Big Data. Big Decisions
InformationWeek
Special Coverage Series

Commentary

Eric Zeman

AT&T's Shared Data Not For The Enterprise

AT&T's new Mobile Share plans offer buckets of data that can be accessed by a number of devices on a single account. They might work for consumers and small businesses, but they're not for large enterprises.

10 Great Summer iPad Apps
10 Great Summer iPad Apps
(click image for larger view and for slideshow)
AT&T today announced its own version of shared data plans. The plans provide consumers with a fair amount of flexibility when it comes to matching a service plan to their individual needs. Like Verizon's shared data plans announced earlier this year, AT&T's plans bundle together voice, text, and data and allow multiple devices to share from the same pool.

The idea has merits for consumers, especially families. For example, before today, a family of four, each with his/her own smartphone, could share voice minutes, but each device had to have its own data plan -- adding significantly to the overall monthly cost of the plan. Throw in a tablet for the kids and a mobile hotspot for mom or dad, and monthly data costs can spiral upwards at a dizzying rate.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

Worse, one device on the plan might use more than its monthly allotment of data, while others use only a fraction. It's hard to swallow a data overage fee at the end of the month on one device when a different device on the same account used less than half its monthly data allotment. (In fact, I'm pretty sure I'd be hopping mad about it.)

[ How do you engineer a successful mobile device management plan for the enterprise? See 6 Keys To A Flexible MDM Strategy. ]

Shared data plans from AT&T and Verizon Wireless are meant to help tackle this problem. Instead of charging each device for its own mobile data allotment, the shared plans provide larger buckets from which all the devices draw. For example, AT&T is offering monthly data buckets ranging from 1GB to 20GB, with basic access fees ranging from $40 to $200. Allowing devices such as smartphones, feature phones, laptops, tablets, hotspots, and netbooks to pull from this same bucket means it'll be easier for groups to balance data usage.

However, the idea appears to work best for a family or other small group. Consumers--and probably very small businesses--could very well save money on a monthly basis with the shared data plans. But AT&T's Mobile Share plan maxes out at 10 devices per account. That makes it unusable for most businesses.

Large enterprises--especially ones that distribute devices directly to employees--should not approach mobile services this way. Instead, they should be speaking to the enterprise sales teams at AT&T, Sprint, T-Mobile, Verizon Wireless, et al., about getting customized rates. When your business is purchasing hundreds or thousands of devices, it has a bit more wiggle room with the carriers when it comes to negotiating rates for voice minutes, messaging, and mobile broadband.

One scenario in which a shared data plan might make sense is large enterprises that use the Bring Your Own Device (BYOD) model. If Employee X has a smartphone, tablet, and laptop, the enterprise could provide that employee a shared data plan that covers all his/her devices rather than sticking him/her on an account that covers multiple employees.

As with most services, consumers, small businesses, and large enterprises will get different mileage from shared data plans depending on their individual circumstances and needs. While consumers and small businesses might have a bit less pull when it comes to customizing their services, big businesses should be engaging wireless network operators more directly to get the best possible rates.

At this year's InformationWeek 500 Conference C-level execs will gather to discuss how they're rewriting the old IT rulebook and accelerating business execution. At the St. Regis Monarch Beach, Dana Point, Calif., Sept. 9-11.



Related Reading




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.