My "baptism" in programming was based on a discussion scratched on the back of my user's used-up cigarette case.

One of the most popular articles ever written for the Harvard Business Review was authored by Frederick Herzberg in 1968. 1 In it, Herzberg proposed a re

In response to economic downturns, it should come as no surprise that many companies turn to short-term cost cutting and/or choose to place big bets on business transformation efforts that may be premature.

There have been significant advances in process modeling tools over the past decade. But that doesn’t necessarily mean that companies are getting good value from the time and effort they have invested in process modeling.

This CBR issue is motivated by the following trend: the ability to access and analyze data as it's created in real (or near real) time. This issue's articles work particularly well together. Federico and Elisabetta help draw our attention to the higher-level question of value creation; a question every organization must tackle. After all, real-time data analytics is difficult and expensive and organizations need to know that they will earn a return on their investment. Zubin then grounds us with some excellent advice and insight around implementing and managing real-time data analytics. Regardless of where you are along the real-time data analytics path, I trust both the survey data and articles in this issue will serve you well.

The ubiquitous, massive creation of real-time data in a natively digital form (a phenomenon known as "digital data genesis,"1 or DDG) provides unprecedented opportunities for novel value creation. Pulled by the diffusion of sensors -- and the consequential increase in the creation, storage, communication, and processing of information -- such generated data can be made readily available or streamed to other partners or appropriately transformed in customer value-added services. We define this concept as the "digital data stream," or DDS. We believe the organizational implications of both DDG and DDS are enormous but that much is still to be understood in order to profit from the harvesting and streaming of data sources. What form does value creation take today? Which activities enable these new forms of value creation? How do these new possibilities for action become tangible value propositions?

First stop: 30,000 feet. For me, one of the key messages from this issue has been the clear need for big-picture thinking.

This survey examined how organizations approach real-time data; how they might use real-time data to benefit the organization; the challenges and barriers to the exploitation of real-time data; real-time data analytics; and the sources, type, and frequency of real-time data streams. A bit more than half (57%) of the 54 responding organizations are headquartered or based in North America, with 19% in Europe, 15% in Asia, 6% in Australia/Pacific, and 2% each in the Middle East and South America.

In my last Advisor (“ Big Data Analytics in a Socially Infused Healthcare Enterprise”), I shared an account of leveraging Big Data analytics in a large healthcare IT organization.

In my last Advisor (“ Big Data Analytics in a Socially Infused Healthcare Enterprise”), I shared an account of leveraging Big Data analytics in a large healthcare IT organization.

A process, in my honest opinion, is the product of its era. It reflects the needs, the constraints, and the predicaments of its time. As those change, the process needs to evolve in tandem. If it does not, it is likely to become obsolete.

As we all know, Abraham Lincoln was largely self-taught in the midst of meager means and living on the frontiers in the US states of Kentucky, Indiana, and Illinois -- far from centers of learning and culture east of the Appalachian Mountains. For Lincoln, the book represented the path, and he sought them with great effort.

As we all know, Abraham Lincoln was largely self-taught in the midst of meager means and living on the frontiers in the US states of Kentucky, Indiana, and Illinois -- far from centers of learning and culture east of the Appalachian Mountains. For Lincoln, the book represented the path, and he sought them with great effort.

A process, in my honest opinion, is the product of its era. It reflects the needs, the constraints, and the predicaments of its time. As those change, the process needs to evolve in tandem. If it does not, it is likely to become obsolete.

Many of my long-time readers might remember that I live out in the woods in the US state of New Hampshire. Just recently, my 20-year-old garden tractor began to die. In looking at a replacement, I started to go over the options.

Back in January, when discussing trends for predictive analytics in 2012, I predicted that some of the issues holding organizations back from realizing their predictive analytics dreams would be offset by new options for implementation (see "The Year Ahead: Will 2012 Be a Breakout Year for Predictive Analyt

Back in January, when discussing trends for predictive analytics in 2012, I predicted that some of the issues holding organizations back from realizing their predictive analytics dreams would be offset by new options for implementation (see "The Year Ahead: Will 2012 Be a Breakout Year for Predictive Analyt

"Cloud computing represents a game-changing paradigm shift in the industry, with consumers (and the enterprises they serve) crying out for a broadened set of standards in areas where standards have never existed before."

-- Mitchell Ummel, Guest Editor

A problem clearly stated is a problem half solved.

-- Dorothea Brande

Standards in the cloud computing space are one of the major drivers affecting ongoing adoption. Attractive financial and service delivery models can only deliver business results if the underlying technology portfolio can interoperate effectively. This article frames cloud computing as the latest generation of extended value chains that require standards to enable providers to interact with their clients.

In the last several hundred years of humankind, technology advancement has played an important role in the overall advancement of civilization. Electricity, communications, and computing are all 100% technology-based innovations. And in these fields, there are implicit requirements for standardization.

Many organizations have developed models to explain the introduction of a new technology in the marketplace. Few of these models, if any, identify the point at which standards become necessary and get developed, or how they influence -- positively or negatively -- the subsequent development of the products they affect.

"Cloud" as a popular term has been around for only a few years, but the concepts of pay-as-you-go services and IT as a utility go back to the first hosted Web servers starting in the late 1990s. After 15 years or so, you would think that cloud technology would have standardized.

Richard Stallman1 is the founder of GNU Linux and the Free Software Foundation and one of the key experts in the field of open computing. In June 2012, I interviewed him for my blog, Watalon.com. The aim of the interview was to get Stallman's views on cloud computing and how open standards should be built around the cloud.