Hey everyone, today you will learn what big data is
and how it is related to HR analytics.
Big data and HR analytics are two buzzwords
that are frequently talked about.
Do you really know what they mean?
And do you know what added value they bring
to the field of HR?
If not, don't worry, that's why we're here.
In this video I'll explain everything you need to know
to answer these questions using different examples,
so stay focused.
First, let's define big data.
What is it all about?
In a way that is easy to remember,
big data is something that can be best described
into four Vs: variety, veracity, volume, and velocity.
Now let's dive into what all these are all about.
First, when we talk about big data, we talk about variety.
Big data comes in all sorts of different forms.
In other words, we're not only talking
about nicely-structured data
that is ordered in neat columns and rows.
We're also talking about unstructured data
like the textual data in an email.
Second, big data entails veracity,
meaning that it can be quite messy
and cannot always be trusted.
Quality and accuracy are thus not always present
in large data sets,
which then makes the cleaning a very important step
in the process of analyzing big data.
Third, there's volume.
Big data, as the name suggests, needs to be big,
and I mean really big.
That is, we're not talking about gigabytes,
we're talking about terabytes and petabytes.
The big in big data represents
millions and millions of cells in your Excel sheet.
Finally, the last V stands for velocity,
which means that big data tends to be dynamic,
as opposed to static.
That is, as things change at a very fast pace,
so does the constantly-collected data.
Take Twitter data, for example.
Gigantic amounts of data represents
hundreds of tweets and retweets every single second.
Now, how do these relate to HR?
First, HR has access to a large variety of data.
Systems containing employee data,
pay information, and engagement scores
are all examples of structured data.
Things like written performance reviews and email content,
on the other hand,
contain interesting information for analysis,
and they're oftentimes unstructured.
Second, in terms of veracity,
HR data is often quite messy and unreliable.
For example, data like someone's career history
within your organization is often missing.
The old date is simply overwritten.
In addition, numerous reorganizations
in restructuring efforts make it hard
to keep it track of how long someone stayed in a function.
Think about it.
How do you know that someone
has kept the same responsibilities
when their job function title
was changed two times in the last three years?
Third, overall, the volume of data in HR is quite low.
I haven't seen a large database with employee records
exceed in a few gigabytes.
This is not necessarily a bad thing,
but keep in mind that for the average HR professional,
a few gigabytes of data is already quite something.
Fourth, the velocity of data in HR is also quite low.
HR data is generally quite static
since records are only changed
when someone switches functions
or when different departments are shuffled.
Last but not least, let's add another V to our list.
HR data most definitely holds value.
When leveraged appropriately,
it can uncover workforce risks,
makes better people decisions,
and help in building a competitive advantage for the firm.
Now let's have a look at examples of big data in HR.
If we look at HR in natural language processing,
for instance, also known as NLP,
we see that most HR departments are sitting on large piles
of unanalyzed written performance reviews.
Yet, you can effectively use NLP to analyze these reviews
and create employee competency profiles
or automatically generate performance scores
for both employees and managers.
You can also use this, too, for example,
with sentiment analysis in email traffic.
You can measure engagement
through analysis of email messages.
This may be slightly tricky to do,
but you could yield very insightful people observations.
KeenCorp is an example of an organization
that has been doing this for the past few years.
They claim to be able to predict employment engagement
and attitudes in different groups by scanning email data.
Now, if it's still not clear enough
what the relationship between big data and HR is,
let's put it this way.
Whenever we talk about predicting employee turnover
or the number of HR self-service tickets
to optimize handling time,
we're working with large quantities of data
that help us generate new workforce insights.
This means that big HR data is the input for HR analytics.
That was it for today's bite.
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to know more about this topic,
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