This Advisor explores two key ways in which the concept of business design can help bolster artificial intelligence (AI): by improving the customer experience and by identifying and protecting the data that powers AI.

Our role as software architects is, first and foremost, to stay in our lane; we are not epidemiologists and should not share our opinions about the right course of action for anyone other than ourselves. The resulting, emergent, unpredictable result of these millions of decisions will shape our future for a long time to come.

As the novel coronavirus contagion rages, governments and commercial enterprises are utilizing blockchain to better manage the disease and mitigate its impact. This Advisor explores how the pandemic is driving the use of blockchain technology across the globe.

Working agreements establish the ground rules needed to encourage acceptable behavior, create depend­ability, and foster consistency in day-to-day work. They also signal the intent of the individual employees to work together as a team.

With announcements on two regulations, one addressing the certification of unmanned aircraft and the other the certification of carriers using drones for delivery, the FAA revealed the regulatory framework that accom­modates commercial package delivery by drones.

My studies of enterprise architecture 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. As we explore in this Advisor, we can use these empirically observed generalities to synthesize a simple, heuristic three-step approach for designing organization-specific architecture functions.

Everything is not equal. Are you able to separate the things that really really matter from those that are less significant? Is your definition of “architectural significance” clear enough to help your enterprise deal with different shades with different treatments?

After a decade of data lakes, their architectural foundation is as muddy as ever.

In her on-demand webinar, “Innovation Models Across Industries: A Linear or Complex Path?” Cutter Consortium Senior Consultant Katia Passerini considers innovation across many of the key sectors that are being — or will be — disrupted by technology. In this Advisor, we share some of the questions addressed in the Q&A portion of the webinar.

Finding systemic solutions to emotional regulation and social problem solving should significantly improve project performance. This Advisor offers some ideas for project leaders to help solve problems linked to social and emotional cognition.

To effectively manage this “digital shift,” enterprises must not only consider how business processes need to evolve, but also how the people within the enter­prise can become its advocates. More so even than technology, it is the human factor that ultimately determines the success or failure of such a project. This issue of Cutter Business Technology Journal (CBTJ) examines the challenges that arise, along with the opportunities presented by the digital shift from a variety of viewpoints, with a particular focus on the human factor.

Data architects need to strike the right balance between addressing data stakeholder pain points and gathering information to build and enhance the data architecture.

The use of machine learning, predictive analytics, natural language processing, smartbots, and other artificial intelligence technologies to automate complex business processes is not new. What is new is the integration of such technologies so that they execute within the workflows of robotic process automation (RPA) platforms to support intelligent process automation.

More and more, companies are looking to Agile technology teams for a model of behavior for the rest of the business. Agile teams work more holistically toward outcomes, make more strategic tradeoffs, are more transparent and responsive, and so on. If your team doesn't make software but you want to be more Agile, what can you do?

In this Advisor, Stijn Viaene has distilled five conditions for digital transformation success at the highest level that have emerged from his research.

With the onset of a myriad of new technologies, such as 5G, network functional virtualization (NFV), and the Internet of Things (IoT), executives are increasingly realizing that transformation of their technology organizations is imminent. As we explore in this Advisor, the CTO office — the center of technology transformation — needs to rethink its strategic roadmap and operating model. 

A data integration strategy and information management within a sizeable organization can be incredibly difficult to define and even more difficult to imple­ment. Organizations need a way to manage data while making the best use of avail­able and appropriate technology platforms to process all of the different types of data within an organization.

The current trend indicates that most organizations tend to rely on (or are planning to rely on) in-house CX development, while just under 30% of organizations surveyed said that they were using or planning to use outside specialists to assist them with implementing their CX strategies and programs. I see this trend changing over the next 12-16 months, with the use of outside CX consultancies increasing in order to satisfy current and future demands for CX adoption.

In this Advisor, we examine five measures to demonstrate success in continuous integration and testing efforts.

In this Advisor, we examine autonomous systems. These systems are on track to find widespread adoption. They will be a game changer and will propel new research, development, and business opportunities. It’s no wonder they are attracting the interest of researchers, manufacturers, and users alike.

Recent research by Cutter Consortium shows that organizations view CX as appropriate for a number of use cases and domains. In this Advisor, we look at three of those areas: customer engagement, customer relationship management, and customer self-service and advisory systems.

To bridge the divide between the general understanding of the concepts that drive the business model and the departments and teams into which the employees have been divided, the organization has to make the leap from a model-driven data architecture to a model-driven organization; it has to derive its own structure from the logical design.

The early emergence of a new, potentially viral term — a “lakehouse” — suggests another wave of fuzzy thinking is about to infect the data architecture space.

In the webinar, “Overcoming the Industry 4.0 Skills Shortage,” Barry M. O'Reilly discussed the skills shortage that is both inevitable and predictable when businesses try to solve problems with Industry 4.0, which is less about automating old processes and more about inventing a new world in which computing drives business rather than mirrors it. It is apparent that we cannot simply continue as we have in the past. Educating engineers faster, matching them to jobs more easily, and simply doing “the same old thing” has not solved the earlier skills crises — and Industry 4.0 presents even tougher challenges than what we have experienced thus far. In this Advisor, Barry shares some responses to questions following the webinar.

I often describe the strategic risk management of emerging technology and disruptive business models as a combination of continuity and change. Striking the balance is often difficult in a high-stakes, rapidly changing environment. However, one should find comfort and guidance in the fact that while the tech­nical components change, the principles of risk manage­ment remain the same. The trick is to understand the technology enough and apply the appropriate mitigation strategy to de-risk the solution while striking a balance between business value and the assumption of too much organizational risk.