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.

In definitional terms, a process is simply a structured, measured set of activities designed to produce a specific output for a particular customer or market. It implies a strong emphasis on how work is done within an organization, in contrast to a product focus’s emphasis on what. A process is thus a specific ordering of work activities across time and space, with a beginning and an end, and clearly defined inputs and outputs: a structure for action.

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.

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.

It takes about twelve years for a pharmaceutical firm to research, develop, test, and launch a product. Several firms, including Pfizer, Novartis, and Celgene, are working with IBM Watson to try to identify and bring new drugs to market faster.

Companies should have well-defined procedures for dealing with the planned departure of a valued knowledge worker... Unfortunately, the evidence suggests that most firms are moving in the wrong direction on recruitment and retention issues.

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.

One large US bank, for example — an aggressive adopter of AI — has announced a $350 million investment in reskilling related to AI-related job changes, and the bank is being both predictive and granular about the initiative.10 It’s working with researchers from MIT and elsewhere to understand — based on a “suitability for machine learning” (SML) assessment — which skills and jobs are most likely to be replaced by AI.11 The SML analysis will help the bank plan for changes in those jobs and help workers gain the skills they need to succeed in their modified jobs or transition to new ones.

Another AI-oriented company that has established several ecosystems — also in partnership with Palantir, in which it has made a substantial investment — is SOMPO Holdings, a large insurance and elder care company based in Japan. SOMPO

Every decade or so, the business world invents another term for how it extracts managerial and decision-making value from computerized data. In the 1970s the favored term was “decision support systems,” accurately reflecting the importance of a decision-centered approach to data analysis. In the early 80s, “executive information systems” was the preferred nomenclature, which addressed the use of these systems by senior managers. Later in that decade, emphasis shifted to the more technical-sounding “online analytical processing,” or OLAP. The 90s saw the rise of “business intelligence” as a descriptor. In the middle of 2000’s first decade, “analytics” began to come into favor, at least for the more statistical and mathematical forms of data analysis.

Ultimately, knowledge worker performance comes down to the behaviors of individual knowledge workers.

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.

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