For the purpose of this article, we define context awareness as the information necessary and ­sufficient to perform the intended func­tion of the device effectively and efficiently. Typically, but not always, the context can be ascertained comprehensively by answers to some or all of what we like to call “the four Ws”: where, when, who, and what. A simple IoT device with limited functionality may only need to answer one or two Ws, while a more complex IoT device may need answers to all four, and perhaps even to additional questions such as how, why, which, how much, and so on.

Compromises are inevitable in larger transitions. After all, you’re doing an incremental journey. To figure out which of the compromises are pragmatic steps and which of them are simply in the wrong direction, you need a clear picture of the business goals behind the Agile transition.

In a recent engagement with a healthcare delivery service provider embarking on clinical trials in a digital health effort, the service provider had three specific reasons for leveraging crowdsourcing: (1) the company had very little direct contact or interactions with patients; (2) the design of the product seemed complex; and (3) the leadership team felt it to be compelling enough to solicit participants.

[From the Editor: In 2012, Senior Consultant Lee Devin wrote about industrial thinking and methods (see  "Artful and Industrial Making"). His words continue to ring true today. We share his message again here.]

Due to its ability to view an enterprise through a common lens, business architecture offers unique insights into the impact and viability of various business strategies and requirements.

One of the most sinister threats impacting data security and protection today is ransomware, which works by infiltrating an organization's systems and encrypting sensitive files and data. The data is then held for ransom by hackers who demand payment—typically in Bitcoin or some other digital currency — before they turn over the key required for its decryption.

Understanding how to become Agile starts with understanding the kind of work your organization performs.

For many practices, it’s a change in lexicon or technology that make them new “flavors,” but the underlying principles remain the same. We need to embrace our teams. We need to identify what we expect of them, and give them the tools and capacity to accomplish their goals. Read between the lines of virtually any new approach, and there should be signs of an homage to what’s been done in the past (and done well).

One characteristic of the digital economy is its enormous scale.

There are many possible collaboration opportunities companies might pursue, but for the purposes of this article, I have elaborated three healthcare-related scenarios. The first involves using information within the personal cloud as a way to monitor conditions and trigger certain actions. The second looks for new ways to collaborate by sharing information in the course of a particular care encounter. The last is a common scenario in healthcare where either historical data or enhanced information is sought for research purposes.

Many corporations have been doing cloud computing seriously for several years. For example, Proctor & Gamble (P&G), Johnson & Johnson (J&J), Allergan, and Sears Roebuck & Company (Sears) have already moved from adoption to the next stage of use and beyond. Seeing the IT function as a strategic partner, senior business executives in these companies, together with their CIOs, business systems thinkers, and relationship builders, have identified how cloud computing deployment can align with dynamic business strategy over time and how it can be operationalized, including with external service providers, for strategic business advantage.

Introducing Agile causes pain to your organization. This is not because Agile doesn’t work — it works for hundreds of organizations, some of them probably quite similar to yours. This is because Agile shows you the problems and deficiencies in your organization as brutally as the mirror you look into in the morning after a late night out. It is not the mirror that makes you look bad! The short iterations of XP and Scrum and the focus on lead time in Kanban work better the more mature the engineering and management skills in your organization are.

The Internet of Things (IoT) is driving demand for cloud-based platforms designed for building and managing connected solutions and for storing and analyzing the data they generate. This Advisor examines the available products for IoT infrastructure services.

Enterprise architecture has often failed when it’s targeted at modeling the entire enterprise. Thus, organizations must perform the appropriate amount of EA to achieve results. Agile approaches, such as Scrum, can sometimes be used to build small pieces of the EA that deliver exactly what the organization needs. Scrum techniques look at harnessing teamwork, delivering within time slots, and identifying “experts” to help with specific issues.

Let me start by explaining my use of the word “coalition” and set the context for using it with respect to enterprise architecture (EA) and Internet of Things (IoT) alliance or synergy. According to Merriam-Webster, a coalition is “a body formed by the coalescing of originally distinct elements.” While EA and IoT are distinct and unsimilar disciplines, my interest is the inherent synergy between them. In my opinion, this originates from the fact that EA and IoT each supports digital strategies for disruptive business operations.

In the past decade, the field of neural networks has evolved very rapidly as a result of new insights obtained in the mid-2000s, when several researchers published articles on deep learning. The number of algorithms has grown rapidly. For example, there is now a whole class of algorithms often termed deep learning, deep machine learning, or deep neural networks that have become popular. This topic can be a bit confusing as “deep” is currently being used in multiple different ways.

Many popular definitions of leadership emphasize charisma, vision, or position. The darker definitions hint at manipulation or even coercion. In software companies, though, people throughout the organization are smart, well intentioned, and capable of making good decisions. So we need a different definition if we want to make our companies more flexible and smarter.

The challenge for the enterprise architect is to figure out what the enterprise chorus lines are; in other words, what we might think of as the “core” architecture.

The question of ethical algorithms doesn’t just affect autonomous robotic operations. As more devices are being increasingly connected into an “Internet of Things,” how, when, and why should the gathered information be used and to whom should it be made available?

Watson Ads is the first application of Watson to advertising. The goal: make ads more appealing, interactive, and engaging; in effect, heighten the consumer experience by allowing them to make more personalized, informed decisions at the point of consideration. Instead of clicking on an ad and receiving a canned marketing spiel about a product or service, consumers will be able to ask specific questions in plain natural language and receive information with real, contextual relevance to their individual needs.

Agile requires real cultural change. Unfortunately, many people new to Agile don’t see the connection between the principles and the practices. In their eyes, Agile is just another process, something that requires following a checklist of behaviors. Other processes in their experience, such as CMMI and ITIL, never asked them to adopt a new worldview. Therefore, even if they become aware of the important connection between Agile principles and practices (which they may not), they may have no past experience in software innovation for making the connection between them.

All that has been said and written about the challenges associated with the Internet of Things (IoT) does not quite prepare you for the practical difficulties that crop up as you start implementing and deploying IoT solutions. Most of the publicly available knowledge about IoT challenges relates to high-level issues that are typically addressed through architecture and design decisions. One of our recent successful implementations, an enterprise-wide Remote Energy Management System (REMS), brought us face-to-face with an entirely new set of ground-level challenges, from data ingestion to data storage, to data processing, to data analytics and visualization.

Understanding the driving forces behind digital transformation, its effects, and the role that certain enterprise architecture best practices can play in embracing digital transformation will help organizations benefit in this challenging time.

If we could for a moment ignore the terms "enterprise architecture" and what does or does not constitute one, and "solution or system architecture" and what does or does not constitute one, we might reach some agreement on the concepts that underlie enterprise architecture. In that spirit, here is my take on enterprise architecture, without using the word (until the end).

I have often joked that data warehouses are as unfriendly to business users as physical warehouses are to shoppers. The reality is perhaps grimmer: data warehouse designs took no cognizance of the actual processes at work within human beings when making decisions. Data lakes, despite metaphors of recreational use and dipping in for data, actually pay as little attention to the mental processes involved in decision making as did data warehousing.