Abstract
We also know that since learning can be thought of as a flow, the application of our theory of constraints-based thinking implies that there will inevitably be bottlenecks that constrain the learning flow. More importantly, there will be constraints on the value of the learning throughput of the data-to-learning-to-action process. So, alleviating the constraints on the throughput of data-to-learning-to-action processes is clearly the prescription for improving business performance.
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Notes
- 1.
This is assuming a traditional for-profit organization. Other types of organizations may have fundamental objectives other than financial. And for-profit organizations may have other objectives in addition to financial objectives. The methods in this book can still apply for such non-financial objectives if there exist, or can be developed, quantified metrics that can be applied to measure the success in achieving the objectives. Those metrics simply replace monetary value as the proxy for the utility that is to be maximized by the associated learning and decisions.
- 2.
Baldoni, John. “Employee Engagement Does More than Boost Productivity”, July 04, 2013, https://hbr.org/2013/07/employee-engagement-does-more
- 3.
An important sentiment that pervades this book. Often attributed to the economist John Maynard Keynes, but apparently first articulated by the philosopher and logician Carveth Read: “It is better to be vaguely right than exactly wrong”. Carveth Read, Logic, Deductive and Inclusive (1898), p. 351.
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© 2018 Steven Flinn
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Flinn, S. (2018). Reversing the Flow: Decision-to-Data. In: Optimizing Data-to-Learning-to-Action. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3531-7_5
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DOI: https://doi.org/10.1007/978-1-4842-3531-7_5
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