HR Analytics and Big Data @ Work
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HR Analytics and Big Data @ Work
Articles, research and reports on HR Analytics, Big Data and related topics
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Teacher Moneyball: Can big data and predictive analytics help find the next generation of star educators?

Teacher Moneyball: Can big data and predictive analytics help find the next generation of star educators? | HR Analytics and Big Data @ Work | Scoop.it
Drawing lessons from sports, Moneyball, and predicative analytics, Jacob Murray asks whether we can isolate the key traits of effective teachers and then assess the prevalence of these traits in prospective teachers to forecast who the next star educators will be.
Tony Brugman (Bright & Company)'s insight:
Interesting question: can predictive analytics help education to find the next best talent in teaching?

The author of this Brookings blog argues that we already know the qualities and characteristics of effective teachers, among them positive disposition, high standards /expectations, organization and clarity, and self-critical / reflective /problem-solvers. Why not use the principles of 'Moneyball' to scout the next star educators?
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The Rise of Data-Driven Decision Making Is Real but Uneven

The Rise of Data-Driven Decision Making Is Real but Uneven | HR Analytics and Big Data @ Work | Scoop.it
Growing opportunities to collect and leverage digital information have led many managers to change how they make decisions – relying less on intuition and more on data. As Jim Barksdale, the former CEO of Netscape quipped, “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.”
Tony Brugman (Bright & Company)'s insight:

Research by MIT and London School of Economics, studying the rise of 'data-driven decision making' (DDD) in US manufacturing. The researchers found that usage rose from 11% to 30% between 2005 and 2010.

 

"However, adoption has been uneven. DDD is primarily concentrated in plants with four key advantages: 1) high levels of information technology, 2) educated workers, 3) greater size, and 4) better awareness."

 

"No doubt the hype surrounding big data and analytics is great. However, (..) there is something beyond the hype: firms are rapidly adopting DDD and fundamentally changing how they approach management in the digital age."

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A Combined Text Analytics – The Best HR Analytics Articles of 2014 &15

A Combined Text Analytics – The Best HR Analytics Articles of 2014 &15 | HR Analytics and Big Data @ Work | Scoop.it
As a renowned practitioner in the global HR analytics space, his endorsements imply that the consolidated intent of these posts ( via deep text analytics ) could be of prime interest to the global HR fraternity
Tony Brugman (Bright & Company)'s insight:

What would you get if you would perform text analytics onto the best HR Analytics articles of the past two years (2014-2015)? The result is this intruiging Linkedin article by Raja Sengupta (data scientist at Quantta Analytics).

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What to Do Before You Fire a Pivotal Employee - HBR

What to Do Before You Fire a Pivotal Employee - HBR | HR Analytics and Big Data @ Work | Scoop.it
Map the impact on your company’s network.
Tony Brugman (Bright & Company)'s insight:

Very interesting article by Belgian HR and Analytics researchers Bart Baesens, Luc Sels and Sophie De Winne, combining social network analysis and analytics.

 

For example to assess the impact of firing a certain employee. "(It) could reveal new serendipitous insights into the relationship between employee and customer drain, which would allow a company to create an unprecedented competitive advantage."

 

In the HBR article they briefly describe

1. how to model an employee/social network through analysis

2. how to further mapping out the employee network

3. how to analyse the employee network using descriptive metrics

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How to Fail at HR Analytics in 7 Easy Steps

How to Fail at HR Analytics in 7 Easy Steps | HR Analytics and Big Data @ Work | Scoop.it
A ‘leading loser’ shares what he learned the hard way—so you won’t have to.
Tony Brugman (Bright & Company)'s insight:

Nice insights by Mark Berry (experienced HR analytics practitioner). He spoke to SHRM HR Magazine about his lessons learned on HR Analytics.

