Our latest featured stock is an Industrials company with numerous hidden non-operating expenses. Last week alone we analyzed 303 filings.
Most investors are likely unaware of these non-operating expenses that distort GAAP numbers by lowering operating earnings. On page 19, MMM disclosed $762 million ($590 million after-tax) in litigation-related charges pertaining to environmental contamination from certain chemicals manufactured by the firm and alleged personal injury from use of some of the firm’s masks and respirator products.
On page 76, MMM disclosed charges related to restructuring actions that management undertook in the second and fourth quarters of 2019. These charges included $137 million bundled in selling, general, and administrative expenses, $72 million included in cost of sales, and $37 million of research, development, and related expenses.
Partially offsetting these expenses, MMM also disclosed an $82 million gain (on page 125) related to the sale and lease-back of an office location and manufacturing site.
After removing the impact of these adjustments, we find that MMM’s 2019 GAAP net income is understated. Furthermore, the year-over-year (YoY) decline in GAAP net income is much worse than the drop in MMM’s core earnings.
MMM’s GAAP earnings were down 15% YoY. Core earnings, a superior measure of profits, were down 7%, while economic earnings, which account for non-recurring items on the income statement and changes to the balance sheet, were down just 2% YoY. Investors relying solely on GAAP earnings get a misleading picture of the true performance of the company.
Figure 1: MMM’s Year-Over-Year Profit Decline is Overstated
Sources: New Constructs, LLC and company filings
With understated earnings, and a “Beat” Earnings Distortion Score, MMM is likely to beat consensus expectations. While MMM looks like a good bet to beat expectations, it does not necessarily represent an attractive risk versus reward opportunity over the long-term. MMM currently earns our Neutral rating, has a free cash flow yield of -3% and both its ROIC and NOPAT margin declined YoY in 2019.
Critical Details Found in Financial Filings by Our Robo-Analyst Technology
As investors focus more on fundamental research, research automation technology is needed to analyze all the critical financial details in financial filings as shown in the Harvard Business School and MIT Sloan paper, "Core Earnings: New Data and Evidence”.
Below are specifics on the adjustments we make based on Robo-Analyst findings in 3M Company’s 2019 10-K:
Income Statement: we made $2.4 billion of adjustments with a net effect of removing $992 million of non-operating expenses (3% of revenue). See all adjustments made to MMM’s income statement here.
Balance Sheet: we made $21.6 billion of adjustments to calculate invested capital with a net increase of $3.7 billion. One of the most notable adjustments was $8.1 billion (23% of reported net assets) in other comprehensive income. See all adjustments to MMM’s balance sheet here.
Valuation: we made $28.9 billion of adjustments with a net effect of decreasing shareholder value by $24.4 billion. Apart from total debt, which includes operating leases, the most notable adjustment to shareholder value was $3.8 billion in underfunded pensions. This adjustment represents 4% of MMM’s market cap. See all adjustments to MMM’s valuation here.
The Power of the Robo-Analyst
We analyzed 303 filings last week, from which our Robo-Analyst technology collected 34,744 data points. Our analyst team used this data to make 6,193 forensic accounting adjustments with a dollar value of $4.3 trillion. The adjustments were applied as follows:
- 2,467 income statement adjustments with a total value of $334 billion
- 2,653 balance sheet adjustments with a total value of $1.8 trillion
- 1,073 valuation adjustments with a total value of $2.1 trillion
Figure 2: Filing Season Diligence for the Week of February 17-23
Sources: New Constructs, LLC and company filings.
Every year in this six-week stretch from mid-February through the end of March, we parse and analyze roughly 2,000 10-Ks to update our models for companies with 12/31 and 1/31 fiscal year ends. This effort is made possible by the combination of expertly trained human analysts with what we call the “Robo-Analyst.” Featured by Bloomberg and Harvard Business School in “Disrupting Fundamental Analysis with Robo-Analysts”, our research automation technology uses machine learning and natural language processing to automate and improve financial modeling.
No Substitute for Diligence
Our technology enables us to deliver fundamental diligence at a previously impossible scale. We believe this research is necessary to uncover the true profitability of a firm and make sound investment decisions. “Core Earnings: New Data and Evidence,” a recent paper from professors at Harvard Business School and MIT Sloan, shows how our adjustments create a measure of core earnings that is more predictive of future earnings than comparable metrics from Compustat and IBES.
This article originally published on February 25, 2020.
Disclosure: David Trainer, Kyle Guske II, and Matt Shuler receive no compensation to write about any specific stock, sector, style, or theme.
 In Core Earnings: New Data & Evidence, professors at Harvard Business School (HBS) & MIT Sloan empirically show that our measure of “core earnings” is superior to “Street Earnings” from Refinitiv’s IBES, owned by Blackstone (BX) and Thomson Reuters (TRI), and “Income Before Special Items” from Compustat, owned by S&P Global (SPGI).
 Harvard Business School features the powerful impact of our research automation technology in the case New Constructs: Disrupting Fundamental Analysis with Robo-Analysts.