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This letter contains our response to comments received from the staff (the “Staff”) of the U.S. Securities and Exchange Commission (the “Commission”) by letter dated July 28, 2020 (the “Letter”) regarding the filing listed above by United Parcel Service, Inc. (references to the “Company” or “UPS” include any or all of United Parcel Service, Inc. and its subsidiaries). We note that, pursuant to a telephone conversation on August 3, 2020 between the Staff and representatives of the Company, the Staff granted the Company an additional ten business days to respond to the Staff’s letter.

including the impact of changes in accounting estimates on your results of operations. Your three changes in accounting estimates in 2019 increased earnings per share by $0.98 per share and your primary and diluted earnings by over 24%. Your change in accounting estimate in 2018 increased earnings per share by $0.26 per share and your primary and diluted earnings by 5%. Please refer to Item 303(a) of Regulation S-K.

The Company acknowledges the Staff’s comment and, in response, the Company has taken disclosures contained elsewhere in Management’s Discussion and Analysis in the Company’s Form 10-K for the year ended December 31, 2019 (the “2019 Form 10-K”) and integrated them in the Overview in the following format to reflect how the Overview would have appeared if this content were addressed there as well. The Company respectfully advises the Staff that it will add disclosure and analysis in its future filings, including in the Overview, regarding the impact of changes in accounting estimates on its results of operations, to the extent material.

During the year, we continued to successfully execute on our strategies and deliver on our commitments, including of improved network efficiency and continuous transformation to stay ahead of market changes. We believe our multi-year investment strategy is positioning us well for the future, including allowing us to support the needs of our customers, create opportunities for our employees and reward our shareowners.


	Year Ended December 31,						$ Change	% Change
	2019		2018		2019/2018		2019/2018
Revenue (in millions)	$	74,094	$	71,861	$	2,233	3.1%
Operating Expenses (in millions)	66,296		64,837		1,459		2.3%
Operating Profit (in millions)	$	7,798	$	7,024	$	774	11.0%
Operating Margin	10.5%		9.8%
Net Income (in millions)	$	4,440	$	4,791	$	(351)	(7.3)%
Basic Earnings Per Share	$	5.14	$	5.53	$	(0.39)	(7.1)%
Diluted Earnings Per Share	$	5.11	$	5.51	$	(0.40)	(7.3)%

Average Daily Package Volume (in thousands)	21,880		20,677				5.8%
Average Revenue Per Piece	$	10.87	$	10.98	$	(0.11)	(1.0)%

•Average revenue per piece is dependent upon base rates, customer and product mix, average billable weight per piece, fuel surcharge rates and currency. Average revenue per piece decreased as a result of changes in customer and product mix, and lower average billable weight per piece in our U.S. Domestic Package segment. Currency movements negatively impacted revenue per piece in our International Package segment.

•Operating profit and operating margin increased with growth and margin expansion in all segments. Consolidated operating profit included the impact of a reduction in depreciation expense of $212 million due to changes in the estimated useful lives of certain of our property, plant and equipment and a reduction in expense of $94 million due to adjustments to our self-insurance reserves, each as described below.

•We reported net income of $4.440 billion and diluted earnings per share of $5.11, which included a positive impact of $855 million or $0.98 per share from the changes in estimates set out above and a refinement in the calculation of the discount rate used to measure our U.S. pension and postretirement benefit plans discussed below. Adjusted diluted earnings per share was $7.53 after adjusting for the after-tax impacts of the following:

Revenue growth was attributable to our U.S. Domestic segment, slightly offset by declines in our International segment as well as lower revenue in our Supply Chain & Freight segment. In the U.S. Domestic segment, both volume and revenue growth were strongest in our Next Day Air product, driven by a structural shift to next day delivery within e-commerce. We expect this shift to continue. Our residential volume grew 11.3%, while commercial volume increased 2.2%. This growth was enabled by our on-going investment in automated facilities and other transformation initiatives, and we experienced growth from a number of large customers and small- and medium-sized businesses. Growth was led by our largest customer, Amazon, substantially all of which was in the U.S. Domestic segment.

In our International segment, we continued to experience a trend toward our non-premium products, with volume strongest in our Transborder Standard product. Overall volume declined slightly due to weak demand from several industry sectors and a 2018 postal strike in Canada that drove additional domestic volume which did not repeat in 2019. Currency fluctuations caused a reduction in average revenue per piece for both our Domestic and Export products. Additionally, the segment recorded a $40 million pre-tax gain in 2019 from the sale of surplus property in Canada.

Revenue in our Supply Chain & Freight segment decreased, driven by our Forwarding businesses. This decrease was due to declines in market rates and lower demand as a result of global trade uncertainties. Our Logistics businesses experienced growth, driven by healthcare and mail services. UPS Freight revenue increased slightly, as declines in volume were offset by yield management initiatives. While we have seen some positive developments in this segment in recent periods, our business may continue to be negatively impacted if global trade uncertainties persist.

