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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The business value of blockchain technologies emerges in the form of business metrics, such as transaction efficiency, cost savings, and reduction of fraudulent activities, among others. In this Advisor, we explore some of the main drivers of value and potential applications beyond cryptocurrencies.
Historically, many projects concentrated their efforts on people, process, and technology. However, a vast amount of projects still fail to fully address the data and information aspects of their efforts. Many projects have failed due to this oversight, while others have left a wake of data quality issues that put long-term burdens on business processes and subsequent projects. It is useful to understand some of the common yet erroneous beliefs associated with projects. Believing such myths has caused many projects to fail because project teams did not account for the reality in their plans and budget. In this Advisor, we examine some of these myths and realities, along with their solutions.
When effective data governance and quality processes are paired with Agile methodologies, data definitions and quality measures can help produce clear and complete user stories.
Bill Fox explores why so many employees are disengaged in the workplace. Fox has been exploring this for several years, engaging business leaders on their thoughts on what employees lack and long for in their work environment. From his research, he defines several themes that may provide new, untapped avenues for greater employee happiness, engagement, and, ultimately, customer satisfaction and business results.
The process of continuous siloization found in many organizations, and in almost all organizations above a certain size, means that the data that employees need to do their work is distributed over a large number of nonintegrated IT systems within different intracompany jurisdictions. We’ve come to the realization that the solution could be to put data modeling front and center. It just has to be done a bit differently than it has been done in the past.
This month’s CBTJ addresses the following question: what can companies do to increase employee engagement in order to increase customer satisfaction and, ultimately, business results?
Instead of moving from technology to key customers with an abstracted total addressable market (TAM), we must instead quantify artificial intelligence (AI) and machine learning (ML) benefits where they specifically fit within business strategies across segment industries. By using axiomatic impacts, the fuzziness of how to incorporate AI, ML, and big data into an industry can be used as a check on traditional investment assumptions.
In light of the current, unprecedented global crisis, it’s crucial now more than ever to reevaluate your risk management process and ensure you are well prepared for what may lie ahead. Today’s executives must adapt their leadership and face the current crisis head-on with a proactive approach to risk management.