Strategic advice to leverage new technologies

Blockchain (in its current and future iterations) will certainly impact various industries and governmental applications. But we will likely derive additional oppor­tunity and value from the convergence of block­chain with other emerging technologies. Data currently created and available from IoT devices, for instance, may very well benefit from some variant of blockchain. Capturing informa­tion from trusted devices and storing it in a distributed model accessible for monitoring and real-time analysis for use by AI packages could dramatically alter the speed and quality of delivery of services and/or reaction.

Product development is challenging for both business people and engineers; one challenge is knowing which features to add and when to stop adding more features. Iterative development solves this problem. With short and repeated development cycles, the product grows. This Advisor seeks to demystify a common myth that surrounds Agile product development: the myth that only the most complete feature set will do. 

Here in Part XIII, the final Executive Update in Senior Consultant Curt Hall's series on artificial intelligence (AI) and machine learning in the enterprise, we focus on findings surrounding the hype around AI and the potential for the technology to lead to social and economic disruption.

Viewing an enterprise as an assembly of various architectures and building blocks allows the development of a coherent vision of how an organization can build the required capabilities to meet anticipated changes in its environment. Enterprise architecture, in particular, helps provide guidance and communicates how the company needs to change to survive. EA brings a shift in focus from technical systems to designing coherent sociotechnical systems that meet strategic requirements and organizational needs, such as those around workforce development, culture, structure, and processes. This Advisor introduces the Service Dominant Architecture (SDA) as a tool to support the digiti­zation of companies by structuring actors and their resources and reducing overall complexity.

For most organizations implementing customer experience (CX) management practices, it is still too early to tell if their efforts are actually paying off. This finding comes from the preliminary results of Cutter's ongoing CX management survey. This Advisor explores this finding and others and discusses why organizations are still waiting to realize measurable benefits from their initiatives.

Here in Part XII of this ongoing series on artificial intelligence (AI) in the enterprise, we examine findings pertaining to the use cases that organizations in our study viewed as most viable for applying AI.

Antifragile Systems Design requires an organization to move as one toward solving the problem of complexity, which means changing the perspective from “us versus them” (IT versus business) to simply “us” (business). The steps outlined in this Advisor require a mix of skills within business, business architecture, and software engineering. However, this is not simply a business activity or a software design activity and cannot be divided into different tasks for different silos; each step in the process creates feedback loops to ensure that answers arrived at are coherent. Business leaders, business/enterprise architects, and software architects all need to engage with the process to make it work. 

In Part VI of this Executive Update series, we take a look at “the procrastination metrics" of V5  and V8.