Our capacity expansion projects, together with the overall increase in volume, drove U.S. average daily union labor hours up 4.7%. The increase in Next Day Air volume drove a 10.3% increase in domestic aircraft block hours, and the growth in U.S. residential deliveries led to increases in average daily delivery stops and daily delivery miles of 10.9% and 7.9%, respectively. Average cost per piece decreased slightly for the year due to our continuing investments in automation and global network efficiency. We anticipate incurring additional costs to improve our time-in-transit during 2020 that may exceed the associated revenue for the year, with a consequential impact on 2020 operating margins.

The preparation of our consolidated financial statements requires the use of estimates and assumptions that affect the reported amounts of assets and liabilities, the reported amounts of revenues and expenses and the disclosure of contingencies. We continually evaluate our estimates and make updates as appropriate. In 2019, consolidated net income was impacted by the following changes in estimates:

• As disclosed in Note 4 “Property, Plant and Equipment”, in 2018, we made prospective revisions to our estimates of useful lives for building improvements, vehicles and plant equipment, which in general had the effect of lengthening the useful lives of these assets. As a result, 2019 depreciation expense decreased $212 million and net income increased $167 million.

• Based on our historical experience of claims and settlements, in 2019 we adjusted our self-insurance reserves from the mid-point to the low end of the actuarial projected range of losses as discussed within “Critical Accounting Policies and Estimates”. This had the effect of reducing operating expenses for the year by $94 million and increasing net income for the year by $72 million.

• In 2019, in consultation with an external actuarial adviser, we refined the bond matching approach used to determine the discount rates for our U.S. pension and postretirement benefit plans. This refined approach considered the increased availability of longer duration high-quality corporate bonds, changes in the content and sources of available data and improvements in computational capabilities. As disclosed in Note 5 “Company Sponsored Employee Benefit Plans”, these refinements resulted in an increase of approximately 10 basis points in the discount rates used to measure our plans, decreasing the total projected benefit obligation at the December 31, 2019 measurement date by approximately $900 million and the resulting mark-to-market charge within other income and expense by $810 million, and increasing net income by $616 million.

discussion of the advances in technology and modeling techniques used to select the discount rate implemented in 2019. Separately, describe for us, in reasonable detail, the differences between the prior and current methodologies, and explain why you believe the current methodology provides a better estimate under your circumstances. Additionally, tell us what the discount rate would have been under the prior approach and the internal controls over financial reporting implemented along with the advanced technology and modeling techniques.

ASC 715 Compensation – Retirement Benefits (“ASC 715”), requires a plan sponsor to measure plan obligations utilizing discount rates that reflect the rate at which plan benefits could effectively be settled. In estimating those rates, ASC 715 permits plan sponsors to look to rates of return on high-quality fixed income investments currently available whose cash flows match the timing and amount of expected benefit payments. The objective of this method is to measure the single amount that, if invested at the measurement date, would provide the required future cash flows to pay benefits when due.

Consistent with ASC 715, we determine the discount rate for each of our U.S. pension and postretirement benefit plans by constructing a hypothetical portfolio of high-quality bonds that would satisfy the plan’s projected benefit obligation at the measurement date. We have worked for a number of years with a third-party actuarial consultant, Willis Towers Watson, who maintains a bond matching model to support this process.

In 2019, Willis Towers Watson completed a comprehensive periodic review of their bond matching model. The review validated maintaining the fundamental conceptual approach as well as other key aspects of the model, including the use of parameters that can be adjusted to establish the criteria for selecting an appropriate bond portfolio. Certain refinements were also made. These refinements were implemented in their model for use after October 31, 2019.


	Prior Version	Refined Version	Rationale
Bond Universe	•Primary data source: Bloomberg Generic Composite (BGN); Secondary: Bloomberg Valuation Service (BVAL) •Bonds with maturity greater than 37.5 years are excluded; any bonds with maturity greater than 30 years are treated as 30-year bonds •Minimum size: $500M outstanding for bonds with maturity less than ten years; $50M outstanding for bonds with maturity ten years or more	•Data source: BVAL •Bonds with BVAL score below a selected level may be excluded, or limits can be placed on the maximum percentage of the market value that can be below a selected level •No explicit limit on maturity and actual maturity is reflected •No minimum dollar amounts	•Based on discussions with Bloomberg, Willis Towers Watson determined BVAL is the most appropriate data source with broader fixed income coverage; has expanded significantly since introduction in 2008 •BVAL allows for exclusion of bonds for which additional support of pricing would be considered appropriate without the use of maturity and size limits •Selecting bonds without regard to outstanding issuance size, while ensuring that observable pricing data exists, better reflects how our obligations would be settled