 

He mentions his pitfalls as seven key actions as a "recipe for failure":


1. Position your program as strategic even if you’ve done nothing that qualifies it as such
2. Focus on the solution before defining the problem
3. Invest most of your resources in technology rather than partnering with the right vendor
4. Hire experts before they demonstrate any expertise
5. Accept a role and reporting relationship that compromises your impact and integrity
6. Delude yourself into believing that others value what you are doing as much as you do
7. Believe your own press

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For Entrepreneur360 'Data Champions,' Success Is Steady, Plotted and Planned

For Entrepreneur360 'Data Champions,' Success Is Steady, Plotted and Planned | HR Analytics and Big Data @ Work | Scoop.it
These companies push forward with proven strategies to drive results.
Tony Brugman (Bright & Company)'s insight:

What does set the best data-driven entrepreneurial companies apart from its less performing peers? According to thorough analysis by Entrepreneur Magazine the characteristics of these 'Data Champions' are:

 

>> They often emphasize a reliance on performance data, sharing it across the company to help employees at all levels make decisions.


>> They are much more likely than their peers to offer employees higher pay and a share of profit.

 

>> They pay close attention to planning and managing growth, looking to build a sustainable functioning business.

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It’s Embarrassing: Every Business Function Measures Quality, Except Recruiting

It’s Embarrassing: Every Business Function Measures Quality, Except Recruiting | HR Analytics and Big Data @ Work | Scoop.it
Recruiting Is Literally the Last Function to Measure It’s Output Quality Quality is such an easy-to-understand thing. It is an improvement in performance a

Via Andrée Laforge
Tony Brugman (Bright & Company)'s insight:

Whoops! (Great analysis as always by ERE's John Sullivan!)

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Andrée Laforge's curator insight, July 28, 2015 8:00 AM

Super article de John Sullivan sur la qualité de l'embauche!

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When Health Care Gets a Healthy Dose of Data | MIT Sloan Management Review

When Health Care Gets a Healthy Dose of Data | MIT Sloan Management Review | HR Analytics and Big Data @ Work | Scoop.it
American health care is undergoing a data-driven transformation — and Utah’s Intermountain Healthcare is leading the way.
Tony Brugman (Bright & Company)'s insight:

Extensive MIT Sloan Management Review case study article of a major healthcare organisation that worked on building a data and analytics culture throughout the organisation. Not without results: "Data-driven decision making has improved patient outcomes in (its') cardiovascular medicine, endocrinology, surgery, obstetrics and care processes — while saving millions of dollars in procurement and in its the supply chain."

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Tech Insights: The Importance of Data Scientists in HR Technology

Tech Insights: The Importance of Data Scientists in HR Technology | HR Analytics and Big Data @ Work | Scoop.it
Data scientists are becoming important in HR technology. I had thought the big thing about SimplyHired was that they were good at scouring the web for job openings and putting them in one …

Via Andrée Laforge
Tony Brugman (Bright & Company)'s insight:

Interesting point-of-view on the role of data scientists in HR Technology.  The claim: Hiring good data scientists is just as important as having programmers.


Why: 1) HR Technology vendors are getting far ahead of HR to understand what they are doing, 2) Big decisions often need deep insight into the data

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Andrée Laforge's curator insight, May 19, 2015 3:44 PM

On a tous besoin d'un bon data scientist en RH...

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The Talent Dividend | MIT Sloan Management Review

The Talent Dividend | MIT Sloan Management Review | HR Analytics and Big Data @ Work | Scoop.it

The 2015 Data & Analytics Report by MIT Sloan Management Review and SAS finds that talent management is critical to realizing analytics benefits.


Via David Green
Tony Brugman (Bright & Company)'s insight:

Updated report by MIT SMR and SAS focuses on the recruitment and management of analytics talent, because talent management matters when it comes to analytics: "The study finds that organizations achieving the greatest benefits from analytics are also much more likely to have a plan for building their talent bench."


Another interesting finding from the study is that despite the increase in data, it does not lead to more insights per se. "Access to useful data has steadily risen, but companies are less effective at applying insights to strategy."

