Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
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In statistical project management (SPM), we simplify the project management approach by eliminating many concepts that the dominant project management methodologies consider central. While I caution you to err to the side of adopting a lighter methodology rather than a thicker one, that choice is a local one and yours to make. The SPM ontology provides you with options. Here in Part IV, we examine how projects grow.
Information gathering and recording are plagued by fragmentation, context switching, and volatility. These problems seem to be inherent to working with data and constitute the data beast. The contradiction between, on the one hand, the search for consensus and, on the other, the fragmentation, context switching, and volatility of information that dilute this effort is a never-ending rodeo ride. The reasons behind fragmentation, context switching, and volatility are misunderstood. This triple plague is often seen as either an imperfection that requires fixing or a roadblock to digitization.
Decision automation means that software — not people — makes decisions. The concept of decision automation is both deceptively simple and intriguingly complex. On the surface, the idea is to write a computer program that uses data, rules, and criteria to make decisions. Decision automation is programmed decision making. A decision automation system replaces and eliminates the need for a human decision maker in a specific decision situation. Through such a system, inputs and events trigger business rules and programmed instructions and then the program “makes” a choice and initiates action. The greatly expanded and evolving computing infrastructure makes it increasingly cost-effective to apply decision automation in situations that previously had been prohibitively costly. Increasingly, decision automation deploys as a distributed, cloud-based application that uses integrated networks and sensors to make decisions in a specific domain.
Connecting a platform with an existing company to a platform organization is beneficial for both established companies and insurtechs. Without pursuing that avenue, the insurtechs face the risk that their competitiveness may decline if others can copy their digital skills at low cost. Thus, connecting their platforms with the incumbent organizations that possess hard-to-copy capabilities guarantees the uniqueness and sustainability of their own business model. The disadvantages of established companies, in comparison to insurtechs, are the reason why traditional companies need platforms. Platforms require changing the culture and business logic in a company from product to service dominance, making processes in relevant areas real-time capable, opening the company to the reuse and integration of solutions and services from other actors, and replacing a hierarchical culture with modern, agile, team-oriented approaches that make optimal use of the internal and external workforce.
Here in Part II of this Executive Report series on the rise of cognitive computing, we dive into the commercial cognitive products, including cognitive development platforms, domain- and industry-specific cognitive platforms, and cognitive-powered solutions
Here in Part II of this Executive Report series on the rise of cognitive computing, we dive into the commercial cognitive products, including cognitive development platforms, domain- and industry-specific cognitive platforms, and cognitive-powered solutions
Enterprise solutions providers now offer cloud-based platforms and services to help organizations with their customer experience (CX) management efforts. These platforms can support various CX scenarios, including omni-channel customer engagement, customer behavioral analysis, personalization, social video and messaging (for engaging with customers on social media platforms), customer loyalty, customer satisfaction assessment and measurement, customer intent/journey analysis and visualization, and visual search, among others. In our ongoing survey covering the adoption of CX practices and technologies, we ask organizations about their plans for using cloud CX platforms and services.
Many technologies exist today that have the potential to change the manner in which we get work done. Currently, the software developer job is heavily labor-intensive. Yes, we use software tools to perform many of the repetitive tasks; however, for the most part, the programming job is performed by highly talented individuals who specify, design, code, and test complex pieces of code and make them work. We have attempted to automate such tasks, but we can best characterize current efforts as assistance (helping workers by providing guidance and information) rather than automation (replacing humans with machines). In this Advisor, we identify 20 technologies that have the potential to alter this picture in both the near and long term. Some present opportunities, while others will disrupt our environments. And some will fall on both sides of that equation.