Big Data. Big Decisions
InformationWeek
Special Coverage Series


Google Sued Over Unpaid Overtime

A former facility coordinator at Google's Council Bluffs data center in Iowa wants to be compensated for working 50-60 hours, six days a week.

Google and two contract service providers, Mainelli Mechanical Contractors and Eurest Services, were sued in Iowa on Monday for allegedly failing to pay overtime wages to a former employee.

Plaintiff Michele A. Peterson, a resident of Papillion, Neb., claims that from January 2008 to her termination in February 2011, she worked as a facility coordinator at Google's "business facility located in Council Bluffs, Iowa," which is to say the company's Council Bluffs data center.

After her hiring, Peterson's complaint claims, Google delegated payroll responsibility to Eurest and then to Mainelli.

Whether Peterson was a Google employee or an employee of a contractor hired by Google isn't entirely clear: The complaint asserts Peterson was hired by Google; a receptionist answering the phone for Mainelli said, "[Peterson] worked for us at Google."

Mainelli provides installation services for HVAC, plumbing, and related needs for commercial construction projects like Google's Council Bluffs data center. A spokesperson for the company was not immediately available.

Google declined to comment. Google announced plans to build a $600 million data center in Council Bluffs in early 2007 and completed the project in May 2009. The project was expected to create about 200 full-time jobs paying around $50,000 annually.

The complaint asserts that Peterson was required to work 50-60 hours per week, six days a week during her employment and that she was not paid overtime wages "to complete the work demanded by Google's management."

Peterson claims to have been a non-exempt employee. Under the Fair Labor Standards Act, non-exempt employees are entitled to overtime pay. Employees classified as exempt, who are not entitled to overtime pay, typically have high salaries or managerial responsibilities.

Litigation about unpaid compensation appears to be relatively common in the tech industry. In April, AT&T settled a class action lawsuit over failure to pay overtime compensation for $12.5 million. In April 2006, game maker Electronic Arts settled a similar overtime lawsuit for $14.9 million. That same year, IBM settled an overtime case brought on behalf of 32,000 workers for $65 million.

Apple was hit with an overtime lawsuit in 2009 but didn't end up paying very much upon settlement--a mere $3500. Apple faced another overtime lawsuit in 2008, settling that case in 2010 for almost $1 million.

This may have something to do with conflicting wage pressures. On one hand, the desire to hire top talent at Google and its competitors has led to the costly acquisitions of start-ups just for access to their engineers.

Yet even as tech companies pay what some argue is too much for talent, Google's recent decision to raise base salaries for its employees by 10% and to shift non-executive compensation from bonuses to salary increases--a move motivated by a desire to retain talent more effectively--suggests that Google had been a bit too successful in keeping wages low.

One reason for that may be the alleged conspiracy between Google and other Silicon Valley firms--Adobe, Apple, Intel, Intuit, Lucasfilm, and Pixar--to not hire each other's employees, an act that plaintiff Siddharth Hariharan, in a lawsuit filed earlier this month, claims suppressed employee compensation.

Businesses have myriad technology options for pulling together people and ideas. But getting it right still isn't easy. Also in the new all-digital issue of InformationWeek SMB: A UC champion's survival guide. Download it now. (Free registration required.)



Related Reading


More Insights




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.