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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Internet of Things (IoT) applications — including connected products and services in general, and remote condition-based monitoring and predictive maintenance in particular — offer considerable opportunities for companies to provide a better customer experience (CX) via real-time customer service and support.
Steven Kursh and Arthur Schnure identify six key arguments for why blockchain technology adoption is “blocked.” The authors investigate each identified rationale, showing its repercussions and proposing potential solutions to move forward. If blockchain technology is evolutionary, rather than revolutionary, as the authors assert, it is critical to understand what the current barriers are and how organizations, governments, and communities can address them. Once these barriers are overcome, more organizations will be eager to implement blockchain to demonstrate the business efficiency of the technology and to leverage its full potential.
This article focuses on how new regulations in the financial services industry and innovative technologies enhance customer experience (CX) by making services more efficient, faster, and less expensive. The authors describe new directives — such as the second Payment Services Directive (PSD2), applicable across the European Economic Area — that, together with new technologies such as blockchain, present a window of opportunity for financial services providers. The authors highlight how service providers, armed with information about target customers and with reduced risk of exposure to fraud, can better serve consumers. The authors also show how leveraging blockchain technology and the PSD2 directive can help deliver better CX and value proposition in the financial services industry.
Iweta Laskowska explains some of the myths around blockchain, such as anonymity, transparency, and privacy. She guides the reader to an understanding of what anonymity in peer-to-peer networks means and introduces the concept of “de-anonymization of transaction history,” which involves the identification of the real-world identities of contractors (senders and recipients), as well as the value that is sent. As Laskowska suggests, “The involvement of third parties in the management and authentication of transactions is expensive and time-consuming. Distributed public networks reduce the need for central authorities and eliminate the ‘single point of failure.’” This ultimately allows for greater participation in decision making.
This article explores the business benefits and technical challenges of blockchain technology implementation in the human resources (HR) domain, specifically in a recruitment space. Recruitment is one of the most critical parts of HR management, one in which there must be an establishment of trust at the beginning of interactions between parties. The authors posit that there is a need for a unified platform where certificates and academic degrees are safely kept in order to ensure the integrity of information and to have a means of verifying the validity of the qualifications, all while ensuring privacy. They propose the design and implementation of a platform exploiting two different open source platforms: Ethereum and Hyperledger Fabric. They then analyze each architecture’s basic features and compare those features to outline lessons learned.
Artificial intelligence (AI) strategy, at its core, must closely align with a company’s business objectives, ensuring synergy between the corporate strategy and the AI strategy.
Artificial intelligence (AI) and machine learning (ML) are technologies that can solve problems and do a world of good. But we must not forget that they are fallible and require human oversight. AI/ML developers must adhere to a strong code of ethics and employ ethicists to audit new applications. They must also ensure valid and reliable data testing and remain vigilant to the possibility that the technology may not work as intended.
Based on recent findings from a Cutter Consortium survey on customer experience (CX) management in the enterprise, most organizations appear to have somewhat guarded expectations of artifical intelligence’s potential to influence CX.