Big Data Recruitment

HOW AGENCIES SHOULD EMBRACE DATA TO IMPROVE SERVICE AND GAIN COMPETITIVE ADVANTAGE

Let’s start with a question. Which Internet browser do you use? Perhaps you are using one right now to read this. Or perhaps you used one in order to download the eBook before reading it remotely. As a PC user do you stick with Microsoft Internet Explorer? As a Mac user is it Apple’s Safari all the way? Perhaps you haven’t given it a second thought. Or maybe the rst thing you do when you get a new computer is to throw out the default option and download Google Chrome or Mozilla Firefox instead.

Think carefully before answering because your response may say something profound about you.

Bernard Marr is a Big Data consultant and author of Big Data: Using Smart Big Data Analytics and Metrics to Make Better Decisions and Improve Performance [1]. Asked by a client to help identify self-driven recruits – the initiative takers – Marr looked at a range of datasets that might help. He alighted at the choice of browser candidates had used to complete the job application. With a little more analysis he concluded that, indeed, this was a strong predictor of the right stuff – someone unwilling to settle for the status quo, someone with the con dence to go his or her own way.

This, in case you hadn’t guessed, is Big Data in action, an example of measuring and analysing large amounts of information from a variety of sources – often at speed – and drawing actionable conclusions from what it shows. For the proponents of Big Data, this story exempli es one of its real strengths – discovery. Opponents hint at hype, suggesting that at best, Big Data is little more than business intelligence redux.

In the course of this eBook, we will explain how Big Data works and examine the potential bene ts for those of you in the recruitment industry. We’ll share examples of good practice, case studies from your industry and from elsewhere. We’ll discuss the practicalities – from identifying the skills needed to discussing privacy and compliance – and conclude with a detailed checklist for those embarking on a Big Data, or a smaller data analytics, project.

So why Big Data? Because if you can capture it, you can measure it. If you can measure it, you can analyse it. And if you can analyse it, you can draw lessons and insights from it – lessons and insights that could have a material impact on the bottom line, even change the way you look at your business.

In their recent book, From Big Data: A Revolution That Will Transform How We Live, Work and Think [2], Viktor Mayer-Schonberger and Kenneth Cukier describe Big Data as “the oil of the information economy”. They go on to write: “Though data is rarely recorded on corporate balance sheets, this is probably just a question of time.”

Data will only appear on your balance sheet if you start taking it seriously. It’s time to get started.

Table of Contents

INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . .1

1. BIG DATA. BIG PICTURE. . . . . . . . . . . . . . . . . . .2

1.1 The Role of Technology . . . . . . . . . . . . . . . . . . . . . . . . . .3

1.2 So What Is Big Data?. . . . . . . . . . . . . . . . . . . . . . . . . . . .4

1.3 Why Big Data? And Why Now? . . . . . . . . . . . . . . . . . . . .6

2. BIG DATA IN ACTION. . . . . . . . . . . . . . . . . . . . .8

2.1 The Logistics Company . . . . . . . . . . . . . . . . . . . . . . . . . .9

2.2 The Tractor Company. . . . . . . . . . . . . . . . . . . . . . . . . . . .9

2.3 The Digital Retailer . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

2.4 The Scientists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

2.5 The Advertising Company . . . . . . . . . . . . . . . . . . . . . . .10

2.6 TheOneThatWentWrong ………………….10

3. APPLYING BIG DATA TO RECRUITMENT . . . . .11

3.1 Seven Ways Recruitment Agencies Should Use Data. . .12

4. DEPLOYING BIG DATA. . . . . . . . . . . . . . . . . . .15

4.1 Calculating Return on Investment (ROI) . . . . . . . . . . . .16

4.2 Who is Your Chief Digital Of cer? . . . . . . . . . . . . . . . . .16

4.3 Privacy, Compliance and Moral Dilemmas . . . . . . . . . .17

5. THE BIG DATA RECRUITMENT CHECKLIST . . .19

CONCLUSION ………………………22

Appendix I: Glossary of terms . . . . . . . . . . . . . . .23

Appendix II: Introducing etzInsights. . . . . . . . . . . .24

Appendix III: Sources . . . . . . . . . . . . . . . . . . . . . .25

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