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.
Recently Published
Data science skills span a wide gamut of capabilities within an organization, including business analysis, Lean-Agile portfolios, enterprise and systems architectures, quality assurance, and, of course, database and statistical skills. In this Executive Update, we address the issues around upskilling people for big data capabilities.
In this Executive Update, we describe the application of Scrum in the restaurant business. This environment is similar to that of Lean hardware Scrum, in that shifts are repeatedly creating and delivering products in short cycles with high quality. Process efficiency and cycle time become the key metrics for production.
In Part VII of this Executive Update series on statistical project management, we turn our attention to the dynamical and often irrational nature of projects.
Choosing a dissent strategy is difficult and the strategy chosen will vary from organization to organization. This Advisor helps software architects craft an effective dissent strategy.
This Advisor describes one way of establishing a non-blocking architecture governance practice for Agile development teams.
Effective decision support requires ongoing innovation and refinement. As decisions become more complex and as data increases in quantity and variety, systems must undergo refinement and enhancement. Consequently, decision support requires a continuous and iterative design and development process.
This Advisor looks at the top two benefits that organizations are interested in achieving with their customer experience efforts.
An understanding of the interplay of human users with automation, the underlying system actors (business applications, data, etc.), the business process, and the overall value chain is complex. What better way to keep human users at the center of automation design than the use of design thinking? Design thinking has already been established as the best way to create solutions for wicked problems that cannot be solved by reasoning alone. By adapting design thinking for smart automation, we can analyze the problem space better and incrementally improve on the solution, moving toward success while considering human factors. The design thinking process has five stages: empathize, define, ideate, prototype, and test. Let’s investigate how we can adapt it for smart automation initiatives.