In this Advisor, I describe some important AI developments we are seeing with the IoT.

The Internet offered wide access, and the smartphone offered direct and personalized access to the insurance customer. What can AI offer?

Can the same path to Agile transformation work for every organization? Does every organization need to go through the same number of steps? Do the organization’s culture, technological landscape, and customer needs necessitate a customized model of such a transformation? In this Advisor, we identify the five elements of design thinking as key principles that every Agile transformation should follow.

We have developed a simple yet powerful framework to help business leaders navigate the digital landscape based on four business-focused questions that are at the core of effective governance of digital. We call these questions the four “ares.” In our previous Advisor, we discussed the first two of the “ares”: Are we doing the right things? and Are we doing them the right way? This Advisor explores the two that remain.

In this Advisor, we examine how fog architecture addresses cybersecurity for next-generation networks.

Agile-at-scale relates to scaling Agile methods for software development use enterprise-wide or on large software development efforts. Scaling has been key as organizations try to tap the benefits of Agile methods to deliver their software products quicker, more cheaply, and with higher quality. This Executive Update presents conclusions based on the analysis of data from over 5,000 software projects fielded by about 500 organizations.

“A culture transformed” means reaching an elusive cultural end state within a business. There are mile markers on this transformative journey, many of them technological, but rarely do we include cultural milestones within the scope of a digital transformation project.

In this Advisor, I introduce an Agile development framework (ADF); not a mainstream Agile offering like Scrum, but rather something I tend to carry around in my head when trying to think about the various views, products, roles, and tasks that a multidisciplined team can bring to bear for different types of Agile projects.

Customer expectations are shaped by their interactions with Uber, Amazon, and Apple — where each interaction is intuitive, easy, and instant. In customers’ eyes, the age, size, and complexity of the organization or industry are all irrelevant: all they care about is having a great experience. Traditional organizations have no choice but to step up their game to stay relevant.

Your business architecture knowledgebase should include content for each business architecture domain that you have determined to be applicable for your organization (most or all usually apply). The content for each domain includes names, attributes, and relationships to business architecture domains as well as other domains (e.g., system applications). The knowledgebase can be created and refined over time.

Artificial intelligence (AI) has reached the point where most major organizations are now investing in the technology. But, a key question I have had for some time now is: to what extent are organizations deriving measurable benefits from the AI applications they have deployed? Fortunately, the latest results from our ongoing survey examining the adoption and application of AI technology in the enterprise offer some insight into this question.

Despite general agreement among researchers and academics of the need for board-level involvement in IT governance, it appears that in practice this is more the exception than the rule. Given the prevalence of this issue, we have sought to answer the question, “What is the state of the art of the research domain of board-level IT governance?” In this Executive Update, we share our findings on the various determinants, theories, and outcomes surrounding board-level IT governance and share some practical guidance.

Despite general agreement among researchers and academics of the need for board-level involvement in IT governance, it appears that in practice this is more the exception than the rule. Given the prevalence of this issue, we have sought to answer the question, “What is the state of the art of the research domain of board-level IT governance?” In this Executive Update, we share our findings on the various determinants, theories, and outcomes surrounding board-level IT governance and share some practical guidance.

In this Advisor, I highlight the need to understand the optimal granularity level in analytics to maximize business value. I also point to the need for business owners and strategists to incorporate context in analytics in a balanced manner in ascertaining the granularity levels. Granularity levels can vary dynamically depending on the needs of the business. Due consideration to such dynamicity ensures that time, cost, and corresponding use of resourcing in undertaking analytics are all utilized to provide maximum value to the business.

APIs are bringing about new opportunities by creating new channels for partnerships, promoting brands, and experimenting with customer-influenced innovative solutions and alternate business models. In this Advisor, I explore the spectrum of APIs. Knowing the spectrum of APIs and how they work helps formulate and guide API and software strategy, aids in decision making on interfacing architecture, and helps assess readiness from business, technical, compliance, and risk perspectives.

Traditional analytics is generally restricted to merely providing a better understanding of historical data or predicting future business outcomes. Consequently, the potential of traditional analytical processes is limited as they only offer insights and patterns based on data provided but they lack the ability to offer or make business recommendations. Prescriptive analytics, however, is substantially different and more powerful because it allows businesses to not only make predictions but also suggests an optimal solution.

This Advisor considers the impact of the Internet of Things (IoT) on traditional business and technology architectures and introduces the role of EA as an effective methodology for developing and implementing IoT strategies. 

Here in Part III, we begin to explore what type of process might be employed at a business analysis level when using the ADF, starting with an examination of some ADF activities and thinking about the inputs, steps, and outputs produced. We then delve into how business analysis fits into the ADF for the early and continuous delivery of valuable system capabilities.

Empowering the people who face the customer to drive business decisions is a hallmark of the Agile organization. Agile leadership, explored in this Advisor, replaces command and control in the Agile organization.

The new frontier for competition is the entire customer experience (CX) — from thinking about a purchase to the renewal (of a service) or replacement (of a product).

The best response to digital disruption from the EA team is to examine the dis­ruption, understand the implications in terms of the components and configuration of the architecture (i.e., translate them into architectural thinking), and present options for responding as potential changes to the architecture. The important thing is to present these options as clearly as possible so that stakeholders can make architecturally informed decisions.

Core computer vision and imaging technologies include facial recognition, image recognition, character recognition, medical image recognition, video analysis, and autonomous driving visioning systems. Organizations are now applying such core vision and image recognition technologies to enhance a myriad of applications across many industries.

Understanding certain perspectives of privacy allows us to detail why it is important in the context of blockchain, distributed ledger, and smart contract technology. Thus, questioning the importance of privacy to anyone deploying the technology, using the technology, or regulating the technology, is important. How is a blockchain different than any database? How is it used differently than normal databases? What are the implications of deploying an immutable record of information in a distributed consensus network? How is the technology used in blockchains different from any other information or data storage technology? These are the questions firms should be asking as they attempt to understand the concept and its implications on an active, and evolving, basis.

While cash still has its place in society, we cannot ignore the growing digitization of money. If digital forms of commerce simplify users’ lives and make it easier for customers to get what they want, when they want it, we can expect to see a much more rapid migration toward merchant mobile applications.

This Advisor offers a model that identifies the big data capa­bilities needed to connect data analysis with a specific business context and to do it quickly.