Thomas H. Davenport Quotes

to frame the decision, asking questions about the data and the methodology, working to understand the results, and using them to improve outcomes for your organization.

The moment a realm of intellectual activity is codifiable, it ceases to be uniquely human.

In an attempt to develop a tool to help organizations begin to identify these errors, the Institute for Healthcare Improvement (IHI) developed a global trigger tool (GTT).9 Briefly, the GTT provides a standard methodology for reviewing patient records for triggers, or indicators, of potential adverse events.

Defined simply, innovation is, of course, the introduction of something new. We presume that the purpose of introducing something new into a process is to bring about major, radical change. Process innovation combines a structure for doing work with an orientation to visible and dramatic results. It involves stepping back from a process to inquire into its overall business objective, and then effecting creative and radical change to realize order-of-magnitude improvements in the way that objective is accomplished.

The availability of all this data means that virtually every business or organizational activity can be viewed as a big data problem or initiative. Manufacturing, in which most machines already have one or more microprocessors, is increasingly a big-data environment. Consumer marketing, with myriad customer touchpoints and clickstreams, is already a big data problem. Google has even described its self-driving car as a big-data project.

Since Rosenthal came up with the recommendation idea, Morgan Stanley has been working on a next-best-action (NBA) system to provide its advisors with financial insights to present to clients.

James March, a Stanford-based social scientist... is much more a gurus’ guru than a guru to the general public. He finished second on the gurus’ gurus list and 48th on the original list.

We refer to these companies’ all-in approaches in multiple ways — “AI fueled,” “AI powered,” “AI enabled,” etc. The common thread is that they are at the far end of the scale in their spending, planning, strategizing, implementing, and changing with regard to AI technology.

That was one of the reasons why Memorial Sloan Kettering Cancer Center decided to work with Watson — to make widely available the level of knowledge of the hospital’s best oncologists to the world at large.

We believe that every large organization — and certainly those that are or aspire to be AI first — should designate smart people to follow AI technology trends, try out new technologies, and import them when they seem to fit the organization’s needs. These people don’t need to be fantastic data scientists or AI engineers, but they do need to understand the key technologies in AI and how they support use cases and business needs.

the use of statistical process control tools to evaluate variation, correlate root cause, forecast capacity, and anticipate throughput barriers. By measuring incidence of preventable venous

Attention is focused mental engagement on a particular item of business. Items come into our awareness, we attend to a particular item, and then we decide whether to act.

The businesses and organizations that succeed with AI will be those that invest steadily, rise above the hype, make a good match between their business problems and the capabilities of AI, and take the long view.

Knowledge workers have high degrees of expertise, education, or experience, and the primary purpose of their jobs involves the creation, distribution or application of knowledge.

In Europe, a consortium of microelectronics companies, the Euro Pact for Skills, is devoting €2 billion to train current and future employees on electronic components and systems.