Joel Nichols discusses the barriers and challenges facing regulated industries as they attempt to implement Industry 4.0 technologies and change their ­cul­ture. The article examines the questions that regu­lated industries must address as they embrace digital trans­formation and the advances that specific Industry 4.0 technologies can yield. The author argues that although digital transformation may require more time in regu­lated than in nonregulated industries, “the impact of regulated industry transformation on producers and consumers alike ultimately will be greater than that of the nonregulated sector.”

Joel Nichols discusses the barriers and challenges facing regulated industries as they attempt to implement Industry 4.0 technologies and change their ­cul­ture. The article examines the questions that regu­lated industries must address as they embrace digital trans­formation and the advances that specific Industry 4.0 technologies can yield. The author argues that although digital transformation may require more time in regu­lated than in nonregulated industries, “the impact of regulated industry transformation on producers and consumers alike ultimately will be greater than that of the nonregulated sector.”

This Advisor shares five practical tips on rolling out “industrial,” scalable robotic process automation solutions based on my experience at a multinational organization.

In this week's edition of The Cutter Edge, we'll explore how to leverage visuals to make your BA initiatives more effective, and examine the five technologies that could help automate your software development efforts.

In this week's edition of The Cutter Edge, we'll explore how to leverage visuals to make your BA initiatives more effective, and examine the five technologies that could help automate your software development efforts.

For most organizations implementing customer experience (CX) management practices, it is still too soon to tell if their practices are living up to expectations.

Our company’s Agile journey across a 2,000+-person product development unit in 10 locations in Sweden, Poland, and China, resulted in a quadrupling of value throughput; a doubling of speed; a tenfold increase in quality; and happier, more engaged people who are, ultimately, more innovative. The company made major shifts in a few areas. In this Advisor, we explore its shift from resource efficiency to flow efficiency.

People’s increased mobility, facilitated by air travel, has resulted in the increased spread of contagion across geopolitical boundaries. A growing awareness that bioterrorism agents could spread in the same way has raised the level of concern even more. Many practitioners and researchers agree that contact tracing, which is the identification and locating of people who may have been in contact with an infected person, represents an important factor in mitigating the spread of a pandemic.

People’s increased mobility, facilitated by air travel, has resulted in the increased spread of contagion across geopolitical boundaries. A growing awareness that bioterrorism agents could spread in the same way has raised the level of concern even more. Many practitioners and researchers agree that contact tracing, which is the identification and locating of people who may have been in contact with an infected person, represents an important factor in mitigating the spread of a pandemic.

About a quarter of surveyed organizations have appointed a “chief customer officer” (CCO) to ensure that the organization provides a unified and seamless customer journey/experience across all customer channels.

Encouraging and developing data-based decision support is an organization-wide effort and requires many resources, including people, money, and technologies. Building an effective decision support capability can help improve decision making, but meeting that goal is a challenging task. So how can senior managers increase the chances of the successful implementation of an enterprise-wide data-based decision support, analytics, or BI project? The answers to the five pivotal questions explored in this Advisor provide some insight.

Financial institutions have digitally transformed their business processes and products, creating vast sources of structured and unstructured data. AI offers the means to complete this transformation in radical ways — across the front, middle, and back offices, while also addressing the big data problem. In addition, AI is also shaping the fintech and regulation (“regtech”) landscapes, particularly in addressing what has become known as “Big Regulation.” However, AI’s promise must be balanced with current limitations to the application of enabling technologies like machine learning (ML) and natural language processing (NLP). This Advisor looks at the promise, potential, and limitations of AI in the financial industry.

The “Recordkeeping for Timely Deposit Insurance Determination” rule from the US Federal Deposit Insurance Corporation (FDIC), or FDIC 370, seems simple but, as we explore in this Executive Update,  it presents several challenges for covered institutions (CIs).

Being able to show that your organization actively considers and cares about its impact on the world is sure to become one of the most important levers for talent and investment attraction and retention. Expectations now go beyond having great-sounding values on your website; people want to practice those values every day and be proud of what they are creating. Investors want to know that they can count on pro­active mitigation. Users want to see those values in the products they use. Consequence scanning requires that participants know what the product or service is intended to do, be able to determine whether the potential consequences of the product or service are positive or negative, and know what their organization considers positive.