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What we learned about HR Analytics in 2014 - Part 2

What we learned about HR Analytics in 2014 - Part 2 | HR Analytics and Big Data @ Work | Scoop.it
Read about the most important HR Analytics lessons from 2014, collected by Luk Smeyers from iNostix, one of Europe's most sought after HR Analytics Experts.
Tony Brugman (Bright & Company)'s insight:

Excellent read! Part 2 of Lessons Learned by HR Analytics experts iNostix (Read Part 1 here: http://www.inostix.com/blog/en/14-hr-analytics-lessons-2014-part-1/)

 

Their lessons from 2014 include:

- Forget ‘big data’ at the start

- You can start tomorrow!

- Make HR analytics into a continuous process (instead of loose projects)

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People data everywhere: Bringing the outside in

People data everywhere: Bringing the outside in | HR Analytics and Big Data @ Work | Scoop.it
The time has arrived for HR to leverage the valuable insights people data can yield—from both internal and external sources.
Tony Brugman (Bright & Company)'s insight:
Interesting new section in the Deloitte Global Human Capital Trends 2015 report on the use of People Data from both inside and outside your organisation. The highlights are:
1. HR and talent organizations are expanding their HR data strategies by harnessing and integrating external data from social media platforms and other external sources.
2. This trend is accelerating as more employee data appears online. Thirty-nine percent of surveyed companies are now leveraging social data to support efforts around recruiting, engagement, and understanding employment brand.
3. While analytics programs based on internal data can be tremendously valuable, the most powerful solutions will leverage external as well as internal data to inform critical talent decisions.
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How Analytics is Changing People Management

How Analytics is Changing People Management | HR Analytics and Big Data @ Work | Scoop.it
Google has regularly been voted the best company in America to work for – its staff get free meals, generous paid holidays, access to “nap pods” for power-napping during the business day, and are even encouraged to grow their own fruit and vegetables at work.And, despite their old “don’t be evil” motto, Google top brass hasn’t set things up this way simply because they are lovely people. Like everything they do, their decisions were based squarely on data – and in this case the data showed that

Via David Green
Tony Brugman (Bright & Company)'s insight:

Good Linkedin blog (from February) by Analytics expert Bernard Marr on the rise and dangers of 'people analytics'. Despite the fact that it is not that difficult to implement and perform, Marr has serious concerns about the possible outcomes.

 

Marr sums it up like this:

"(..) In the age of Big Data analysis, measuring the efficiency of staff, and identifying the factors that may be affecting it, is a relatively simple process. (..) However if implemented in a sloppy or discriminatory fashion, (it) could also lead to serious problems with staff trust, and the level of intrusion into their private lives that they feel."

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The data deluge: Five years on

In a new slideshow, explore how data in business and and society has progressed since 2010.
Tony Brugman (Bright & Company)'s insight:
Nice summary overview five years after The Economist published its article 'The Data Deluge' written by data specialist Kenneth Cukier. This slidedeck shows how the story continued since in 2010.

Hint: Mo(o)re and Mo(o)re!
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What Work Email Can Reveal About Performance and Potential

What Work Email Can Reveal About Performance and Potential | HR Analytics and Big Data @ Work | Scoop.it
People who send more messages are often higher performers.
Tony Brugman (Bright & Company)'s insight:

Interesting HBR article on using digital data (for instance from e-mail) can be used to predicting the performance of individuals. With these data, organisations can uncover patterns and insights from these data about employee networks and performance.

 

The author argues that strong networks/connections can predict employee performance and large employee networks can predict (high) potential.

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Compensation still to embrace People Analytics: a matter of skills or behaviors?

