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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Can a method like EVM, developed to control projects with well-defined objectives, be applied to control product development initiatives that evolve continuously toward a “moving target”? In an Agile environment, we are faced with the dynamic evolution of a finite boundary of integrated scope, cost, time, and resources; this finiteness — essential for business management and decisions — is the cradle for project management techniques, tools, methods, and frameworks. The EVM method was first developed to help with managing complex R&D projects mostly characterized by an unstable, volatile, and evolving scope. It is therefore no surprise that EVM applies to Agile projects.
Agile adoption often goes hand in hand with abandoning the so-called traditional methods of project management and software engineering. This comes from the idea that Agile approaches originated from a point of rupture with traditional methods and, hence, must not inherit any of their characteristics. However, most traditional methods, tools, and techniques were devised to address legitimate and universal management questions, which happen to be present in Agile initiatives as well and therein continue to require a project management answer. This Executive Report discusses how the earned value management method can be adapted to fit into an Agile product development process, and thereby deliver the required controls essential to achieve business value and stakeholder expectations.
In recent years, visual analytics (VA) has been introduced to represent massive multidimensional temporal data with various visual encodings. VA combines automated analysis techniques with interactive visualizations to enable effective understanding, reasoning, and decision making on the basis of very large and complex data sets.
In this article, the authors make detailed comparisons of the most notable robo-advisors in the US — namely, Betterment, Wealthfront, and Schwab Intelligent Portfolios. Although they are quite similar, they have their own features. Betterment uses smart financial models, such as a downside-risk optimization model, to make sure that each of its four primary investing goals (retirement, safety net, general investing, and major purchase) is based on a different stock allocation path. Wealthfront is more like a technology company, making sophisticated financial advice and investment strategies available to every individual investor at low cost by combining financial theory and machine learning. Schwab, as a traditional financial services firm, uses more traditional investment strategies in asset allocation.
Internationalization and localization are important steps in distributing and deploying systems to different regions of the world. Internationalization refers to the process of engineering a system such that it can support various languages and regions without further modification. Localization refers to the process of adapting an internationalized software system for a specific language or region.
Ontologies have been explored as alternatives to traditional relational databases for some time, particularly in sectors such as manufacturing and microbiology. Their application in finance could possibly be game-changing due to several key benefits of an ontological approach.
It’s a pleasure for me to introduce the first of two special issues of Cutter Business Technology Journal (CBTJ) showcasing the thought leadership and cutting-edge research and development (R&D) being done in State Street Corporation’s Advanced Technology Centres in Europe, the Middle East, and Africa (EMEA) and Asia Pacific (APAC), in partnership with University College Cork (UCC) and Zhejiang University (ZJU), respectively. The articles in this issue represent a small sample of the output from the R&D undertaken in these centers, which combine academic excellence with real industry impact.
Every business must deal with crisis, risk, and compliance challenges. Teams chartered with addressing these challenges are often split across business units and regions, which fragments crisis, risk, and compliance management efforts. Business unit silos and related complexities obscure ecosystem transparency, which in turn constrain an organization’s ability to identify risks, assure compliance, and prevent and disarm crises. Business architecture delivers business ecosystem transparency as a basis for improving a business’s ability to collectively address challenges related to crisis, risk, and compliance.