	Prior Version	Refined Version	Rationale
Portfolio Construction	•Select bonds sequentially from longest to shortest maturities •Parameters determine allowable maturity difference between bond payment and targeted benefit payment •Reinvested cash is not explicitly bounded	•Simultaneously select entire portfolio to minimize cost of the portfolio •Parameters restrict amount of cash flow that can be carried forward to the next year; excess cash flow is not applied to settle obligations •Surplus cash carried forward is explicitly bounded	•Enhanced computational capability has enabled this approach, which results in a more optimized portfolio •This portfolio better reflects the cost of bonds at relevant maturities that match the duration of our estimated benefit cash flows, resulting in a more precise estimate of the cost to settle the obligations
Long Maturity Payments	•Discounted value of benefit payments beyond 30 years is settled rather than matching payments themselves to the portfolio payments •Yield curve reflected only to Year 30 with constant spot rates thereafter	•Threshold maturity is a parameter that can be adjusted if/when bond issuances are sufficient to match longer maturities •Full yield curve used for corporates, Treasury curve has constant spot rates after 30 years	•Provides flexibility to accommodate evolution of bond market and accommodate yield curves as input •Provides a better match of bonds to the plans’ projected cash flows

We reviewed guidance provided by Bloomberg on their BVAL scoring, and noted that a score of six or higher implies that there are recent, direct observations on the target instrument which may be either trades, executable or indicative data. We determined this would indicate sufficient relevant and reliable data for a bond to be included in our hypothetical portfolio and set the model parameter to include bonds with a score of six or higher.

We also reviewed scenarios prepared by Willis Towers Watson that first included, and then excluded, bonds according to the outstanding issuance threshold noted in the table above. We determined that, while these bonds did not significantly impact the discount rate, inclusion of such smaller issuances with an appropriate BVAL score would better reflect how we would settle our pension obligation.

We believe the improved computational capabilities reflected in the updated model, which permit the selection of bonds simultaneously rather than sequentially, reduce the risk of management bias as the bond selection process minimizes the judgment applied in the discount rate assumption. We therefore determined this enhancement improved the reliability of our estimate.

As a result of performing this review, we adjusted the selection of bonds within each portfolio. Upon examination of the revised listing, we concluded that the selected bonds conformed to the requirements of ASC 715 and that the associated cash flows appropriately matched the amount and timing of the Company’s expected benefit payments.

From the execution of these controls, we concluded that the refinements to the model, both individually and in the aggregate, resulted in a better estimate of the cost to settle our pension obligations. The refinements enhanced the relevance and reliability of the data and provided a more precise estimate of the discount rates we use to measure our plans.

The evaluation of the model was overseen by our corporate actuary. Both our corporate actuary and our external actuarial consultant are familiar with the short- and long-term aspects of defined benefit plan valuations and collectively meet the Qualification Standards of the American Academy of Actuaries to render actuarial opinions. The refinements to the bond matching model are consistent with current Actuarial Standards of Practice governing model development and validation.

In aggregate, we estimate that the refinements to the bond model had the effect of increasing the discount rates for our U.S. pension and postretirement benefit plans by ten basis points. This is less than the 25 basis point discount rate sensitivity analysis that we include within our “Critical Accounting Policies and Estimates” section of Management’s Discussion and Analysis of Financial Condition and Results of Operations in the Form 10-K.

Adopting the refinements at this time was appropriate, since this was the first time Willis Towers Watson had made the refinements available and they reflect the significant evolution of markets, data and computational capability since the prior refinements to the model. We believe this model continues to provide appropriate support for our discount rate selection process and the measurement of our plans’ obligations.

For the convenience of the Staff, expanded disclosure proposed to be included but based upon the facts and circumstances present at February 20, 2020 has been set forth below compared to that disclosed in the Company’s 2019 Form 10-K. This disclosure is included within Note 5 Company-Sponsored Employee Benefit Plans, page 78, under the heading Actuarial Assumptions. In this regard, please note that the proposed disclosures which have been added in response to the Staff’s Comment have been noted in underlined bold italics, and proposed deletions are shown with a strikethrough:

In October 2019, we refined our the bond matching approach by implementing advances in technology and modeling techniques used to determine the discount rates for our U.S. pension and postretirement plans. Following a routine, periodic review of their standard bond matching tool which we reference to support discount rates, our external consultants refined their model to reflect the increased availability of longer duration high-quality corporate bonds, changes in the content and sources of available data and improvements in computational capabilities. We believe these refinements enhance the simulation of bond portfolios that match the plans’ expected cash flows and result in a better estimate of the plan discount rates. This refinement These refinements resulted in an increase of approximately 10 basis points in the discount rates used to measure our plans, decreased decreasing the total projected benefit obligation on our consolidated balance sheet for our U.S. pension and postretirement plans at the December 31, 2019 measurement date by approximately $900 million as of December 31, 2019. Additionally, we estimate that this refinement in method decreased our and the resulting pre-tax mark-to-market charge within other income and expense by approximately $810 million, and increased increasing net income by $616 million, or $0.71 per share on a basic and diluted basis.