book

Evidence-Based Management

Name: Evidence-Based Management
ISBN: 9780749483753

by Eric Barends, Denise M. Rousseau

September 2018

Intermediate to advanced

392 pages

10h 16m

English

Kogan Page

Read now

Unlock full access

Cover
Title Page
Copyright
dedication
Contents
List of Figures
List of Tables
About the authors
Contributors
Foreword

Preface
How to read (and use) this book
Acknowledgements
01 Evidence-based management: the basic principles (with Rob Briner)
1.1 What is evidence-based management?
1.2 What counts as evidence?
1.3 Why do we need evidence-based management?
1.4 What sources of evidence should be considered?
1.5 Why do we have to critically appraise evidence?
1.6 Why focus on the ‘best available’ evidence?1.7 Some common misconceptions of evidence-based management1.8 What is the evidence for evidence-based management?
02 ASK: Critical questions about assumed problems and preferred solutions
2.1 Identifying underlying assumptions
2.2 Starting point: What is the problem to solve or opportunity to address?
2.3 PICOC
2.4 Step 1: What is the assumed problem to be solved?
2.5 Step 2: What is the evidence for the problem?
2.6 Step 3: What is the preferred solution?
2.7 Step 4: What is the evidence for the preferred solution?
2.8 Developing your capacity to ask questions
2.9 Checklists
PART ONE Evidence from practitioners
03 ACQUIRE: Evidence from practitioners
3.1 What to ask?3.2 Whom to ask?3.3 How many practitioners should I ask?
3.4 How to ask?
3.5 Developing questions3.6 Eight tips for asking valid and effective questions
04 APPRAISE: Evidence from practitioners
4.1 How to tell whether a practitioner has professional expertise4.2 Why is it so hard to develop valid and reliable professional expertise?4.3 Two modes of thinking
4.4 Cognitive biases
4.5 Avoiding or reducing bias
4.6 Critical appraisal of evidence from practitioners
4.7 Checklist
PART TWO Evidence from the scientific literature
05 A short introduction to science (with Rob Briner)
5.1 What is science?
5.2 Science is not about ‘truth’ or ‘proof’
5.3 Limitation 1: Coincidence
5.4 Limitation 2: Methodological bias
5.5 Limitation 3: Confounders
5.6 Limitation 4: The placebo effect
5.7 Limitation 5: Moderators and mediators
5.8 Qualitative versus quantitative research
5.9 Research designs5.10 How to read a research article
06 ACQUIRE: Evidence from the scientific literature
6.1 The scientific literature
6.2 Determining your search terms
6.3 Searching in research databases: Some basic search techniques
6.4 Pre-testing your search terms
6.5 Searching for empirical studies: Systematic, transparent and reproducible
6.6 Finally, some tips
07 APPRAISE: Evidence from the scientific literature (with Rob Briner)
7.1 Critical appraisal: Three preliminary questions
7.2 Critical appraisal: Methodological appropriateness
7.3 Methodological appropriateness: Cause-and-effect studies
7.4 Methodological appropriateness: Non-effect studies
7.5 Critical appraisal: Methodological quality
7.6 Finally: The ‘best available’ evidence
7.7 Overview of the appraisal process
7.8 Checklists
PART THREE Evidence from the organization
08 ACQUIRE: Evidence from the organization (with Martin Walker)
8.1 Why is evidence from the organization important?8.2 From data to information and evidence8.3 What questions to ask?
8.4 What types of organizational evidence are typically available?
8.5 Big data8.6 Where to find organizational evidence8.7 Techniques and tools for acquiring data8.8 Organizational data turned into information
8.9 Other considerations when acquiring data
09 APPRAISE: Evidence from the organization (with Martin Walker)
9.1 Barrier 1: Absence of a logic model
9.2 Barrier 2: Irrelevant data
9.3 Barrier 3: Inaccurate data
9.4 Barrier 4: Missing contextual information
9.5 Barrier 5: Measurement error
9.6 Barrier 6: The small number problem
9.7 Barrier 7: Confusing percentages and averages
9.8 Barrier 8: Misleading graphs
9.9 Barrier 9: Correlations and regressions – overfitting the data
9.10 Barrier 10: Wide confidence intervals
9.11 Artificial intelligence, machine learning and artificial neural networks
