion Eases

The key question remains focused on whether the last stumbling blocks around congestion ease in the US - notably the still-full warehouses, as well as the East Coast port backlogs. Should this continue to mitigate, then it is conceivable we could sustain the index being back to a '1' over 1H23. As suspected could happen when we first introduced the index, labor and equipment availability is improving alongside demand moderation, both helping the fall in the index.
With the dramatic easing that already took place in 2022, we think from a transport subsector perspective – we would look to the US Rails (NSC, UNP, CSX) and intermodal marketing companies (SNDR, JBHT) as being the prime beneficiaries should congestion stay easier, as these networks have generally been amongst the most adversely impacted by supply-chain problems – both from operational constraints and underperformance on volumes due to an inability to translate high consumer demand into actual throughput. The truckload sector, on the other hand, has benefited significantly from elevated spot rates due to constraints on truck capacity. Should the labor and equipment shortages see further relief due to moderating congestion, this could open the pressure relief valve as presumably additional effective truck capacity would be created through more normalized goods flow.

Indicator Updates

Of the metrics we track (Exhibit 3), we provide updates for the weekly and monthly variables below (Exhibit 4 - Exhibit 5).

Exhibit 3: Tracked Congestion Metrics

3. Tracked Congestion Metrics. Data available on request.
Source: Goldman Sachs Global Investment Research

Exhibit 4: Bottleneck metrics were more mixed this week; certain overweighted variables (Ship Backlog, dwell times) deterioarted, pushing the index back slightly above '1'

4. Bottleneck metrics were more mixed this week; certain overweighted variables (Ship Backlog, dwell times) deterioarted, pushing the index back slightly above '1'. Data available on request.
As of 3/28/22, we added and backdated our estimates for the East and Gulf Coast container ship backlog
Source: Marine Exchange of Southern California, AAR, STB, Freightos, Pool of Pools, Pacific Merchant Shipping Association, Port of Long Beach, Port of Oakland, Port of Los Angeles, LMI, US Bureau of Labor Statistics, IHS Markit, Refinitiv Eikon, compiled by Goldman Sachs Global Investment Research

Exhibit 5: Most monthly bottleneck metrics improved sequentially in March

5. Most monthly bottleneck metrics improved sequentially in March. Data available on request.
Source: Marine Exchange of Southern California, AAR, STB, Freightos, Pool of Pools, Pacific Merchant Shipping Association, Port of Long Beach, Port of Oakland, Port of Los Angeles, LMI, US Bureau of Labor Statistics, IHS Markit, compiled by Goldman Sachs Global Investment Research

Weekly Indicator Update

Anchored Container Ships

  • West Coast backlogs remained unchanged at 0 this week but East Coast backlogs increased from 4 to 7.

Exhibit 6: 7/0* container ships backed up this week on the East/West Coast

West vs. East Coast Container Ship Backlog, Weekly Average, Feb 2020 - Apr 2023
6. 7/0* container ships backed up this week on the East/West Coast. Data available on request.
*East Coast is estimated via satellite data - includes container ships sitting for more than 3 days within 140 miles of US ports to the right of longitude 100 (i.e., Gulf and East Coast)
Source: Marine Exchange of Southern California, Refintiv Eikon, Goldman Sachs Global Investment Research

Rail Intermodal Trends

  • West Coast Class 1 Rails' (Union Pacific and Burlington Northern Santa Fe) combined intermodal traffic was largely unchanged in terms of YoY growth in reporting week 16 of 2023, as better traffic at UNP was offset by worse traffic at BNSF.

    • BNSF intermodal traffic at -20.2% YoY this week vs. -18.9% YoY last week; UNP intermodal traffic at -3.6% YoY vs. -8.0% YoY last week.

    • Note that intermodal volume declines have continued into April (Exhibit 8).

Exhibit 7: West Coast Class 1 Rails' Intermodal Volume Growth, Week 1 - Week 52

YoY % growth
7. West Coast Class 1 Rails' Intermodal Volume Growth, Week 1 - Week 52. Data available on request.
Source: AAR, Data compiled by Goldman Sachs Global Investment Research

Exhibit 8: Intermodal volume declines (UNP and BNSF) have continued into April

West Coast Class 1 Rail Intermodal Traffic YoY % Growth
8. Intermodal volume declines (UNP and BNSF) have continued into April. Data available on request.
Source: AAR, Data compiled by Goldman Sachs Global Investment Research
  • West Coast Class 1 Rail intermodal speed improved, but dwell was mixed, in the most recent week.

    • BNSF intermodal dwell up to 13.6 hours from 7.3 last week; UNP dwell down to 12.2 hours from 14.3.

    • On intermodal velocity, BNSF +12.7% YoY vs. +8.3% YoY last week; UNP at +8.4% YoY vs. +5.5% YoY last week.

Chassis Dwell Time

  • Chassis dwell is showing sequential improvement when comparing the April data to the March average – as per Exhibit 9. Dwell metrics improved in the most recent week.

    • Average street dwell time for 20ft shipping container chassis was 5.9 days in reporting week 16, up from 5.4 hours in week 15.

