In this Advisor, we illustrate a five-step neural network development process. Neural networks are systems of nodes, “neurons,” or processing elements arranged in multiple layers. The nodes are connected by links that, at any given moment, either pass information or don’t pass information from one node to the next. Upon the passing of information, certain connections become stronger. As specific outcomes or results are reinforced, pathways become stronger and the network comes to identify specific pathways with particular outcomes. This process is called training. As the network becomes exposed to more data and as it is reinforced, it continues to modify its outcomes and “learns.” 

The hunt for a suitable insurtech, which not only brings the desired business value to the table but is also the least painful to align with from an IT perspective, needs to be approached in a systematic manner.

Applying cognitive computing to a business ecosystem is by no means far-fetched, with the concept of the cognitive enterprise evolving in theory and practice.

There are multiple challenges that emerge as an enterprise moves toward an Agile development approach, both at the team level and when scaled to the program and portfolio level. Here are five pieces of advice from my personal experience with Agile development at the team and enterprise level and how enterprise architecture leaders can influence and impact the ability to deliver value.

One trend that will impact Internet of Things (IoT) development in 2018 is a significant growth in edge computing.

Senior management behavior is vital to the foundational change of establishing an enterprise culture for the digital era.

In this Advisor, we examine four common misconceptions that stand in the way of digital transformation.

Autonomous vehicles continue to make headlines.

Moving EA into a position of strategic importance involves making the case that enterprise architecture provides value, and that the business stakeholder can directly and immediately benefit from that value. Under­standing the services EA provides, and the value proposition for each one, is a requirement for making that argument.

Today’s digital technologies are driving continuous disruption. Survival is based on an ability to sense changes early — and adapt quickly. However, most top-down, hierarchical organizations have structures and processes that attempt to treat continuous changes as discrete, one-time events. Simply put, organizations are using change management approaches that don’t work with digital transformation. Digitally-driven change is messy and unpredictable. Unpredictability unsettles everyone. Successful orga­nizations of the future will embrace the mess — and fundamentally change their organizational culture.

A small number of cutting-edge companies have effectively exploited big data’s potential. These companies have a strong focus on data gathering, recognize the potential value locked in their data, and effectively use machine learning to convert potential value into real, measurable business value. In this Advisor, we outline examples of three such companies and the way in which they utilize ML in practice.

This Advisor examines the use cases surveyed organizations indicate as being most viable for applying blockchain technology.

Just like excellent poker playing, deciding how and whether to act in an innovative effort requires both fast and slow systems of thinking. You need slow thinking to update your current beliefs with recent learning and then use fast thinking to act based on your experience and intuition. This Advisor explores some examples of fast and slow thinking in today’s organizations.

It pays to really assess your current marketplace situation and learn from disruptors in your own or adjacent marketplaces. Enterprise architecture (EA) is an asset that you can use to counter the threat of disruptors. The three generically applicable scenarios we introduce in this Advisor may help you choose the right pattern for your EA, depending on the business model of the disruptor, your choice of counter-strategy, and your current EA maturity.

Participants in partnering enterprises can evaluate their Organizational Agility maturity using the Organizational Agility Maturity Rubric. The characteristics of Organizational Agility presented in this rubric can emerge and evolve through the sustained practice of key techniques by all participants.

The most exciting development coming out of the recent consumer electronics show CES 2018 is Kodak's announcement that it plans to develop a blockchain-based photographic rights and royalties management platform (KODAKOne) and accompanying cryptocurrency (KODAKCoin). The goal is to enable photographers and other agencies to take more control over how images are commercially managed and licensed.

Shadow IT exists in your company. Some form of DevOps is being implemented, and somewhere online tools and the public cloud are being used without your approval. Shadow IT can create many risks and bad economic management of IT resources. You can choose to go to war and forbid the use of the new methodologies and tools or learn how to leverage them. This Advisor advocates for the latter.

Modern software systems are routinely very complex, comprising millions of lines of code with many thousands of dependencies. Moreover, software engineer availability, workloads, and turnover compound the problem of keeping track of the complexities of systems. In this Advisor, we examine the benefits of contextual software analysis for mitigating business risk.

External phenomena have transformed competitive advantage from sustainable to transient. Organizations must learn how to succeed and survive in this new business environment, an environment that has forever changed due to digital technologies.

The notion of architecting for flexibility so that enterprises can change is not new. But what about disruptive change? And why does disruptive change matter? Why now?

In this Advisor, the authors demonstrate their analytical approach with a direct and practical example of using Twitter data in real time to understand the sentiments (positive or negative) of trade show participants and to gain insights from them.

Agility is about being adaptable to changing environment conditions, delivering or acting swiftly to fulfill customer needs, and in turn becoming a successful and sought-after organization. Being connected to the fundamentals of agility and tracking the transformation progress based on the Agile principles described in this Advisor helps organizations to be on track toward transformation progress and stay connected to the big picture.

I suspect that of all things, big data will address the human mind last. For whatever reason, people approach the science of the mind differently than they approach the science of the body.

The constants across all the customer experience winners include listening, communication, honesty, responsiveness, and innovation. Follow these seven steps to make your customers happy.

The dynamic nature of the business capability architecture (BCA) aptly lends itself to modeling the new paradigm of big data analysis.