Most of us will have some intuitive criteria for judging what data is valuable. These intuitive criteria may be good enough for simple and familiar operations, but when we start to address more complex and dynamic ones, we need a more systematic method for assigning value to data. In this Executive Update, we look at some of the challenges of putting a monetary or nonmonetary value on your data assets.

Most of us will have some intuitive criteria for judging what data is valuable. These intuitive criteria may be good enough for simple and familiar operations, but when we start to address more complex and dynamic ones, we need a more systematic method for assigning value to data. In this Executive Update, we look at some of the challenges of putting a monetary or nonmonetary value on your data assets.

In this on-demand recording of part 1 of this webinar series, you'll discover why you need to consider AI and ML approaches to risk management and learn from the case study of a pharma organization that used AI/ML-based risk models to determine exactly when to restart its clinical trials during the Coronavirus pandemic.

The job of the IT strategy isn’t to align to the business strategy. It’s to give the business people who create it as many options to change tack as possible. It’s a provider of IT capability in support of strategic business capabilities. Supporting, enabling, and aligning with core business capabilities equals competitive advantage when the business strategy is a good one.

Rapid and unprecedented changes to the unemployment laws have created both a tidal wave of transactions that need to be processed, and significant changes to the programmed business processes that execute those transactions. Those business processes are entombed in old COBOL code on old mainframe systems. People are starting to panic about needing COBOL programmers. Yes, but.…

Rapid and unprecedented changes to the unemployment laws have created both a tidal wave of transactions that need to be processed, and significant changes to the programmed business processes that execute those transactions. Those business processes are entombed in old COBOL code on old mainframe systems. People are starting to panic about needing COBOL programmers. Yes, but.…

In this Advisor, Rich Huebner shares some of his thoughts about how the COVID-19 pandemic is going to fundamentally change the education industry, in particular, and offers some lessons learned for other industries as well.

Artificial intelligence (AI), machine learning (ML), and big data are expected to have a huge impact on how we live and what we choose to do. Most categories involving these technologies focus on specific lifestyle items like shopping, dining, movies, and so forth. But such customer-centric categories lack specificity from the investor’s eye. In this Advisor, we redrew the categories on which AI/ML and big data startups should focus.

Enterprises must move away from the old model of centralized decision making to a model of public self-governance. Away from monarchy and toward democracy, giving teams the knowledge and authority to make decisions in the open.

In a broad Arthur D. Little (ADL) study, we interviewed 30+ industry and technology experts along the automotive value chain (i.e., OEMs, suppliers, distributors, and end customers) in Europe, North America, and Asia. This Executive Update highlights the biggest challenges, barriers, and implications for vehicle design and the industry’s business models.

In a broad Arthur D. Little (ADL) study, we interviewed 30+ industry and technology experts along the automotive value chain (i.e., OEMs, suppliers, distributors, and end customers) in Europe, North America, and Asia. This Executive Update highlights the biggest challenges, barriers, and implications for vehicle design and the industry’s business models.

In Part X of this Executive Update series on customer experience (CX) management in the enterprise, we examine survey findings pertaining to how organizations view their CX efforts to date.

In Part X of this Executive Update series on customer experience (CX) management in the enterprise, we examine survey findings pertaining to how organizations view their CX efforts to date.

in this edition of The Cutter Edge, we explore decision making lessons in wartime medicine, the impact of COVID-19 on the business technology sector, managing risk with AI and machine learning, and more!

As a result of the pandemic, we are witnessing increasing interest by organizations for utilizing natural language processing and speech recognition solutions targeted at customer engagement and support — particularly in the form of smartbots, intelligent assistants, conversational computing, and other applications designed to automate customer requests and assist human agents with contact/call center operations. In this Advisor, we examine some of the types of NLP and speech solutions available to organizations and consider some of the issues to keep in mind when it comes to employing such offerings.

As of this writing, we have no firm idea of the human and economic toll to expect from the COVID-19 pandemic or how long painful countermeasures will be necessary. A crisis? For sure. Let’s not waste it; let’s learn from it. Our forced adaptation to a totally unfamiliar world can and should cause us to critically examine assumptions about how we live and work and conduct business. There is a broad spectrum of possibilities, but this Advisor focuses on where IT plays a major role.

Eric Willeke’s look at whether we’ve missed a turn somewhere on the path. Perhaps we need to gene-splice some deliberate characteristics into our next incarnation of Agile. Forget whether we’re picking the right approach: Are we asking the right questions? Are we even asking questions? Do we know what we want to be? Are we even Agile for the right reasons?

Matt Ganis, Michael Ackerbauer, and Nicholas Cariello tee up our CBTJ discussion directly from where the “What will it take?” question leaves off. They look at the challenges and missteps associated with Agile, beginning with adopt­ion, which relies on expectation setting. And there’s no expectation setting without education. Can it be that simple? Occam’s razor says, “Probably.”

Cutter Consortium Senior Consultant Masa K. Maeda schools us in some hard-hitting, data-driven food for (evolutionary) thought. He helps us understand what we should be looking for when considering an agility path. It’s no simple checklist or algorithm. Maeda’s outline makes us take a holistic look at our environment; at our choice of primordial soup, as it were. The good news is that we are not completely afloat in the flotsam of the universe. We can choose how we evolve.

This CBTJ issue takes us on an evolutionary journey of Agile. In a rather normalized bell curve, we start with fundamentals and progress through more advanced concepts. We then ease back with practical steps forward and wrap up with a cautionary send-off. The good news is that you’re free to take the journey, or wait for the asteroid. Your call.

The COVID-19 pandemic has altered the risk landscape for businesses around the globe. Enterprises are learning firsthand whether the business resilience and business continuity plans they put in place are proving successful or not. In light of this crisis, it’s crucial now more than ever to reevaluate your risk management process and ensure you are well prepared for what may lie ahead. As an executive, this involves adapting your leadership and facing the current crisis head-on with a proactive approach to risk management.

Jeff Doolittle helps us to set out on our own path to disruption. He suggests the most drastically disruptive action: don’t do Agile. At the very least, don’t do Agile the way too many others are doing Agile. Doolittle invokes the same line of thinking that started our thought experiment to begin with — what has Agile become? Has it grown in unintended ways? Have we lost what it is supposed to be? What else is there if not Agile? Should we completely abandon Agile? Wouldn’t that be disruptive!

Bob Galen picks up on this issue's evolution theme and goes back to basics. When pursuing Agile, which comes first: the chicken or the egg? Clearly not making breakfast, Galen takes aim at whether teams or leadership “goes Agile” first. He gives us a taste for what it must look like to have teams come first and what seasonings to pepper leadership with so that leadership and teams can be “Agile-y” effective together.

Many organizations today struggle with a strong disconnect between their business model and their IT systems, data distributed over a large number of nonintegrated IT systems, manual interfaces between incompatible applications, or difficulties with EU GDPR compliance. We can trace most, if not all, of these issues back to an abundance of unspecific, inflexible, and non­aligned data models underlying the applications these organizations use to conduct their business. Often, these data models have been developed with insufficient business involvement and in isolation from each other — or have been purchased from vendors with little concern for the actual needs of the organization. In this Advisor, we briefly describe the origins of some of these issues.