Compensation still to embrace People Analytics: a matter of skills or behaviors? | HR Analytics and Big Data @ Work | Scoop.it
A winning employee value proposition cannot be solely centered on the competitiveness of pay. Gauging the overall competitiveness of rewards requires to assess a number of factors related to career,
Tony Brugman (Bright & Company)'s insight:

Good and critical article on using (HR) analytics in the field of compensation. The author argues that compensation can benefit from analytics in at least four ways:


1. Identify the “right” compensation program mix

2. Improve talent attraction and retention

3. Create a clear line-of-sight to influence behaviors

4. Improve performance assessments


Yet, to become more successful he presses that "a fundamental behavioral change is requested"! Requiring a new attitude, which is "more than quantitative skills, (starting with) asking the right question!"

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Critical Evaluation: Put Your Analytics into Action (by Jeanne Harris) - SHRM

Critical Evaluation: Put Your Analytics into Action (by Jeanne Harris) - SHRM | HR Analytics and Big Data @ Work | Scoop.it
Jeanne G. Harris, author and HR thought leader, on how to go beyond quick fixes to building real analytic capability.
Tony Brugman (Bright & Company)'s insight:

Nice tips from Jeanne Harris (co-author of analytics must-reads 'Analytics at Work' and 'Competing on Analytics') on getting more out of your HR analytics this year.

 

"Here’s what HR should do in 2016 to help their organizations get real value from HR analytics:"
1. Develop your company’s analytical literacy
2. Use diverse teams to solve major talent challenges
3. Focus on big results, not analysis

 

"Buying a new software solution is easy, but it is time for HR to forget about quick fixes. Only by building a real analytic capability can HR professionals become the proactive, data-driven critical thinkers and business leaders that their organizations need." - Agree!

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How Machines Learn (And You Win)

How Machines Learn (And You Win) | HR Analytics and Big Data @ Work | Scoop.it
Making smart predictions with statistical models
Tony Brugman (Bright & Company)'s insight:

Nice insight into how data scientists work with machine learning applications. In this HBR article an example of a Machine Learning process is visualized via a decision tree.

 

1. Process: Decide What You Want to Know

2. Build a Model

3. Accumulate Answers

4. Make a Decision

5. Iterate

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Why Good Spreadsheets Make Bad Strategies

Why Good Spreadsheets Make Bad Strategies | HR Analytics and Big Data @ Work | Scoop.it
We live in a world obsessed with science, preoccupied with predictability and control, and enraptured with quantitative analysis. Economic forecasters crank out precision predictions of economic growth with their massive econometric models. CEOs give to-the-penny guidance to capital markets on next quarter’s predicted earnings. We live by adages like: “Show me the numbers” and truisms […]
Tony Brugman (Bright & Company)'s insight:

Reality-check HBR article by Leadership and Strategy expert Roger Martin on 'our' preoccupation with predictability and focus on numbers in decision-making. The blog article has been published in 2010, but is still actual and relevant now. Especially in the world of analytics and Big Data.

 

"We must stop obsessing about measurement so much that we exclude essential but un-measurable qualities from our understanding of any given situation. We must also consider the possibility that if we can’t measure something, it might be the very most important aspect of the problem on which we’re working."

 

Martin wrote a more extensive piece in Rotman Management with the title 'Beyond the Numbers', in which he gave three pieces of advice "regarding the qualitative paradigm":

 

1) Decision making is not only about equations and symbols. We must use all of our senses as we form opinions and make decisions. Numbers can help to describe sensory experience, but they cannot serve as a substitute for it.

 

2) Never dismiss strong feelings that you have but cannot explain. (Sometimes) your feelings will run ahead of your ability to explain them to another person. But that doesn’t mean that they are wrong.

Rather than dismissing these feelings, integrate them into your quantitative analysis.

 

3) Cultivate surprise and learn to embrace it. If the course of action you have chosen — i.e. your model — produces an outcome

that you didn’t expect, don’t get upset and throw out the experiment. Instead, learn from it and adjust your model.

