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.

Data architecture as currently practiced is beset with a range of problems, many of which are described in a recent issue of Cutter Business Technology Journal — as are some solutions to some of the problems. However, I contend that we need to return to basics in decision making and ask how decisions are actually made by people and in organizations.

From the need for more tech­nology regulation to what technologies will be most transformative, from guidelines for keeping our data safe to minimizing the profusion of misinformation — we are sure you’ll find value in the observations in this issue of Cutter Business Technology Journal. We trust that they’ll give you the foresight to proceed with optimism, yet vigilance, into this new decade.

With a systematic way to assess, design, measure, implement, and effec­tively manage data, leaders increase the chances of maximizing the true potential of AI/ML, while meeting the needs of regulators.

Agile budgeting in the value streams is about products, rather than projects, forming the value stream portfolio. A product can already exist and generate value or can be an innovative idea that may turn into a component of the value stream portfolio.

The combination of a blockchain data structure and a set of consensus rules allows something magical to happen: stateless, bankless, digital money (aka cryptocurrency). More precisely, what is loosely described as a cryptocurrency is a fungible “token” that is “native” to a blockchain. The major native tokens can be exchanged for the government-backed fiat currencies we are more used to, but smart contracts can create and maintain special-purpose tokens.

In the webinar, “Envisioning the Organization of the Future: The Cognitive Enterprise,” Cutter Consortium Fellow William Ulrich described the formalisms that underpin the cognitive enterprise vision, the benefits to be accrued under that vision, and the steps your organization can take to begin its journey toward a cognitive enterprise vision while achieving incremental value at each step along the way. This Advisor shares with you some of the questions Bill fielded at the end of the webinar and his responses.  

Transformer-based natural language processing (NLP) models have serious implications for the entire field of NLP — from speech recognition systems to natural language generation (NLG), natural language understanding (NLU), machine translation, and text analysis applications. Consequently, tools for developing transformer-based models have become popular among researchers and developers implementing NLP applications.

To increase the chance for blockchain/distributed ledger technology (DLT) to gain traction and for improved market awareness and adoption of the technology, what should the reference model of the regulatory sandbox dedi­cated for blockchain/DLT technology look like?

To create an organization that can effectively respond to heightened customer centricity and product customization, you need effective and coordinated product development teams. To respond to customer needs quickly, teams need to be autonomous, empowered, self-organizing, and cross-functional. They must take high-level direction from management and then, through intense collaboration, complete work more quickly than their predecessors. In this Advisor, we share our thoughts on putting up guardrails for your teams.

Digital architecture involves internal stakeholders shifting paradigms from thinking of solutions from within to fully incorporating external stakeholders (customers) in the solution design process. Different organizations leverage various approaches to achieve this paradigm shift, but one of the main drivers of digital architecture is customer centricity. This Advisor highlights this driver as well as some of the other most critical ones.

This issue of Cutter Business Technology Journal (CBTJ) continues the conversation we began in our last CBTJ and focuses on blockchain technology adoption beyond cryptocurrencies and financial services. The authors explore areas such as energy and utilities and government and present real examples of successful DLT implementations. They share their practical experiences in overcoming and addressing some of the known issues with blockchain projects.

In the era of open source projects, which enable deep analysis of code, it is doubtful that we can maintain privacy through the ages. Publicly accessible code facilitates consistent improvements and debugging through the regular scrutiny of accessible data. At the same time, it also increases the possibility of finalizing an attack on the network, causing losses and a reduction in trust. As a result, several companies now focus on analyzing blockchains.