In this Advisor, we align the Agile leadership framework to the key players in the Scrum process.

While the name DevOps points toward a merger of the role of the developer (creating software) and operations (making software run), this is not really the case. What DevOps does is automate as much as possible the work of operation, and in a way that is comfortable and usable by developers.

Analytics can be performed at various points in the deployment of a solution. Certainly, there are situations where “localized” analytics may be more appropriate than analytics performed in the cloud, and still others where analytics on the organization’s network might be more appropriate. The location of analytics can also determine where and when to integrate data into the analytical solution.

This Advisor describes the first step in implementing a digital backbone: scoping. It draws on the lessons the author has learned in his work with transformational change in technology organizations.

Blockchain’s cryptographic capabilities can be applied directly to the business process, via the distributed ledger and data flow, obviating the need for third parties and ensuring privacy and confidentiality. In this Advisor, we present an example of blockchain’s use in the financial industry.

Among all metrics, share of wallet has evolved into the go-to financial metric for customer experience because it is a true measure — relative to alternatives — of how customers spend their money at the point of sale.

To develop an exponentially growing Lean/Agile organization that will have the capabilities to meet uncertainty/unpredictability and adaptability/maneuverability on demand, we must develop the potential of its people with a primary emphasis on designing and developing the whole organizational system(s).

This Advisor lists some career options for business architects who have successfully mastered the role and want to advance further.

In this Advisor, we focus on F.A. Hayak’s essay “Competition as a Discovery Procedure” from New Studies in Philosophy, Politics, Economics and the History of Ideas 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.”

The artificial intelligence (AI) technology organizations are most interested in adopting is predictive analytics, according to nearly 80% of the respondents in our ongoing survey examining the adoption and application of AI technology in the enterprise.

It is crucial that good customer experience (CX) embraces change since it is a given that customers will change as they learn more and continue to engage. This implies the need for a continuous conversation with customers that is more ­­­­­of a continual interaction rather than a face-to-face conversation. It is a way of doing things rather than a thing itself.

A recent debate between two human debaters and IBM’s Project Debater effectively showed that Project Debater could interact in a human debate scenario. This Advisor examines Project Debater’s functionality.

To cope with the disruption of digital transformation, an incumbent should combine its advantages with those of insurtechs, including a service mindset.

Big data analytics is becoming more effective with cloud computing. The cloud shifts the analytical computing activities to a centralized, shared server. Thus, the data and its processing are housed away from the devices used to access the data and display (visualize) the results. 

It’s not always clear where to begin on analytics projects. This Advisor provides some guidelines on how your business can get started.

In this Advisor, I offer one company’s experience of moving to a cloud HRIS system.

The components embedded in the Data Value Map (DVM) provide a foundational shared language that allows meaningful group conversations to take place; conversations that all parties can understand and to which they can contribute. The two examples illustrated in this Advisor demonstrate how the DVM can help build a shared understanding around organizational data strategies and data projects.

The knowledgebase is the foundation of business architecture. Without it, we cannot achieve the benefits and vision that the discipline intends to provide. A business architecture knowledgebase enables an organization to do the following:

With the rise of social media, big data, and the heightened emphasis on the customer experience (CX), it is more important than ever to build an organizational leadership team committed and laser-focused on implementing the necessary behaviors and orienting business operations to continuously improve CX.

According to our research, the biggest obstacle to enterprise artificial intelligence (AI) adoption is a lack of available experts skilled in AI development. So how are organizations meeting or planning to meet their AI implementation needs? Results from our ongoing survey examining the adoption and application of AI technology in the enterprise — based on the initial responses from 107 participating organizations worldwide — helps to somewhat clarify this question.

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.

For nearly all counter-strategies, a company must look at its digital assets in relation to each other and to the present digital landscape — that is, the enterprise architecture.

Here, 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.

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