Artificial intelligence (AI) in all its various forms — machine learning (ML), natural language processing (NLP), speech recognition, cognitive systems, intelligent agents, chatbots, and robotics — is generating intense interest across every industry — from consumer electronics, banking, and finance to automotive, insurance, healthcare, government, aerospace, big pharma, retail, and manufacturing.

Artificial intelligence (AI) in all its various forms — machine learning (ML), natural language processing (NLP), speech recognition, cognitive systems, intelligent agents, chatbots, and robotics — is generating intense interest across every industry — from consumer electronics, banking, and finance to automotive, insurance, healthcare, government, aerospace, big pharma, retail, and manufacturing.

In this Advisor, we consider what leaders are expected to do within Agile organizations, then see how these duties translate to a set of desired skills and personality traits.

The existence of a digital backbone in an organization means that anyone aspiring and planning to transform different parts of the enterprise will be able to leverage the digital backbone in a consistent and sustainable way, ensuring that each effort connects to and leverages a common platform. 

Even radical approaches to change management, such as business process engineering or Lean, assume there is a desirable endpoint (however temporary) toward which change is directed. However, what if change happens so continuously that no fixed endpoint exists for any initiative, but instead organizations must constantly change, not just to succeed, but even to survive?

Governments are starting to embrace the possibility of creating their own cryptocurrencies.

If electric cars and trucks are the vehicles of the future, then that already suggests a massive change in the industrial infrastructure — new modes of manufacturing, new modes of refueling and repair, and, perhaps, new roads. Given the key role of autos in society, such a transition will be a major story. However, it is really only a small part of the changes facing the automobile industry. As we explore in this Executive Update, other technological changes in the auto industry include: self-driving cars, intelligent auto production processes, and cars as entertainment centers.

If electric cars and trucks are the vehicles of the future, then that already suggests a massive change in the industrial infrastructure — new modes of manufacturing, new modes of refueling and repair, and, perhaps, new roads. Given the key role of autos in society, such a transition will be a major story. However, it is really only a small part of the changes facing the automobile industry. As we explore in this Executive Update, other technological changes in the auto industry include: self-driving cars, intelligent auto production processes, and cars as entertainment centers.

As a second-order effect of the Internet, digital transformation can be broken down across the three major areas that it will transform: customer experience, operational processes, and business models. Although transforming the customer experience is the most visible manifestation of digital transformation, as I discuss in this Advisor, transforming internal processes through digitization, worker enablement, and performance management can also show great benefits.

Both the explosive growth of Agile adoption and the return to collaborative and experiential learning are part of a larger global transformation whereby people are seeking to cast off authority in exchange for autonomy and peer collaboration.

There is an ingrained optimistic spirit infusing the enterprise, creating a bias toward action, toward change, toward better things. And, a resulting need for speed: speed to market, shorter cycles, quicker turnaround, and more throughput. Faster, faster, faster! More Agile. But speed kills. Even avid practitioners of Agile — if we pay attention to some of the current conversations — are generally of the view that Agile is not merely about speed, and that breakneck speed can break necks and more, if “Agile” is simply an excuse to hurtle mindlessly into space.

This Advisor discusses the risks and challenges of implementing prescriptive analytics in the context of machine learning.

In many market sectors, the journey to become more Agile is a strategic imperative. This Advisor looks at some of the reasons some organizations find this transition difficult. These challenges point to the practices, processes, and cultures of the past as potential hurdles.

Researching and writing about the digital backbone has strengthened my initial thesis of the concept due to an overwhelming response to the research and from opportunities to engage with audiences worldwide on the topic. In this Executive Update, I’d like to share some of my own discoveries and insights from conversations with CEOs, chief architects, CIOs, market and sales leaders, as well as innovation leaders across many industries and geographies — what I refer to as my “digital backbone learning lab.”

When successfully deployed and business value-focused, a business architecture practice is a critical enabler for digital transformation.

During this webinar, featuring Cutter Consortium Senior Consultant Philip O'Reilly and four of his colleagues, you'll discover how data harmonization — via the marriage of open industry standards and semantic database technologies — results in improved outcomes in data quality, analytics, risk management, and governance.

How do end-user organizations feel about the potential for AI to disrupt their particular industries and lines of business? An ongoing Cutter Consortium survey that asked 62 organizations about their efforts to adopt and apply AI technology helps provide some insight into this question.

This Executive Update proposes a five-layer customer engagement stack — running from customer dissatisfaction through customer satisfaction, customer delight, customer success, and finally partnership. The maturity level of an engagement between a service provider and a customer is a function of the attitude of the people working with the service provider and the perception formed by the customer.

Entrepreneurial organizations typically have severely limited resources and many last only briefly; consequently, their ability and opportunity to implement knowledge management (KM) practices before suffering the consequences of “knowledge mismanagement” are limited. In fact, one might say that the flat managerial structure and agile business processes characteristic of entrepreneurship are in direct opposition to the somewhat time-consuming and structured processes traditionally associated with KM.

The three challenges described in this Advisor represent those that Agile teams face when attempting to follow enterprise architecture (EA)-level planning and design documents as well as the issues faced by Agile teams when transitioning their products to the operations team.

IT portfolio management is the continuous process of selecting and managing the optimum set of project-oriented initiatives to deliver maximum business value.

By putting the science of numbers, data, and analytical discovery to work we can find out if our assumptions about what is contained in the data are only opinion or truly fact.

In this Executive Update, we explore how digital technologies will play a pivotal role in driving superior passenger experience as well as operational excellence in the journey toward smarter, safer, greener, more secure, and more sustainable airports of the future.

In this Executive Update, we explore how digital technologies will play a pivotal role in driving superior passenger experience as well as operational excellence in the journey toward smarter, safer, greener, more secure, and more sustainable airports of the future.