    • Street dwell for 40/45ft container chassis was 6.0 days in week 16, down from 6.2 days week 15.

    • Chassis terminal dwell time for 20/40ft containers was at 10.0/6.6 days in week 16 versus 9.0/7.1 days in week 15.

Exhibit 9: Dwell for the more typical 20ft container chassis is showing sequential improvement in April

Chassis Street Dwell Time (20ft Containers)
9. Dwell for the more typical 20ft container chassis is showing sequential improvement in April. Data available on request.
Dwell time shown in days
Source: Pool of Pools

Ocean Shipping Rates

  • Ocean rates' YoY growth was better than -90% YoY for the first time in 14 weeks. The third week of April saw ocean rates tick back up to ~$1.7k (-89% YoY) from ~$1k, implying levels slightly above to more inline with Pre-Covid (versus below Pre-Covid levels for the last two months).

    • China to North America West Coast: ocean shipping rates -89% YoY in reporting week 16 versus -94% in week 15.

Exhibit 10: Ocean Container Shipping Rates, China/East Asia to North America West Coast

10. Ocean Container Shipping Rates, China/East Asia to North America West Coast. Data available on request.
Rate is $ per FEU (Forty-Foot Equivalent Unit)
Source: FBX

Monthly Indicators (March Data)

San Pedro's Bay Container Dwell

  • Container weighted average dwell time declined slightly to 2.5 days in March from 2.9 days in February at San Pedro's Bay, implying dwell down 60% YoY.

  • 6% of the San Pedro's Bay containers were dwelling for more than 5 days in March -- this is down from ~50% at peak congestion levels and down slightly from February.

  • Rail container dwell moved down to 4.1 days in March from 5.8 days in February.

Exhibit 11: Container Weighted Average Dwell Time at San Pedro's Bay, Days

11. Container Weighted Average Dwell Time at San Pedro's Bay, Days. Data available on request.
Source: Pacific Merchant Shipping Association

Exhibit 12: % of Containers Dwelling More than 5 Days

12. % of Containers Dwelling More than 5 Days. Data available on request.
Source: Pacific Merchant Shipping Association

Exhibit 13: Rail Container Dwell Time, Days

13. Rail Container Dwell Time, Days. Data available on request.
Source: Pacific Merchant Shipping Association

"Big Three" West Coast Ports' Inbound Loaded Containers

  • Total inbound containers for the Ports of LA, Long Beach, and Oakland -35% YoY in March.

Exhibit 14: West Coast Ports' Inbound Loaded Containers -35% YoY in March

14. West Coast Ports' Inbound Loaded Containers -35% YoY in March. Data available on request.
Source: Port of Long Beach, Port of Los Angeles, Port of Oakland

Door to Door Shipping, China to US

  • It was taking an average of 53 days to ship (door-to-door) from China to the US in March, largely unchanged from the prior 3 months.

Exhibit 15: Door to Door Shipping Days, China to US

15. Door to Door Shipping Days, China to US. Data available on request.
Source: Freightos

Trucking Employee Count

  • Truck transportation employee count remains above pre-pandemic highs (+4.7% above), with YoY growth averaging about 4% over the past six months. March's employee count increased 0.4% sequentially after declining 0.3% in February.

Exhibit 16: Total Truck Transportation Employee Count, Seasonally Adjusted

16. Total Truck Transportation Employee Count, Seasonally Adjusted. Data available on request.
Source: US Bureau of Labor Statistics

LMI Capacity and Utilization

  • LMI Transportation Capacity Index

    • Transportation capacity remained in expansionary territory in March, and the rate of expansion accelerated relative to February. March's reading was 71.4 versus 70.4 in February.

  • LMI Warehouse Capacity Index

    • Warehouse capacity remained expansionary in March after February rose above contraction territory for the first time in nearly 2.5 years. March's reading of 58.2 expanded from 56.6 in February.

  • LMI Warehouse Utilization Index

    • Warehouse utilization continued to increase in March with an above-50 reading. March's 65 reading fell from February's 70.3 reading, indicating a slower rate of utilization growth.

PMI Supplier Delivery Times

  • Delivery times contracted on an absolute basis (i.e., above 50 indicates contracting delivery times) given the 55.1 reading in March; this implies delivery times are growing nearly 2x slower than at this same time last year.

Exhibit 17: PMI: Manufacturing Suppliers' Delivery Times, YoY, Seasonally Adjusted

17. PMI: Manufacturing Suppliers' Delivery Times, YoY, Seasonally Adjusted. Data available on request.
Source: IHS Markit

