As has been our tradition for the last several years, we've compiled the five most intriguing articles published by the Data Analytics & Digital Technologies practice this year for today's Advisor. How did we come up with this list? We chose the articles that garnered the most feedback from Cutter Members and clients and those that created controversy among Cutter Senior Consultants and Fellows.

Outcomes are becoming the moments of truth for customers and employees alike, developing into the points where value is created for the business. Shifting the dial is not about changing capabilities; it’s about changing the way organizations look at what people really need and delivering that as an outcome. This is a competitive differentiator now and will become an essential hygiene factor for competing tomorrow.

In this Advisor, the author explores how cognitive technology can be used “in the small” with benefit today as potential users wait for it to scale for use “in the large.” The author shares three operational scenarios to show how firms could build tools to put cognitive computing techniques to work today.

As our world becomes more and more connected, the need for precisely timed predictive sensor fusion algorithms is essential for business success.

Engaging enterprise architecture (EA) in the acquisition process allows the acquisition team to plan, execute, and evaluate acquisitions within a strategic planning framework that improves acquisition performance without compromising orga­nizational performance.

Data breaches are front and center in the news again. And with the hacking of the US Democratic National Committee's (DNC) servers, allegedly by Russian security services in an effort to influence the outcome of the American presidential election, and Yahoo's latest announcement of a yet another hack involving data associated with more than one billion (!) accounts, it is obvious that no system should ever be considered entirely safe from breaches, regardless of the data security and protection solutions in place.

Business capabilities are a foundational business architecture domain. Capabilities play the role of anchoring business perspectives for a wide variety of transformation scenarios, including digital transformation. Coupled with value stream, organization, information, product, strategy, and initiative mapping, capabilities provide a central focal point for exposing multidimensional aspects of a business ecosystem.

It is nearly impossible to prevent technology debt from being created — ­product/service lifecycles are getting shorter, making time to market an imperative for which taking shortcuts becomes a necessity. However, the size and scope of the ­technology debt being created can be contained, and on rare occasions some technology debt can be ­prevented, with proper analysis of the impact of a ­proposed workaround on business process agility/scalability.

Cognitive computing requires more than just a collection of advanced algorithms. It involves the use of massively parallel processing (MPP) architectures to coordinate the interaction of the various natural language processing (NLP), machine learning (ML), statistical, and other algorithms as well as the retrieval and integration of data acquired from different systems. This enables processing to arrive at an intelligent decision or outcome when analyzing large volumes of data or interpreting a user’s natural language question.

We hope the articles in this issue of CBTJ will advance the state of the knowledge for all readers, regardless of your specific area of interest in fintech. Whether you wish to gain an overview of the emerging fintech themes, broaden your knowledge of blockchain technology, or understand the impact these technologies are having on the insurance and payments industries, there are learnings for you here as you continue on your fintech journey. 

Generating new revenue streams, collaborating with customers and business partners, sensing customer sentiment — there are many reasons to adopt social media. But what is the best way to go about it, and how can you measure the results once you have? Is there a model for getting started?

Businesses cannot establish a culture that is characterized by innovation until they intentionally adopt patterns and practices that enable innovation in the organization. Agile software development consists of many practices that businesses can adopt to facilitate innovation. In this Advisor, I highlight three core practices that businesses need to adopt to keep innovation alive in their organizations.

In the early 1980s, one of the events that kicked US artificial intelligence (AI) efforts into high gear was the announcement that the government of Japan was funding the Fifth Generation Project — a project to design a special computer for AI work. The US government promptly followed suit, and US Defense Advanced Research Projects Agency (DARPA) and the military provided grants for US companies to work on their own “Fifth Generation” computers. I mention this because Japan’s National Institute for Advanced Industrial Science and Technology (NIAIST) has just announced that it will fund the development of an AI supercomputer.

Against the background of an evolving digital society, disruptive new concepts in information technology emerge. Cloud, big data, mobility, and social media are just a few of these technologies. Each is disruptive on its own, but as they converge and reinforce each other, the disruption is compounded. This is the new style of IT: the combination of these technologies, forcing organizations to rethink how IT is delivered and, more importantly, how IT is consumed to deliver business value.

The new role of IT distributors is crucial to understand as they become more sophisticated in offering financial solutions that better serve enterprise customers. By structuring financial terms — similar to extending financing solutions from hardware days — IT distributors make it easier to buy cloud.

In this Advisor, I look at some key issues organizations should consider that could potentially hinder their adoption of cognitive advisory and decision support systems as well as the continued growth of cognitive computing in general.

When we look at an organization as a whole and ask ourselves where we can make the biggest improvement, it’s probably not in the development process. If the developers are using Agile, they have already made gains simply by adopting the time box. There are certainly things that can be improved, but I would argue that the real opportunity for improvement lies in the remainder of the organization that is often operating with little or no observable process at all.

In our experience, one of the most important attributes in the success of top-performing organizations is a collective mindset that differentiates them through a deeper understanding of their customers.

The excitement of location awareness in apps and websites has passed; people are looking for the next evolution in the location arena. If you’re looking to see where your investment in location technologies might go next, the five examples in this Advisor are a good starting place. They all represent different approaches to the idea that location isn’t enough. Location — even with the best interactive mapping technologies — is one-dimensional. When you add things to it, you expand it across many useful dimensions of information and — more important — action.

Architecture is an organization function, just like the many other functions. And, it therefore needs to deal with many of the same issues that, say, finance, needs to deal with. Many of these issues are readily apparent if we get in touch with the intrinsic nature of organizations and what they consist of. Sometimes, this “dust” isn’t as visible because it is often swept under the wide rug of “architecture leadership.” This would be okay as long as there is a clear understanding of what architecture leadership is, but if it becomes just an amorphous catchall, it may end up hiding important organizational behaviors and patterns that lie unaddressed and untapped.

A value archetype is a basic model for value creation based on digital data streams (DDS). Archetypes are not exclusive classes of value creation, meaning you can adopt one for a specific set of customers and another for a different set. In classifying companies, consider the five value archetypes described in this Advisor.

In my experience, I've found that IT executives operate, understandably, on a diet of logic, rationality, and the search for the "right" way. This reliance on finding and applying the one and only answer — the "truth" — prevails despite numerous technical advances over the years that have disproved previously held IT "truths." In contrast, business leaders are beginning to realize that today's complex world means that there is perhaps no single truth, no one easy strategy to achieve competitive advantage and add value.

Having an Agile organization attracts a different type of employee, guarantees Agile market behavior, and is fun to work in. It is a sufficient precondition to resilience and fast market reaction, but not a necessary one.

Application programming interfaces (APIs) are both perennial and ubiquitous in computing. They've been around since the beginning and occur at every level of the IT stack — from software-hardware interaction through system software to applications. They reside in protocols, libraries, and frameworks; in fact, they are intrinsic to the design of programming languages themselves. This raises the question: how can something so commonplace be causing so much excitement?

While there are many ways to represent a business pattern, there is also value in having a more formal or consistent model. At the other extreme, it would be a mistake to be too rigorous by only ever applying one modeling approach. As a general principle, any model must be suitable for the use to which it is applied.