9.12 Organizational evidence: Quality versus purpose9.13 Checklist
PART FOUR Evidence from stakeholders
10 ACQUIRE: Evidence from stakeholders
10.1 Not all evidence from stakeholders is stakeholder evidence10.2 Types of stakeholders
10.3 Who are the most relevant stakeholders?
10.4 Whom to ask?
10.5 What to ask?10.6 How to ask?
11 APPRAISE: Evidence from stakeholders
11.1 The importance of subjective feelings and perceptions11.2 What is the impact of the decision?
11.3 Representativeness
11.4 How representative is my sample?11.5 Checklist
12 AGGREGATE: Weighing and pulling together the evidence
12.1 Evidence-based management is about probabilities
12.2 Bayes’ Rule
12.3 The prior probability12.4 The likelihood of the evidence
12.5 Updating the posterior probability when new evidence becomes available
12.6 Using Bayes’ Rule to aggregate evidence from different sources
12.7 Bayesian thinking
13 APPLY: Incorporating the evidence into the decision-making process (with Alessandra Capezio)
13.1 Does the evidence apply?13.2 What is the expected value?
13.3 Is it the biggest bang for your buck?
13.4 Is the level of risk acceptable?
13.5 Are there ethical issues to consider?
13.6 Is the evidence actionable?
13.7 Are there moderators that you need to take into account?
13.8 How and in what form can you apply the evidence?
13.9 Dissemination, implementation and change
14 ASSESS: Evaluate the outcome of the decision taken
14.1 Types of decisions14.2 Assessing the outcome: Two preliminary questions
14.3 Assess: The gold standard
14.4 Assess: The silver standard
14.5 Outcome measures
14.6 Assessing stakeholder effects14.7 Keep it simple!
15 Building the capacity for evidence-based management
15.1 Becoming an evidence-based manager15.2 Building evidence-based capacity among bosses and peers15.3 Building evidence-based capacity in your organization
15.4 Some final words
16 Guidelines for critically appraised topics
16.1 Step 1: Background – What is the context of the CAT question?
16.2 Step 2: Formulating the CAT question – What does the CAT answer?
16.3 Step 3: PICOC
16.4 Step 4: Inclusion criteria – Which studies will be considered?
16.5 Step 5: Search strategy – How should the studies be sought?
16.6 Step 6: Study selection – How should you select the studies?
16.7 Step 7: Data extraction – What information should you extract
16.8 Step 8: Critical appraisal – How should the quality of the studies be judged?
16.9 Step 9: Results – What did you find?
16.10 Step 10: Conclusion
16.11 Step 11: Limitations
16.12 Step 12: Implications and recommendations
16.13 Checklist
Glossary
Index
Backcover

Content preview from Evidence-Based Management

Figure 9.5

Cumulative versus interval data

Instead of plotting data for separate time intervals, sometimes cumulative data are presented. For example, the number of sales can be visualized for each month, quarter or year separately, but it is also possible to present them as cumulative sales per month, quarter or year – that is, total sales to date. When the cumulative sales are presented in a graph, each single sale makes the graph’s line go up. This is particularly convenient when the total number of sales is decreasing. This is exactly what Apple’s CEO Tim Cook did during a presentation on iPhone sales in 2013.¹¹ In Figure 9.6 you can ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

Read now

Unlock full access

More than 5,000 organizations count on O’Reilly

O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.

Julian F.

Head of Cybersecurity

I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.

Addison B.

Field Engineer

I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.

Amir M.

Data Platform Tech Lead

I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.

Mark W.

Embedded Software Engineer

Publisher Resources

ISBN: 9780749483753

Cloud Computing

Data Engineering

Data Science

AI & ML

Programming Languages

Software Architecture

IT/Ops

Security

Design

Business

Soft Skills

Evidence-Based Management

by Eric Barends, Denise M. Rousseau

Cumulative versus interval data

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.