Strategic advice to leverage new technologies

Ciara Heavin and Daniel Power provide an overview of the design and development of modern BI and data-driven DSSs. They identify challenges and opportunities for managers and provide a sociotechnical view of DSSs by demonstrating practical guidelines for the people, process, and technology components of modern BI and data-driven DSSs.

Here in Part V of an Executive Update series on statistical project management, we explore a common metric used in economics and market analysis: the Herfindahl-Hirschman Index (HHI).

To meet increasingly elevated customer expectations, organizations are implementing detailed strategies for distributing customer experience (CX) practices across the organization. This includes defining and standardizing the “customer journey” across various channels in order to strengthen their brand, increase customer loyalty, reduce costs, make better use of customer feedback, and so on. Organizations are also investing in leading technologies designed to enhance CX, regardless of which channels customers choose to engage with them.

Businesses are implementing analytics and trying to use data to uncover new insights about their operations, customers, suppliers, employees, and so on. Even though the idea of using analytics is exciting, these types of projects are not for the faint-hearted — at least if you’re trying to implement analytics across the entire enterprise.

The need for business architecture in organizations has never been greater than it is today, as we must continually sense and respond to opportunity and change, both of which abound. Though the business architecture discipline continues to gain traction at an ever-increasing pace, how we practice it is critical for its adoption and effectiveness. This Executive Update provides an overview of the importance of using visual techniques as part of a business architecture practice and highlights three aspects: visual design, graphic recording and facilitation, and storytelling.

For decades, the commercial relationships between companies that provided software development services and their clients have been shaped by either fixed-price/fixed-scope or time-and-materials types of contracts. The drawbacks of both approaches have long been evident, but, nevertheless, both sides have learned to use them to protect their own interests. As we explore in this Advisor, an Agile ecosystem requires the creation of a systemic setup that works with the market, not just selected vendors.

Large, non-software companies introducing Agile to their organizations tend to suffer from a cognitive dissonance of sorts: we would like to have the same look and feel across the entire company, delivering stellar-quality products, yet we want to enable high-performing, self-organizing, self-managed, and self-empowered teams to deliver (or demo) at the end of each sprint. This Executive Update summarizes five key scenarios in which this cognitive dissonance becomes especially evident for large companies, particularly with non-software teams.

Identifying and developing new drugs and conducting clinical trials involve complex and lengthy (i.e., costly) processes that require researchers and drug manufacturers to integrate, manage, and analyze incredible amounts of data while at the same time collaborate with other medical research and pharma companies in their efforts. Pharmaceutical and biotechnology companies are using artificial intelligence (AI) to optimize the discovery and evaluation of new drug compounds, to explore patient and efficacy data, and to develop and bring new therapies to market.