Merchant mobile payment applications represent a first step toward frictionless commerce but achieving this initial milestone has been challenging in the US.

This article provides specific ideas on how to improve CX, larded with examples, good and bad, from literature, case files, and first-hand experience.

As you read through the articles in this month’s issue, we invite you to consider the customer experience that your organization provides and what lessons our authors offer for improving CX and making it great.

As you read through the articles in this month’s issue, we invite you to consider the customer experience that your organization provides and what lessons our authors offer for improving CX and making it great.

I don’t know how to best identify the point in time when computers merged with communications and became customer utilities and entertainment devices, but clearly that transition was a major step toward creating the digital environment we all live in today.

The task organizational leaders face right now is how to turn their companies into resilient organizations. Though this is a question far beyond the scope of an Advisor, there are three basic capabilities resilient systems need to show: speed, flexibility, and diversity.

This Executive Update is the second in a series that focuses on how to accelerate the development of an organization’s business architecture. It explores how to leverage reference models to further accelerate business architecture development.    

Data-driven decision management is an approach to managing business that focuses on decision making that can be backed up with verifiable data.

It used to be that the services and functionality from Amazon Web Services (AWS) could only be afforded by companies with deep pockets and wide technical expertise. Today you can get AWS services at a low price point, making them in reach of nearly every company. But still, you need much of the same technical expertise to truly harvest the power of the cloud and its cost-saving promises.

It used to be that the services and functionality from Amazon Web Services (AWS) could only be afforded by companies with deep pockets and wide technical expertise. Today you can get AWS services at a low price point, making them in reach of nearly every company. But still, you need much of the same technical expertise to truly harvest the power of the cloud and its cost-saving promises.

We need to understand that a customer’s interactions with our company are just a small part of a bigger picture. The sum of the interactions a customer has with our company isn’t the customer experience, that is just part of the whole customer experience.

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.