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.

Cognitive computing is beginning to impact a range of industries due to its ability to ingest, analyze, and summarize massive data sets and facilitate self-service analytics, intelligent decision support, and smart advisory systems via the application of natural language processing (NLP), machine learning (ML), and intelligent reasoning capabilities. 

What you need to drive your digital transformation is a realistic stakeholders’ consensus about the purpose, expected results (for your customers and your organization), and a roadmap of actions to deliver those results. Such a consensus requires you to create a shared understanding about the nature of the digital business economic environment.

The most common pressures driving Agile data analytics investments are data stored in silos and poor data quality impacting decision making. Both complaints betray the burden of legacy business systems and analytics. Data in back-end IT systems is very often difficult to access, difficult to integrate, difficult to normalize, and therefore difficult to harness to answer the questions posed by the business. Mired in these inflexible and out-of-date sources of data, the efforts to create front-end tools and reports will have limited success.

By leveraging business architecture as the mechanism to connect across business areas and drive toward a collective intent, IT will be in a better position to plan its strategy and roadmaps. What comes down the pipe from the business should be self-consistent and offer a holistic picture of the collective intent of the organization.

This issue of Cutter Business Technology Journal is focused on cognitive computing. Cognitive computing is a term that is similar to, but currently more popular than, artificial intelligence (AI), and it refers to all those innovations in computing that are being driven by various types of AI research. Now is the time to start thinking about how to transform your organization with cognitive computing.

Where in security practice do we turn for inspiration when it comes to protecting our well-being and health from cyberattacks?

Research and discovery are big application areas for applying cognitive techniques, including for financial market analysis, marketing, and product development. Several versions of IBM’s Watson technology, in the form of focused applications, are now being utilized by banking and financial companies in these roles. In addition, commercial cognitive solutions such as Kenshoo, targeted specifically at supporting financial market research, are also available.

The transformation to an Agile culture starts with an understanding of what we mean by culture.

One of the biggest organizational design (OD) challenges facing many organizations is the switch from the more structured, hierarchical forms that were effective in the Industrial Age to more fluid, networked structures that are more appropriate in the Information Age. This is an often unspoken transition that lies at the heart of many enterprise architecture (EA) projects.

While some know-what is vital to understanding long-term implications of the IoT, organizations must begin generating know-how if they are to begin harvesting the potential of this emerging (and likely disruptive) technological paradigm.

Watson Virtual Agent is an important development because it aims to streamline the process of implementing intelligent agents and bots.