Thanks to advancements in technology, there is an explosion of data being collected from us daily. Common websites such as Google, Facebook and YouTube have your browsing preferences recorded in a background system, which is then used to inform the newsfeed that appears on subsequent webpages. Navigating your drive to work using a mobile application like Google Maps will mean that that GPS location data will be tracked live simultaneously with all other vehicles and users to help you get to work with no traffic jams and in record time.
Nowadays, every move we make leaves behind a string of data. The new buzzword to capture this phenomenon is ‘big data’ - but what exactly is it?
- Definition of big data
- How can big data help inform best workplace practice
- Limitations of big data
- The future of big data
Definition of big data
In general, big data is defined as the collection of huge amounts of data and datasets which can then be used strategically across a wide range of areas to improve customer experience and to inform business decision making. The form of the data does not have to be numerical digits - it can be captured as open text, photos, videos, voice recordings, and sensory data.
These varied forms of big data usually share three attributes - referred to by Douglas Laney, Chief Data Officer Research at Gartner, as the “three Vs”:
- Volume - the sheer size of data either in terms of number of datapoints or computer disk space usage
- Velocity - the dynamic nature of the data, the amount of data being added and updated constantly and the recency of this data
- Variety - multiple data sources being combined which are distinct (e.g., text and numerical data)
However, data that is on the scale of billions is only of value if there is a way to interpret the data, or if the data is relevant to important industry or organisation questions. Scott Tonidandel and colleagues from the Department of Management at the University of North Carolina says it may be more effective to define big data as a different way of thinking about and visualising data.
How can big data help inform best workplace practice?
Big data is based on the principle that the more data you collect, the more reliable predictions will be. With more and more historical data points collected, relationships that were previously hidden begin to emerge, which can then be used to make better predictions. Employees surveys, like most organisational psychology research, are snapshots of workplace attitudes at a single point in time. Usually after survey debriefing and action planning, there is some sort of change intervention. Attitude shifts captured by follow-up surveys are attributed because of that intervention.
Big data in the HR analytics realm takes a different approach. There is no specific start and end to data collection because new data keeps being collected. There is also no change intervention that is controlled and rolled out. Essentially, there is no clear start nor end as to what sorts of insights can be drawn, because the dataset itself is continuously changing.
Therefore, the major advantage big data provides is its adaptive predictions, which can offer a lot of value when it comes to informing best practice in the workplace. For example, Alex Pentland, director of MIT’s Human Dynamics Laboratory, analysed communication patterns in teams. Team members were given wearable personal sensors which tracked their interpersonal networking behaviour within and outside of formal work meetings. Analysis of their geographical and verbal data over multiple work days (more than 100 data points per minute per individual) highlighted the importance of social relationships in team performance. These big data insights led to workplace recommendations to introduce shared break times to foster efficient social connections and improve staff engagement and productivity. To have a more in-depth understanding of the research, please read Alex’s Harvard Business Review article.
Limitations of big data
Although big data is a great tool to inform business decisions, it does have limitations.
Potential misinterpretation of data
Data analysts can use big data to obtain correlations, i.e. when one variable is linked to another, and use correlations for predictions. However, not all these correlations are necessarily substantial or meaningful to a business and its employees. Insights can be drawn to an endless array of questions; however, it is up to the individual to determine which questions are meaningful. The type of data collected can also be inconsistent and subject to change as a business adapts to the evolving market. Using the wrong data, misinterpretating the data or getting the right answer to the wrong question can be costly for a business and its stakeholders.
It may also be difficult to safeguard and manage big data. Big data is prone to data breaches, and it takes technical knowledge to understand how to store data safely. It also requires expertise to obtain relevant data efficiently and effectively to an analytics team. It may also be difficult to consistently transfer relevant data to external specialists for analysis.
Cost of big data
In addition, a big data approach to HR practices may not result in the best return on investment. The largest companies have thousands of employees, not millions, and common HR observations on those employees (e.g., performance reviews, 360s, etc.) are still for the most part annual. In small to medium-sized organisations, there may be even less reason (and resources) for HR to use special software and tools that are associated with big data. For most businesses, the current challenge in HR is simply to use data at all.
The future of big data
The amount of data that is being gathered is increasing at an unprecedented rate and will continue to increase as technology to capture big data develops. For organisations, the ability to leverage big data to inform evidence-based practice may provide an opportunity for competitive advantage, but it does come with its setbacks. The use of big data is akin to using any other complex technology - it is powerful, but one needs to really know how to use relevant data to drive meaningful results in a cost-efficient manner.
As a first step into the world of big data, it may be more useful to link current survey data with other organizational and employee data to learn how surveys can predict core business outcomes like performance, absenteeism, safety incidents and turnover.
If you have any questions or would like more information about how to use your data to improve your organisation, please contact us on 1800 8 VOICE or email@example.com.