Big Data. Big Decisions
InformationWeek
Special Coverage Series


Why IT Needs To Push Data Sharing Efforts

Company culture as well as technology can work against data sharing initiatives.

As IT organizations change their focus from cost cutting to growth, one of the single best things they can do for their businesses is enable effective data sharing. Sounds like a no-brainer, right? The right data sharing can open new markets, win new customers, improve relationships with existing customers, and expedite jobs from materials delivery to inventory management to payment reconciliation.

Yet data sharing, particularly automated systems that give your external business partners access to your data when they want it, are not ubiquitous or easy, and the level of data sharing of any kind is surprisingly low at points before and after the sale, our exclusive research finds. Your colleagues resist data sharing, but they're not the only problem. IT is way too slow at creating such integrations--taking months, not days, to build new links, in many cases.

FedEx and UPS make package tracking so simple, it's easy to take that capability for granted. Yet only half of companies even share order status with customers. Meanwhile, in the most sophisticated supply chains, companies share data as deep as inventory levels with key customers, such as manufacturers looking to coordinate just-in-time deliveries. With vendors, electronic invoicing is the simplest level of sharing. On the other end of the spectrum are companies that share point-of-sale data with vendors, something fewer than one in six companies in our survey do.

It's such an important trend that IBM in late May said it would pay $1.4 billion for Sterling Commerce, an integration software and services company owned by AT&T. While the deal didn't attract a lot of attention, it was IBM's largest acquisition in three years. The appeal to IBM is straightforward: Data sharing and integration projects always require some custom integration and ongoing maintenance of the links. Therein is the opportunity for IBM's consulting and services army, and the challenge for most IT organizations. But the problems go well beyond creating and maintaining data integration links. Our survey of 281 IT professionals finds that while technology is part of the problem, organizational resistance is a bigger obstacle.

Almost every company we surveyed shares data with someone. Most (74%) share data with customers, while 62% share data with suppliers. Almost half of respondents are required to share data with other third parties, mostly government agencies. Yet there's wide disparity in data sharing strategies: A fourth consider it a top IT priority, about a third build connections on request, while 22% admit they resist data sharing to some extent.

When it comes to what frustrates data sharing efforts, the classic culprit, budget limitations, tops the list of survey respondents, followed by complaints about the multiple sets of tools and the care and feeding required by legacy connections. However, we suspect that it goes deeper than any technology.

Sales, manufacturing, or merchandising tend to drive the decision to build new data sharing relationships with suppliers and customers. "They're usually the starting point and are a major factor in getting a program expanded," says Jim Frome, chief strategy officer at EDI software-as-a-service provider SPS Commerce. That trio historically doesn't have the greatest relationship with IT in many organizations, Frome says. Yet IT really needs to have an active role in educating the different teams about capabilities and options available both internally and externally.

InformationWeek:June 21, 2010 Issue To read the rest of the article, download a free PDF of InformationWeek magazine
(registration required)


Time To Play Nice

Subscribe and get our full report.

This report includes 30 pages of action-oriented analysis, packed with 19 charts.

  • Survey responses from 281 IT professionals
  • Best practices on internal processes and selling projects to management
  • ROI spreadsheets on e-invoicing, stock-level sharing, marketing data, and product service data
Get This And All Our Reports



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.