While the software industry is currently grappling with ideas of complexity and resilience, there has been very little in the way of concrete actions or activities that software engineers can use to actually design systems. Residuality theory answers this need and draws on complexity science and the history of software engineering to propose a new set of design techniques that make it possible to integrate these two fields.

My studies of enterprise architecture (EA) practices in multiple diverse organizations have identified several consistent patterns describing the size and structure of architecture functions that companies tend to find optimal for their needs. We can use these empirically observed generalities to synthesize a simple, heuristic three-step approach for designing organization-specific architecture functions.

Intelligent automation applications are reaching the point where both organizations and governments must create policies regulating the use of and the liability associated with using smart technologies.

This Advisor looks at three of the challenges facing customer experience (CX) initiatives in the enterprise: problems providing seamless CX across all customer channels, a lack of CX professionals in the organization, and difficulty defining/mapping CX.

A primary motivation of decentralized social media is censorship resistance, often achieved through anonymity. But anonymity comes with a price. Checking the reliability and trustworthiness of information is much harder with anonymous information. In this Advisor, we present a brief overview of two main under­lying technologies that help in decentralization while still providing a degree of trust between networked entities: (1) P2P social networks and (2) blockchain technology.

Even those who recognize the advantages of a cloud-based remote access platform over a VPN might argue that the current WFH solution is a temporary anomaly. In that case, why not just muddle through with a VPN until things get back to normal?

We have typically found in the acquisition process that EA is primarily a technical capability and engaged in a constrained fashion. In most firms, the EA team does not possess the necessary critical business knowledge and, therefore, is not able to contribute to the acquisition process through direct engagement. At some pioneering firms, however, the reformation of EA has explicitly aimed to build a business strategy competence in the EA team by giving enterprise architect roles the responsibility for business and operations architectures.

An important trend is the development of emotion recognition technology for speech-based systems with the goal of optimized customer engagement while providing an enhanced customer experience.

A new wave of innovation within healthcare is driving the need for more advanced, robust, and scalable hospital information systems (HIS). Healthcare providers — hospitals, in particular — are starting to reorient their investments in core technologies and how technology vendors are adapting their solutions and services to meet these needs. Here in Part II of this two-part series of Advisors, we look at three challenges of digitalization as well as eight key trends changing the HIS solution space.

Despite research limitations, the psychological basis for estimation biases is much clearer now than several decades ago, and these insights can have a positive impact on the practice of project management.

Leaders peering over the edge of the horizon of their own and adjacent industries might wonder, “What are companies that have achieved digital success doing differently?” We believe that at the heart of the ability to manage an ongoing and multilayered organizational transformation rests a sophisticated enterprise architecture capability with a specific charter to act as a transformation engine connecting strategic intent and execution excellence.

Enterprises are expanding their API programs to include the broader concerns of enterprise architecture. In this Advisor, we describe some next steps for evolving your API platform.

To mitigate cybersecurity threats, it is essential to understand the cycle of infor­ma­tion security governance and control: preparation, prevention, detection, response, and learning. This information security management cycle provides important guidance to organizations dealing with security incidents. However, in the con­text of Industry 4.0, these five tasks present different challenges. This Advisor explores the challenges of cybersecurity management.

In this two-part Advisor series, we illustrate how healthcare providers — hospitals, in particular — are starting to reorient their investments in core technologies and how technology vendors are adapting their solutions and services to meet these needs. Here in Part I, we focus on the key features of this paradigm shift.

What are the ramifications of moving from a project orientation to a process or product orientation? First, an organization needs to establish an efficient means of production. It must create a funding model and a value stream equipped and staffed with people able to deliver its software requirements. Then the organization must manage the flow of work into that development value stream. The concept of flow is critical to value stream performance. Lean manufacturing principles have established that an overloaded value stream slows down the rate of delivery, increases costs, and decreases quality.

This issue of CBTJ discusses various aspects of corporate crisis management and how business technology can help companies deal with crises of all kinds, but especially those that change everything. Remember that corporate crisis planning and management is a continuous activity that must be acknowledged and well-funded.

Data is not a resource. Data is the breadcrumb trail of human activities. Like a true breadcrumb trail, it indicates the activity but never fully describes it. Data doesn’t fall out of the sky like manna from heaven; it cannot be mined like cobalt, either. Data is a residue of activity, and when you think about data in this way, you can envision a data management practice where you start to fully focus on the activities that bring you value and, therefore, the data you need to collect.

Neural-symbolic artificial intelligence (AI) combines the pattern-recognition and pattern-matching capabilities of neural networks with the symbolic-reasoning functionality and transparency features of rule-based and knowledge-based systems (KBSs). One of the main goals of neural-symbolic AI is the development of hybrid AI systems that are more explainable and transparent in their reasoning.

Robotic process automation (RPA) and artificial intelligence (AI) are complementary – when implemented together they enlarge the scale of value that can be created. In this Advisor, we share some practical insight into how communication service providers (CSPs) and other organizations can embark on the AI-powered RPA opportunity.

This Advisor explores a key question regarding digital transformation among analog-native companies: how can these businesses adapt their organizational structures to accelerate the transformation and build digital maturity?

Leading organizations leverage BA not only to articulate and detail their business strategy, but also to create guidance that drives business and IT execution toward that future-state vision. Business architects can succeed only if they support BA in conjunction and in collaboration with, and maybe integrated with, other closely related disciplines, including business analysis, strategic planning, and portfolio management.

While the current level of trust may be satisfactory for some uses, we must secure a higher level of trust when accessing personal sensitive data. Establishing a trusted Web layer, in which users are uniquely identified and thoroughly authenticated, reduces the lack of trust issue.

Effective risk management begins with a culture in which reality isn’t overwhelmed by hubris. No project manager can be a good risk manager in a political environment in which executives are so gung ho that it blinds them from the reality. Effective risk management requires that executives and project managers make hard tradeoff decisions as the speculative hypotheses we call plans are smashed against the reality of the rough-and-tumble business world.

Several fundamental Agile principles drive behaviors that can improve an organization’s ability to make use of its data. One of the Agile behaviors that is key in identifying and analyzing data, and eventually for designing a solution, is the use of cross-functional teams.