What is technical debt? Consider the metaphor of ­running through mud. There are two consequences of running through mud. One of them is low speed, because the mud has high friction; therefore it slows you down. The second consequence is that mud is much less stable, making it much easier to injure yourself, such as twisting your ankle or falling. These consequences are metaphors for developing with systems that have high technical debt. Everything else about the systems is harder to do, slower, and more dangerous — there is a higher risk of failure in production, and the systems will be harder to maintain.

Businesses need to face the connected consumer-led economy with clear-cut imperatives that are aligned in lockstep with business and IT. Every prior enterprise transformation journey has been enabled by IT, but the digital technology transformative imperative changes the equation. Most digital transformations lose their way due to the complexity of overlapping boundaries at a high level between traditional and digital IT.

During this on-demand webinar, Cutter Senior Consultants Murray Cantor and John Heintz introduce a process for applying next generation agile planning to your software delivery process, so you can gain an accurate view of your current status, make modifications where necessary, and improve your odds of success.

We observe from digital transformation in the real world that EA as a discipline has the responsibility to facilitate changing the mindset or culture of the enterprise.

Developing cognitive applications requires training cognitive models to be able learn and reason from their interactions with data and their experiences with users and the environment they operate in.

During the first two quarters of 2016, Cutter Consortium conducted a survey that focused on the methods, tools, and techniques surrounding business adoption of disruptive technologies. We collected data across multiple industries and countries, but primarily from the US. There were just about as many business professionals as technology professionals who responded to the survey. The purpose of the survey was to understand how companies identify, pilot, and deploy specific emerging or disruptive technologies. 

During the first two quarters of 2016, Cutter Consortium conducted a survey that focused on the methods, tools, and techniques surrounding business adoption of disruptive technologies. We collected data across multiple industries and countries, but primarily from the US. There were just about as many business professionals as technology professionals who responded to the survey. The purpose of the survey was to understand how companies identify, pilot, and deploy specific emerging or disruptive technologies. 

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

A good mental model of your ideal organization is that of a well-designed system: one that is efficient, responsive, and serves its purpose well. An organization is a system comprising staff and technology. Good systems design is about balance. This Executive Update, Part II of a two-part series on Agile management, discusses balance in relation to collaboration and empowerment.

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.

EA, as a formalized practice, is less than 20 years old. As with any profession or practice, there are many definitions, perspectives, and schools of thought surrounding EA. Here in Part II of this three-part series, we address a shared goal among enterprise architects to evolve the practice from a fragmented, often poorly understood field to a “real profession,” on par with well-established professions such as accounting and engineering.

This Executive Update provides a high-level description of EA, what it can do for an organization, and how EA can (and should) play a critical role in alignment efforts. We present insight into what enterprise architects do, what kinds of skills they need, and what results and benefits an organization should expect from their EA efforts.

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.

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.

Predefined source or reference frameworks such as TOGAF, Zachman Framework, IFW, or DoDAF are all very different. We need a simple way to first identify the factors that we need from each framework, and then combine them to create several relevant checklists or frameworks. This tool is the EA metaframework. This Executive Update provides an explanation of the different types of architecture frameworks, describes the role of the metaframework, and shows how architects can use it to create multiple integrated practical frameworks.

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.