Scientific-based modeling systems contain extraord­inary amounts of data and produce mountains of output. These systems offer almost limitless options for providing the user with informed knowledge. This Advisor seeks to use the concept of technology embeddedness to delineate factors that are prohibiting emergency managers from harnessing the capability of scientific modeling systems when responding to disasters.

Ninety-two percent of executives say agility is critical for the future of their business, yet only 4% of their transformation efforts are delivering agility. The leading causes for this gap are an entrenched legacy culture and general resistance to change. Responding to these challenges and delivering business agility may require more than Agile practices. As we explore in this Executive Update, many organizations are discovering “solution focus” to be the missing piece of their transformation puzzle.

Leveraging visuals is particularly important for a business architecture practice. Visuals matter, and for a business architecture practice to be effective, it must connect with people on a human level and in ways that build true under­stand­ing. Graphic recording is the visual live capture of content for an event or meeting, which acts as a visual record of the session. With this technique, there is little to no interaction between the graphic recorder and the speaker and participants. Graphic facilitation also includes visual live capture of the content for an event or meeting, but the graphic facilitator serves as a guide throughout the entire meeting process. These visual techniques bring people together to co-create around a specific topic, challenge, or opportunity. They allow people to “see” their thinking and shape concepts together. 

The field of robotics has benefited considerably from advances in various artificial intelligence (AI) technologies — most notably deep learning neural networks, computer vision, intelligent guidance and control systems, and voice and speech recognition. The biggest advances are being realized from developments in deep learning algorithms and machine vision technologies, which are allowing the creation of robots featuring advanced autonomous navigation and intelligent object recognition capabilities.

Join Cutter Consortium Fellow Lou Mazzucchelli for this Cutter Consortium Members-only peer-to-peer discussion of the potential risks posed by machine learning applications and how to deal with them.

The growing prevalence of the Internet of Things, together with plummeting component costs, has made it possible to connect just about anything, from the very simple to the very complex, and to offer remote access, sensing, control, and monitoring. These technologies make it possible for healthcare providers and patients to work together to improve health in novel ways that were previously unimaginable. A critical element in this new model is that focusing on what is happening with the patient when they are not in front of a health pro­fessional, using sensors to deliver remote monitoring and a more complete picture of an individual’s health, is more likely to have an impact than focusing on the brief amount of time spent during in-person medical visits.

Large, non-software companies introducing Agile to their organizations tend to suffer from a cognitive dissonance of sorts: we would like to have the same look and feel across the entire company, delivering stellar-quality products, yet we want to enable high-performing, self-organizing, self-managed, and self-empowered teams to deliver (or demo) at the end of each sprint. In this Advisor, we summarize one area where this conflict becomes especially evident for large companies, particularly with non-software teams: process misalignment. We also share a potential solution that we’ve seen work in industrial practice.

Here in Part II of this Executive Update series on customer experience (CX) management, we look at survey findings covering budgeting trends for CX initiatives and the status of the “chief customer officer” (CCO) in the enterprise.

Here in Part II of this Executive Update series on customer experience (CX) management, we look at survey findings covering budgeting trends for CX initiatives and the status of the “chief customer officer” (CCO) in the enterprise.

In this Advisor, I have chosen the simple word “change” as a starting point for thinking about architectural change, rather than many of the others in rampant use — words such as “transformation,” “permutation,” “enhancement,” and so on. This choice seems appropriate because “change” is an abstract, neutral, and descriptive word without the deeper connotations that might impede the nuancing of this notion into something of a practical, if rudimentary, taxonomy that will help us grapple better with the different kinds of changes that we are compelled to deal with.

Although recent advances in computing user interfaces for decision support tools make the tools much easier to learn, understand, and manipulate, some decision makers may be reluctant to adopt and use a new decision support tool. Potential users with greater IT knowledge and expertise often find it easier to learn new systems than those who are infrequent users and hence lack knowledge and expertise. Thus, developers should strive to build a decision support capability that targets potential users, matching the design to user needs, abilities, and skills.