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Earning Consumer Trust in Big Data: A European Perspective on Regulatory Issues and Legal Risks | BCG

Earning Consumer Trust in Big Data: A European Perspective on Regulatory Issues and Legal Risks | BCG | HR Analytics and Big Data @ Work | Scoop.it
As BCG research has shown, consumer trust is the key to unlocking big data’s full value potential; without such confidence, billions of euros in future economic and social value might be lost.

Earning Consumer Trust in Big Data: A European Perspective, a new report by The Boston Consulting Group and global law firm DLA Piper, addresses the competing interests of businesses, consumers, and governments. Specifically, the report examines the unique legal approach to data protection and privacy that the European Union (EU) is taking.
Tony Brugman (Bright & Company)'s insight:

Interesting report by BCG and DLA Piper addressing legal, security and privacy issues of consumer Big Data use by companies and governments in Europe.

 

According to the report earning consumer trust in Big Data is key! "It takes time to gain it, but an instance to lose it". The report gives insights, case examples and tips for mitigating potential issues and risks.

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Beware Spurious Correlations - HBR

Beware Spurious Correlations - HBR | HR Analytics and Big Data @ Work | Scoop.it
Analytical sleight of hand can mislead managers.
Tony Brugman (Bright & Company)'s insight:

Good insights from this HBR article on the dangers of seeing correlations in data graphs and charts.

 

Beware: "When we see lines sloping together, bars rising together, or points on a scatterplot clustering, the data practically begs us to assign a reason. We want to believe one exists."


However, it often is more of a "visual parlor trick to imply a relation."

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Study: Businesses Embracing Big Data but Hurdles Remain for Success

Study: Businesses Embracing Big Data but Hurdles Remain for Success | HR Analytics and Big Data @ Work | Scoop.it

"While companies are racing toward implementing Big Data initiatives, a recent Xerox study says there are significant issues slowing the capture of value. Business executives said there are a wide range of challenges in implementing Big Data strategies, including data security, privacy and data quality."

Tony Brugman (Bright & Company)'s insight:

Results from a Xerox-Forrester study amongst top-level execs from Western European companies "paints a portrait of the Big Data business journey".


Overall "the large majority of companies are moving forward with big data technology (..) but there’s also a wide range of issues that keep executives up at night.”


The study cites three key trends:

- Big data > gut-feeling in decision-making: 61% say decisions made in 2015 are likely to be based more on data-driven intelligence than factors such as gut feeling, opinion or experience

 

- Inaccurate data = costly: 70% encounter inaccurate data, 46% believe it's has negative impact on business

 

- Data security and privacy = big challenge: 37% rate data security and privacy as one of their biggest challenges when implementing big data strategies

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Rise Of The Quants — Again

Rise Of The Quants — Again | HR Analytics and Big Data @ Work | Scoop.it

I graduated from Stanford in the late 1980s with a dual degree in engineering and economics, and, like so many others of my day, I was drawn to Wall Street.


Via David Green
Tony Brugman (Bright & Company)'s insight:

Back to the future... Nice story about the (re)invasion of algorithms and analytics in the financial sector.

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The Algorithm That Tells the Boss Who Might Quit

The Algorithm That Tells the Boss Who Might Quit | HR Analytics and Big Data @ Work | Scoop.it
Companies including Wal-Mart, Credit Suisse and Box are analyzing an array of data points to determine who is likely to leave. The idea is for managers to have early warning so they can take action before employees jump ship.
Tony Brugman (Bright & Company)'s insight:

Is it OK for an employer to predict whether an employee has a higher chance or risk to leave the company? Or does this mean a less 'human'-side in HR? This article from WSJ stirred up some debate (100+ comments).

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Why data storytelling is so important—and why we’re so bad at it

Why data storytelling is so important—and why we’re so bad at it | HR Analytics and Big Data @ Work | Scoop.it
Five reasons why data and analytics-based stories are important to organizations, and four reasons why so many people and organizations do it badly or not…
Tony Brugman (Bright & Company)'s insight:

Tom Davenport on the importance of storytelling in combination with data and analytics.

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