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The Value of Value Chain Analysis in Transforming Your Business

N2Growth Blog

For example, determining skill gaps and training staff could be core activities here; Perform – which contains a collection of core work activities that support the key mission of the department.

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7 Steps to Problem Solving

Skip Prichard

Complex problem solving is the core skill for 21st century teams. Their new book is BULLETPROOF PROBLEM SOLVING: The One Skill That Changes Everything. New Skills Required. Would you share a little about the evolution of managerial skills and what skills are needed in the current era? Bulletproof Problem Solving.

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10 Ways to be a Better Team Player :: Women on Business

Women on Business

Categories : Communications , Ethics , Leadership , decision-making Echo Garrett is the National Practice Manager for KPMGs Financial Credit Risk practice and a Co-Founder of "Her Voice", a National Womens Organization that brings women together for local support and charitable opportunities. Now what to do?

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How P&G and American Express Are Approaching AI

Harvard Business Review

And they have well-honed approaches for developing the requisite new skills in employees. Ash Gupta is President of Global Credit Risk and Information Management at American Express, and Guy Peri is Chief Data Officer and Vice President of Information Technology at P&G. Do most of the work yourself.

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A Dedicated Team of Problem Solvers Can Help Big Companies Act Like Lean Startups

Harvard Business Review

We have a lot of newer businesses that come to us for credit and we need to do due diligence on them. So it’s an incredibly labor intensive process for us to verify whether they are a good credit risk.” ” Haller’s team was able to put together a prototype and present it to the client within 90 days.

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What Every Manager Should Know About Machine Learning

Harvard Business Review

Rating the credit risk of loan applicants. With the right mix of technical skill and human judgment, machine learning can be a useful new tool for decision-makers trying to make sense of the inherent problems of wide data. Forecasting long-term customer loyalty. Anticipating the future performance of employees.

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