Carlos Rodriguez - Automatic Data CEO and President and Director

ADP Stock  USD 295.57  1.24  0.42%   

CEO

Mr. Carlos A. Rodriguez is President, Chief Executive Officer, Director of Automatic Data Processing, Inc. Prior to his appointment in November 2011 to President and Chief Executive Officer, he served as President and Chief Operating Officer from May 2011 to November 2011, and as President, Employer Services International National Account Services, ADP Canada, and GlobalView and Employer Services International, from March 2010 to May 2011. since 2011.
Age 60
Tenure 13 years
Address One ADP Boulevard, Roseland, NJ, United States, 07068
Phone973 974 5000
Webhttps://www.adp.com
Rodriguez joined ADP in 1999. Prior to his appointment in November 2011 to President and Chief Executive Officer, he served as President and Chief Operating Officer from June 2011 to November 2011, as President, Employer Services National Account Services, Canada, and GlobalView and Employer Services International, from 2010 to May 2011, and as President, Employer Services Small Business Services from 2007 to 2010.

Carlos Rodriguez Latest Insider Activity

Tracking and analyzing the buying and selling activities of Carlos Rodriguez against Automatic Data stock is an integral part of due diligence when investing in Automatic Data. Carlos Rodriguez insider activity provides valuable insight into whether Automatic Data is net buyers or sellers over its current business cycle. Note, Automatic Data insiders must abide by specific rules, including filing SEC forms every time they buy or sell Automatic Data'sshares to prevent insider trading or benefiting illegally from material non-public information that their positions give them access to.

Automatic Data Management Efficiency

The company has Return on Asset of 0.0654 % which means that on every $100 spent on assets, it made $0.0654 of profit. This is way below average. In the same way, it shows a return on shareholders' equity (ROE) of 0.8726 %, implying that it generated $0.8726 on every 100 dollars invested. Automatic Data's management efficiency ratios could be used to measure how well Automatic Data manages its routine affairs as well as how well it operates its assets and liabilities. As of 12/17/2024, Return On Tangible Assets is likely to grow to 0.1. Also, Return On Capital Employed is likely to grow to 0.56. At this time, Automatic Data's Total Current Liabilities is relatively stable compared to the past year. As of 12/17/2024, Liabilities And Stockholders Equity is likely to grow to about 57.1 B, while Non Current Liabilities Other is likely to drop slightly above 926.2 M.
Automatic Data Processing has 3.71 B in debt with debt to equity (D/E) ratio of 1.4, which is OK given its current industry classification. Automatic Data Processing has a current ratio of 0.95, suggesting that it has not enough short term capital to pay financial commitments when the payables are due. Note however, debt could still be an excellent tool for Automatic to invest in growth at high rates of return.
Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide. The company was founded in 1949 and is headquartered in Roseland, New Jersey. Automatic Data operates under Staffing Employment Services classification in the United States and is traded on NASDAQ Exchange. It employs 60000 people. Automatic Data Processing (ADP) is traded on NASDAQ Exchange in USA. It is located in One ADP Boulevard, Roseland, NJ, United States, 07068 and employs 64,000 people. Automatic Data is listed under Application Software category by Fama And French industry classification.

Management Performance

Automatic Data Processing Leadership Team

Elected by the shareholders, the Automatic Data's board of directors comprises two types of representatives: Automatic Data inside directors who are chosen from within the company, and outside directors, selected externally and held independent of Automatic. The board's role is to monitor Automatic Data's management team and ensure that shareholders' interests are well served. Automatic Data's inside directors are responsible for reviewing and approving budgets prepared by upper management to implement core corporate initiatives and projects. On the other hand, Automatic Data's outside directors are responsible for providing unbiased perspectives on the board's policies.
M Heron, Managing Operations
Christian Greyenbuhl, Vice President Investor Relations
Jonathan Lehberger, Corporate Officer
David Kwon, Chief VP
Joseph DeSilva, President Sales
Don McGuire, Chief Officer
Max Li, Global Officer
Maria Black, President - Employer Services - TotalSource
Brock Albinson, Principal Accounting Officer and Corporate Controller
Allyce Hackmann, Vice Communications
Carlos Rodriguez, CEO and President and Director
Gus Blanchard, Chief Officer
Paul Boland, Chief Officer
Michael JD, Chief Officer
Michael Bonarti, VP, General Counsel and Secretary
Vipul Nagrath, Global Officer
Sreenivasa Kutam, President Innovation
David JD, Chief VP
Donald Weinstein, Chief Strategy Officer
John Ayala, Vice President - Client Experience and Continuous Improvement

Automatic Stock Performance Indicators

The ability to make a profit is the ultimate goal of any investor. But to identify the right stock is not an easy task. Is Automatic Data a good investment? Although profit is still the single most important financial element of any organization, multiple performance indicators can help investors identify the equity that they will appreciate over time.

Pair Trading with Automatic Data

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Automatic Data position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Automatic Data will appreciate offsetting losses from the drop in the long position's value.

Moving together with Automatic Stock

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The ability to find closely correlated positions to Automatic Data could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Automatic Data when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Automatic Data - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Automatic Data Processing to buy it.
The correlation of Automatic Data is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Automatic Data moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Automatic Data Processing moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Automatic Data can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching

Additional Tools for Automatic Stock Analysis

When running Automatic Data's price analysis, check to measure Automatic Data's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Automatic Data is operating at the current time. Most of Automatic Data's value examination focuses on studying past and present price action to predict the probability of Automatic Data's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Automatic Data's price. Additionally, you may evaluate how the addition of Automatic Data to your portfolios can decrease your overall portfolio volatility.