Of all the scrum roles, the scrum master seems to be the hardest one to grasp in large organizations.

In this Advisor, we look at how teams can lose their coordination and their focus on delivering quality work while at the same time accumulating a significant amount of technical debt. This can be a hard balance to manage: delivering quality outcomes but sacrificing the longer-term success of the team by cutting corners and delaying necessary work until later for the sake of short-term delivery.

The distinction between businesses that focus on a relatively small range of products with a high volume of sales and businesses that embrace either a wide range of products or highly specialized niche products with relatively smaller sales volumes is highly relevant to enterprise architecture.

Traditionally, farmers have applied new techniques — such as new seeds, pesticides, herbicides, and so forth — to a small plot to observe optimal yields. Instead of such empirical analysis, which takes time, farmers are also embracing results from analysis of large, real-world data sets from public sources. Analysis of such big data can produce reliable recommendations much more quickly.

Understanding individuals and how they interact with each other is one of the key priorities of Agile.

Our vision strives for a software-driven approach that improves drones' energy consumption by establishing practices, tools, and metrics for developing and evaluating energy performance at the system level. With this knowledge, we can outline ways to utilize software solutions to measure and optimize drones' energy consumption and critically improve their flight autonomy.

By targeting basic human traits, enterprises can attract more customers, create a network effect, and improve employee productivity and performance.

A truly effective enterprise architecture should be something that senior executives in an enterprise use to manage their business on a day-to-day basis, that guides the implementation of strategy, and that helps them in communicating and implementing change.

A number of trends and developments — stemming both from advances in information technology and rising consumer/social expectations — are driving the commercialization of cognitive computing for consumer and enterprise use.

Connecting business expectations and value generation through enterprise scenarios envisioned by these storyboards can carry several benefits that help narrow the gap between Agile teams and business users by ensuring a mutual understanding of the business and technical vision.

The most common problem we see in RFPs for cloud services is the reuse of tendering materials that were designed for the outright purchase of physical objects. Problems that arise include buyers being unnecessarily specific in the definition of their requirements, buyers trying to impose what they would do in their small data center to an exascale cloud provider servicing thousands of diverse clients, and many others. The best way to spot these problematic approaches is by way of analogy.

In this Advisor, I discuss how we addressed, in building our own private cloud, the security concerns that companies considering a migration to the cloud often face.

Succeeding as a digital business requires organizations to fundamentally transform their operating model in order to infuse the required level of flexibility and data-driven responsiveness at every level of the enterprise. Establishing an operating model geared for competing in a digital economy involves three key capability areas, as discussed in this Advisor.

It truly takes a village to build a nimble (Lean) and flexible (Agile) enterprise architecture (EA) program in this digital era. EA as a discipline may not have to change drastically to address digital transformation, but EA does have to play a much bigger role in embracing the change swiftly and facilitating the change across the enterprise.

Organizations seeking to incorporate effective analytics programs will likely encounter several challenges along the way. Whereas many of these can be dealt with in the short term, others will require solutions that we do not know to exist at the present time.

Big data has already demonstrated many successes, and experts assert that cognitive computing systems can actually make the context behind decision making “computable,” acting as a proxy for human intuition. It is that convergence — human creativity supported by relevant information — that offers the greatest potential.

It is hardly necessary to explain or justify that security is a concern when we think of applying Internet of Things (IoT) technology to industrial applications, but it is useful to consider how it differs in this context from the consumer domain.

Successful digital transformation enables the organization to embrace innovation, to develop new products and models, and to rapidly realize those to create value. Although there are no blueprints for success, we will examine three best practices that can allow businesses to increase speed and reduce cost, reach customers with an excellent user experience, and experiment with new products, features, and models.

Scientific insight, connectivity, computing, and technology have all reshaped civilization. We are officially in a Knowledge-Machine Age that is still going through its angst of childhood while its parent, the Industrial-Information Age, has withered away into senility, no longer able to guide the new child. Even the term "post-Industrial," which denotes the shift from a manufacturing to a service economy, is inadequate here. What we have facing us is the full-blown use of advanced computation driving all things in the economy: from manufacturing to all services.

When designing products and services for the Internet of Things (IoT), organizations should make defining procedures for ensuring customer privacy an initial priority to avoid embarrassing and potentially costly surprises down the road.

Business process change and cognitive computing do not necessarily overlap, but in business environments, they often do. Put simply, we will increasingly use cognitive computing techniques to improve business processes.

The key to Agile management is that the organization and analytics that implement the interlocking sense-and-respond loops up and down the organization enable overall organization agility.

Consumers enamored of mobile and social media are forcing banks and other financial institutions to optimize their interactions with customers and transform the way they conduct marketing, sales, and service. Today’s consumers expect financial companies to know them individually and deliver personalized interactions and self-service options.

How do you compute the valuation of something that has no clear definition? There are a couple of ways to respond: accept that it is good enough to have a very general value proposition for activities that somewhat fit under an “architecture” umbrella, or delineate specific architecture strategies and initiatives whose value can be measured in a manner similar to other investments that enterprises are used to.

Successful IoT use cases can emerge only by moving away from a product-centric approach that focuses on one-time sales and toward enabling an ecosystem of collaborating devices and services working in concert to build a longer-term, value-based customer relationship.