Big Data. Big Decisions
InformationWeek
Special Coverage Series

Commentary

Chris Murphy

Chris Murphy

Editor, InformationWeek

Silicon Valley Needs To Get Out More

The next great technology problems to solve are out there in rail yards, power plants and farm fields. If Silicon Valley is going to drive this "Internet of things," it needs to build closer ties with companies in established industries.

 Big Data Talent War: 7 Ways To Win
Big Data Talent War: 7 Ways To Win
(click image for larger view and for slideshow)
The industrial Internet, or what's more commonly called the "Internet of things," needs a new wave of innovation and invention to advance. Better analytics software, better sensors, new business models. If the Silicon Valley technology startup ecosystem is going to drive that invention, it needs to build closer ties with companies in established industries in order to understand their problems and opportunities.

Uber didn't arise because taxi companies called a conference to ask for technology to disrupt their industry. It started with three guys who had a problem calling a cab. So how do you let those "three guys" know about the everyday problems of running railroads, power plants, mines and farms?

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

We need ways for more people to tinker with industrial Internet problems without each industry's permission. Silicon Valley needs to figure this out, but so do established companies searching for the next wave of efficiency and revenue from technology.

[ Read How To Find Strategic Advantage From Big Data. ]

The industrial Internet promises to deliver that boost via machine-to-machine online connections -- putting sensors on equipment and infrastructure, including tractors, airplanes, electricity grids, medical systems and gas turbines, in order to collect data. Using analytical software to make sense of that data can let companies do things like predict when a jet engine part is starting to wear out and replace it long before it fails. GE recently forecast that the industrial Internet could add as much as $15 trillion in worldwide economic growth in the next 20 years.

Silicon Valley startups and venture capitalists will want their cut of that $15 trillion, but is the startup ecosystem sufficiently plugged in to these problems to work its magic?

Consider this advice from investor Paul Graham, from his recent essay on How To Get Startup Ideas, which anyone remotely interested in business innovation should read:

"The way to get startup ideas is not to try to think of startup ideas. It's to look for problems, preferably problems you have yourself. The very best startup ideas tend to have three things in common: they're something the founders themselves want, that they themselves can build, and that few others realize are worth doing."

The problem isn't that these industrial Internet problems are inherently harder because they involve sophisticated equipment such as power plants and jet engines. Consumer Internet companies such as Google and Facebook, with their massive-scale database, analytical and data center technology, connect with billions of people. That's what showed us that connecting hundreds of billions of machines and making sense of the data is possible.

Global CIO
Global CIOs: A Site Just For You
Visit InformationWeek's Global CIO -- our online community and information resource for CIOs operating in the global economy.

The risk is that people in the traditional startup talent stream: a) don't know what industrial problems exist; b) aren't jazzed by the problems (see Graham's "something the founders themselves want"); and c) don't see a big enough opportunity in solving those problems.

You get excellent Silicon Valley perspective on this challenge from an intriguing panel discussion led by Tim O'Reilly last week at a conference GE held about the industrial Internet.

On the subject of needing to know that problems exist, EMC chief strategy officer Paul Maritz framed things this way. The first generation of Silicon Valley was plugged into enterprise IT needs and was wildly successful at automating companies' paper processes. The next generation pioneered the consumer Internet. Now the two worlds need to come together, to use the Internet to solve industry-specific problems.

But Silicon Valley lacks the deep industrial domain knowledge. "What we haven't had happen yet is the education of what does it mean to move a locomotive all the way from Long Beach to Chicago?" said DJ Patil, a former LinkedIn executive who's now data scientist in residence with the venture fund Greylock Partners.

 1 | 2  | Next Page »


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.