Big data. A strong contender for business buzzword of the year 2017. You’ve probably heard the term, but maybe you’re unsure what it actually means? It’s simply defined by McKinsey Global Institute as “any dataset that is too large for typical software tools to capture, store, manage, analyse”.
You might find that most definitions of big data are vague, but so are some of the applications. You should care about big data, because if you get it right, it can help your HR department prove its worth to company directors, through data-led decision making.
Barman and Ahmed (2015) suggest that big data analysis has the largest implications within HR departments. The following pie chart was produced in their research paper, Big Data in Human Resource Management – Developing Research Context
The 5 V’s of Big Data
Bernard Marr, says that:
Essentially, big data refers to two major phenomena:
- The breathtaking speed at which we are now generating new data
- Our improving ability to store, process and analyse that data
- The size of data – not measured in bytes, instead, Mr Marr refers to the example that 10 billion messages are sent on Facebook every day, and the “like” button is clicked 4.5 billion times.
- The speed at which new data is created. A good example of this is fraud checks that are carried out on credit card transactions. This can occur in milliseconds.
- The different types of data. Think of photos, videos, social media posts. These cannot easily be put into tables or a structured format.
- The trustworthiness of the data. data can be less controllable (think social media posts). However, simultaneously the sheer volume of big data can account for the lack of quality or accuracy.
- Ability to turn data into value. Without value big data is useless. Don’t fall into the trap of a big data venture without making it worthwhile for your business.
Eileen McNulty talks through authors that have each contributed V’s towards 7V’s of big data. adding Variability and Visualisation to the 5 already stated in this article.
Big data, getting bigger
Who remembers floppy disks?
Once upon a time, people used floppy disks. In 1986 the standard floppy disk held 1.44MB. You can’t even fit an average MP3 file on that these days. That was roughly 30 years ago. In three decades, technology has come a very long way. Those familiar with Moore’s law will be telling me I’m stating the obvious. For those who don’t know, Gordon Moore (Co-Founder of Intel) made the observation that computing would increase in it’s power, and decrease in relative cost at an exponential rate.
Data is often measured in bits. There are 8 bits to a byte.
Most people are familiar with the terms kilobytes, megabytes, gigabytes, etc…
1 kilobyte (KB): 1,024 bytes
1 megabyte (MB): 1,048,576 or 1,0242 bytes
1 gigabyte (GB): 1,073,741,824 or 1,0243 bytes
1 terabyte (TB): 1,099,511,627,776 or 1,0244 bytes
1 petabyte (PB): 1,125,899,906,842,624 or 1,0245 bytes
1 exabyte (EB): 1,152,921,504,606,846,976 or 1,0246 bytes
1 zettabyte (ZB): 1,180,591,620,717,411,303,424 or 1,0247 bytes
1 yottabyte (YB): 1,208,925,819,614,629,174,706,176 or 1,0248 bytes
It’s not the size – it’s how you use it
Strangely, some multi national companies try to claim usage of the largest datasets. Which I find quite odd.
Due to the nature of some businesses it makes sense for them to have large datasets, for example, Cern recently just surpassed 200 petabytes. But don’t think the need for a large data set applies to you, and feel the need to compete with other businesses on the size of your dataset. You could just end up drowning in a sea of data, lacking any real benefit.
After all, big data isn’t just for big businesses; there are plenty of benefits for SME’s too. Using big data is not about thinking bigger, it’s about thinking smarter. Marion Barraud wrote an article for Harvard Business Review, which was titled “You Don’t Need Big Data — You Need the Right Data” which I think adequately sums up my point of view.
That said, as a rule of thumb, more of the ‘right data’ is probably still better than less of the ‘right data’.
But how does any of this apply to human resources?
A quick search on Google Scholar will show you hundreds, maybe even thousands of articles detailing potential uses and/or hazards of big data analysis in HR. Entrepreneurs and analysts, such as Matt Straz (Founder and CEO of Namely) are suggesting the implementation of big data in the long term will enable firms to:
- Deliver better training to employees
- Hire more suitable applicants
- Have a higher retention of employees
- Gain better insights into the management of employees
Ultimately, the aim is to create value for your business and its employees, which can
potentially be converted into higher sales, revenue and hopefully profit.
If it’s that easy – why isn’t everyone doing it?
Although I disagree, it’s worthwhile noting what Mr Cappelli has to say. He points out HR datasets are limited in their use, which is of course a valid observation. There are many things to consider, for example data protection, which will be a particularly big implication for HR departments.
There is debate between whether focus of analysis is better aimed at causality, or correlation. It’s notoriously difficult to determine causality. Correlation however is a much simpler starting point.
You shouldn’t expect sudden results from big data, however they can be achieved. Analysis of data is generally considered more reliable if it is tested over a period of time and constantly reassures the same conclusions. Intuition might serve some of the more experienced HR managers better than bad analysis.
Right time, right place, right data?
Josh Bersin emphasises the importance of using the right data, at the right time, in the right way. His contributions to Forbes pose the view that big data as a stand alone tool, isn’t particularly effective. However Mr Bersin does suggest that HR departments effectively utilising big data are:
- Producing more effective reports
- Four times more likely to be respected by their business counterparts
- Making better hiring decisions, with leadership pipelines that are 2.5X as healthy as competition firms not using big data to power its data lead decisions.
Apply HR big data to reveal how knowledge flows through your organisation
Innovisor is a company that combines the big data from HR, with organisational network analysis. Richard Lalleman manages the company’s Network Diagnostics Centre of Excellence, and he believes that HR big data is moving away from a standalone tool, into an integrative solution that brings companies real action-oriented diagnoses.
The image below, from Innovisor, shows one such action-oriented diagnosis. It uses data to illustrate how a real organisation is connected.
When I asked Richard to explain the graphic, he told me the following:
“It illustrates how knowledge is shared, and helps you to identify individuals that act as bridge builders, and highly connected employees. This shows who takes part in critical knowledge flows, but also where your organisation is at risk. In this image, you can see that the knowledge flow in the largest network only depends on one individual. If this individual leaves, the network will fall apart.”
By putting HR big data on top of these connections, Richard believes we can gain evidence-based insights on barriers to success. We can learn which people should be connected, as well as what might be stopping them from being connected.
Is big data more than just the latest buzzword?
Essentially, it makes sense for your HR department to get to grips with big data and the implications surrounding it, before you fall too far behind. Perhaps if your business doesn’t yet employ big data at all, your department can lead the way, showcasing creativity and innovation.