Appendix

Given the importance supply chain fluidity has on retailers, consumer goods companies, inflationary pricing, etc., we think this scale’s importance is tied most directly to the pace at which supply chain congestion is on the mend. To this end, we look at a variety of variables that we think tie directly, or in some cases indirectly, to overall congestion; including ships at anchor, days to deliver, various dwell times, intermodal volume and velocity statistics amongst others. Aggregating this data, we create the Supply Chain Congestion Scale – an attempt to quantify the balance between supply chains being “Fully Bottlenecked” and “Fully Open,” relative to the pre-pandemic benchmark we chose as Feb 3rd, 2020. Basically, how fluid is the overall transport logistics network.
To determine the position of the Legacy Congestion Scale (1-10), we calculate growth or decline in each category (monthly and weekly variables) relative to pre-congestion levels, overweighting certain categories we deem most directly tied to supply chain bottlenecks (i.e., ships anchored off the ports of LA and Long Beach, shipping container and chassis street dwell times, door-to-door shipping days from China to US), and scale it based on our Composite Scale (Exhibit 19).
We publish the weekly scale on Monday PM/Tuesday AM to relay leading edge data that will inform the roughly one month lagged composite (i.e., we will update the weekly scale every week and the legacy scale will be updated monthly). Looking at the two charts, it is generally clear that the weekly composite should have good predictive ability as to the eventual direction of the monthly composite (which includes more encompassing variables than pure weekly ones to provide strong confirmation on congestion direction), and this is confirmed by the similarly high R^2 values seen in Exhibit 18.

Exhibit 18: The weekly composite index (light blue) leads the monthly (dark blue); expect future monthly updates to confirm recent weekly trends

18. The weekly composite index (light blue) leads the monthly (dark blue); expect future monthly updates to confirm recent weekly trends. Data available on request.
Source: Goldman Sachs Global Investment Research

Exhibit 19: Our March monthly reading averaged 104, indicating a bottleneck score just above '1' when looking at all metrics (weekly and monthly combined)

Weekly + Monthly Combined Congestion Scale*
19. Our March monthly reading averaged 104, indicating a bottleneck score just above '1' when looking at all metrics (weekly and monthly combined). Data available on request.
*We rescaled our index on 3/28/2022 to account for higher-than-anticipated peak bottleneck levels
Source: Goldman Sachs Global Investment Research

Exhibit 20: GS Legacy Supply Chain Congestion Scale (incorporates monthly and weekly data)

20. GS Legacy Supply Chain Congestion Scale (incorporates monthly and weekly data). Data available on request.
Source: Goldman Sachs Global Investment Research

Exhibit 21: GS Weekly Supply Chain Congestion Scale (High-Frequency Data)

21. GS Weekly Supply Chain Congestion Scale (High-Frequency Data). Data available on request.
Source: Goldman Sachs Global Investment Research

Glossary:

  1. West Coast container ship backlog: tracks the number of container ships waiting to dock at the ports of LA and Long Beach; we add the number of ships anchored within 40 miles of the coast to the number of ships slow-steaming to port (AKA: ships loitering farther offshore) to get a better depiction of the true container ship backlog.

  2. East Coast container ship backlog: estimates the number of container ships waiting to dock at the East and Gulf Coast ports in the US; based on satellite image data technology (Eikon), we add the number of container ships sitting for at least three days within 140 miles of a US port (accounts for ships to the right of 100 degrees of longitude to account for East Coast).

  3. Intermodal traffic: tracks Y/Y intermodal carload volume growth for West Coast Class 1 Rails (BNSF and UNP). Accelerating volumes would indicate a more fluid supply chain for our purposes as more goods get moved through the system.

  4. Intermodal velocity: tracks the average speed of the intermodal railcars (BNSF and UNP).

  5. Intermodal dwell: tracks the average number of hours an intermodal railcar is idle (i.e., how long the car spends waiting at a terminal).

  6. Chassis dwell: refers to the average time for chassis waiting on-terminal and on-street.

  7. Rail container dwell: refers to the number of days a container waits to depart from a rail facility after being unloaded from an ocean carrier.

  8. Container weighted average dwell: refers to the number of days a container stays at a marine terminal after being unloaded from an ocean carrier and taken off the premises by a truck.

  9. Ocean shipping rates: refers to the average cost of shipping a container by ocean; we specifically track the cost of shipping from East Asia to the US West Coast via the FBX01 index from Freightos.

  10. Big Three West Coast Ports' inbound loaded containers: refers to the Y/Y growth that the Big Three West Coast ports (LA, Long Beach, and Oakland) see in inbound loaded containers (i.e., how many more goods are moving through the port versus the same period last year).

  11. PMI manufacturing supplier delivery time index: readings of 50 indicate no change in delivery times versus the prior month; readings above 50 indicate delivery times improved (faster supply chain) and readings below 50 indicated delivery times deteriorated sequentially (more delayed supply chain). The index is a result of IHS Markit's PMI business survey which asks purchasing managers, "Are your suppliers' delivery times slower, faster or unchanged on average than one month ago?"

  12. China-to-US door-to-door shipping transit time: sourced from Freightos, this metric tracks the number of days it takes for a good to reach final destination (on average) once an order is placed and accepted (i.e., door-to-door shipping is not necessarily port-to-port as it also captures delivery times from port to final destination).

  13. GS Data Works leverages alternative data sources and advanced analysis techniques to create unique data-driven insights across Global Investment Research. GS Data Works analysis (East Coast container ship backlog estimates) provided by Dan Duggan, Ph.D., Aditi Singh, and Parag Agrawal.

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