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by Mark Van Buren, Jean Martin, John Mattox
Publisher: Kogan Page
Release Date: September 2016
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Table of contents
Drawing on the latest research, this practical guide shows how to utilize organizational data to make better decisions about managing the learning and development of your workforce.
Table of Contents
Praise for <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" class="normal">Learning Analytics</span>
01 Why now? The occasion for learning analytics
Changing the way talent analytics work gets done
Providing unique insight into employee behaviour
The learning analytics opportunity
02 What is learning analytics?
Learning analytics today: measure for measure, what should be measured?
Why measure learning?
Most organizations start with the simple: measure training adoption and satisfaction
Efficiency, effectiveness and business outcomes: closing the learning measurement gap
The journey to learning analytics
The Four Levels of Evaluation
The Return on Investment training methodology
Impact Measurement Framework
Success Case Method
03 Technology’s role in learning measurement
What should technology do?
Benefits and costs of learning technologies
What are the requirements for any new technology system in the business intelligence space?
What is the ROI of technology systems?
Applying principles of business intelligence systems to learning and development
04 Linking learning to business impact
Why does it work?
Alternatives to experimental designs
The end of the null hypothesis – almost
05 Scrap learning: the new leading indicator of success
Your training programmes are not as good as you think they are
Running L&D like a business
Reporting on scrap learning
How can scrap be reduced?
Scrap and manager engagement
06 Aligning L&D to business goals through needs assessment
Measure twice, cut once
How is alignment achieved?
The ADDIE model: linear vs cyclical business alignment
Unpacking the ‘Analyse’ stage of business alignment
How can evaluation results inform the Analyse phase?
What about tests?
Using competency assessments to find skill gaps
A journey of a thousand miles begins with one step
Benchmarking improves maturity
Why are benchmarks valuable in the L&D space?
What benchmarks are available?
Benchmarks and statistical significance
What does MTM bring to the market beyond benchmarks?
How do clients use benchmarks to support decision making?
08 Optimizing investments in learning
Learning and development groups struggle to create value
Developing a framework
Reporting measures to the business
Working with business leaders
Continuous improvement and management approaches
Less is more
09 Beyond learning analytics to talent management analytics
The future is for those who can predict it
Defining what to measure in talent management
Understanding the employee lifecycle
Research on talent analytics
It’s not the analytics that matter; it’s how they are applied
Managing data in the analytics process
Improving analytic impact
How companies are addressing the challenge of talent analytics impact
Analytics across the talent lifecycle