Strategic advice to leverage new technologies

Fog computing, also referred to as "Edge computing," is an IoT applications architecture designed to distribute the resources and services of computation, communication, control, and storage closer to the devices and systems at or near the edge of an IoT network or its endpoints (e.g., mobile devices, connected machines, users).

With more and more companies embarking on digital transformation efforts of one kind or another, Conway’s law applies simultaneously to three levels of disruption, as identified by Geoffrey Moore: the traditional R&D and IT level, the operating model, and the overall business design. This Executive Update provides guidance on how to apply Conway’s law meaningfully within and across these three disruption levels.

The Internet of Things (IoT) is expected to generate incredible amounts of data from a myriad of connected consumer devices and industrial applications. Achieving business value from this massive data stream will require the use of big data storage and analysis technologies that have the ability to scale to meet the constantly increasing demands placed on organizations. Of course, this brings up the question: just how familiar are organizations with the various big data technologies? A Cutter Consortium survey that asked 80 organizations worldwide about their IoT plans helps offer some insights into this question.

Takeaways for developers from the companies developing wearables are clear right now. You can find them in the public keynotes at developer conferences from Google and Apple as well as the not-for-disclosure documents widely available to developers for those and other platforms. Detailed APIs are available to developers, and with little effort you can find discussions and test code on public and semi-public resources such as GitHub and YouTube.

From the fantasy to the real world, there is already an emerging business in large shared-screen experiences. Museums, libraries, hotels, and resorts are among the first locations where organizations can see an immediate return on their investments in creating engaging experiences for visitors in an anonymous fashion. Currently most of these experiences are a small step forward from digital signage, providing people with the opportunity to navigate their own way through the content provided and in some instances share the content to their personal devices.

An effective EA measurement program typically begins by identifying a set of precise and easy-to-use metrics recognized by both business and IT organizations across the enterprise. At a strategic level, EA metrics establish a number of quantifiable parameters that enable practitioners to assess and evaluate the EA program, the IT assets employed, and their relevance to delivering business value for the enterprise. At a tactical level, EA metrics include parameters that impact the EA and its effectiveness across the organization — both directly and indirectly.

Industrial, manufacturing, and process industries have used sensors, analytics, and other technologies to monitor and measure how equipment and processes are performing for some time. Now, we are seeing companies seek to apply sensor-enabled devices to support more human-centric monitoring in industrial settings.

In this article, you'll get an overview of how to design, build, and operate a new breed of cloud-native applications. The author also looks at how cloud-native design positively impacts a business, bringing new and crucial capabilities to your organization.