One thing must be understood clearly for an Agile approach to be applied to a data warehouse or any other BI development: user value is not found in the application, but rather in the information availability for reporting and analysis. Next to the availability of information, the data warehouse can provide additional value to the user by providing insight into the sourcing of data and the quality of the resulting information.

In this Executive Update, I wish to argue that, whatever one thinks of F.A. Hayek’s politics, his work has vital insights to offer those advancing Lean/Agile/DevOps ideas for software development. Here, I focus on his essay “Competition as a Discovery Procedure” and note how similar Hayek’s vision for the role of competition in the market is to the Agile understanding of the importance of the “development” part of the phrase “software development.”

Whether we choose to face it or not, digital disruption is here to stay. Whether we choose to accept it or not, digital disruption will affect every enterprise. The jury on our digitized future is still out, and it may be some time before it comes to a unanimous conclusion. In the meantime, there are plenty of serious writers and researchers who predict some significant changes in our world. In this Advisor, I sketch some of these ideas so that you can consider them in your future planning scenarios.

In this Executive Update, we present the Data Value Map (DVM), a discursive template that facilitates the development of a shared understanding around data. The template helps enable open conver­sations and a co-construction of understanding between the parties involved, which can promote a value-driven approach to data projects.

In this Executive Update, we present the Data Value Map (DVM), a discursive template that facilitates the development of a shared understanding around data. The template helps enable open conver­sations and a co-construction of understanding between the parties involved, which can promote a value-driven approach to data projects.

A key question I’ve had for some time is: how well are enterprise AI applications living up to expectations? Initial results from our ongoing survey covering the adoption and application of AI technology (based on initial responses from 105 participating organizations) provides some insight into this question.

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.

The real “lean” in the Lean world (or the “agile” in the Agile world) will manifest only when an organization’s focus is on the development of the whole organizational system.

One way to better understand the customer is through data about that customer.

The ever-increasing demand for cloud computing services deployed across multiple cloud data centers (CDCs) necessitates a significant amount of power, resulting in high carbon emissions and a negative effect on the environment. In sustainable cloud computing, renewable energy resources power the cloud data centers, replacing the conventional fossil fuel–based grid electricity or brown energy to effectively reduce carbon emissions.

Agile organizations need a description of how teams work from beginning to end. The Agile product development framework will illustrate how operational and delivery risks are evaluated and reduced in an innovative environment.

Designing cognitive computing systems (CCSs) requires a strong case for the investment into those systems. Organizations must not only be able to justify the initial investment into developing a CCS, but also think through the investments that will be needed to ensure it can be refined and enhanced over time.

The objective of this Update is to present an overview of an Agile development framework (ADF) as a set of different perspectives covering artifacts, roles, and activities, as the elements that populate the framework. Using a set of views, it suggests how this set of perspectives and elements may help us, as business analysts, in our understanding of Agile development and where we could next explore the ADF in more detail.

Many enterprise architecture (EA) teams struggle with creating a program that demonstrates the level of strategic value that they believe EA should have. Taking actionable steps to remove many of the most common roadblocks to growing the strategic nature of your EA program takes time. For most programs beginning the journey to strategic engagement, I strongly recommend dividing up the enterprise into business segments and applying EA to one (or at most two) segment(s) at a time.

Our latest research indicates that organizations overwhelmingly view customer engagement/customer experience management as the most viable use case for applying AI. This finding comes from an ongoing Cutter Consortium survey covering the adoption and application of AI and machine learning technology, based on the initial responses from 105 participating organizations.

Does culture drive success, or is culture emerging from the implementation of carefully considered strategy, structure, and processes inside the organization? Our view is the latter, and the good news is that culture is something that executives can affect.

This Advisor describes three areas of customer experience that are affected by digital transformation: customer understanding, top-line growth, and customer touchpoints.

We can define the real test of maturity through a key set of characteristics that demonstrate acceptance of, and commitment to, the discipline.

In this Advisor, we highlight a few AI applications that Indian banks have implemented to enhance customer experience. 

We hope the articles in this issue provide you with new perspectives on blockchain’s potential as a game-changing technology now and in the future.

2018 is a defining year for the commercial adoption of blockchain. Initiatives in various industries have reached a maturity threshold, marked by a transition of focus from experimental proof of concept projects toward production use.

2018 is a defining year for the commercial adoption of blockchain. Initiatives in various industries have reached a maturity threshold, marked by a transition of focus from experimental proof of concept projects toward production use.

With all the focus on “exciting” AI applications, it’s sometimes hard to get a broader overview of how the market is actually developing.

DevOps practices and cloud platforms can catapult enterprise technology forward, improving consumer responsiveness, time to market, throughput, and resilience, but they depend on continuous improvement to become internalized and self-sustaining.

Blockchain protocols have the potential to facilitate a fundamental shift in the Internet business model from its current status, where the user is the product, to a future model, where the user is the customer and the user’s data always remains in the user’s control.