By Peter Smit
Opening the door for new insights
Big Data and analytics has been a popular topic in the business press lately, and for good reason: it is a powerful tool that can add tremendous value to organizations by making tasks easier, faster and more insightful. By pairing Big Data with imagination and creative thinking, unexplored concepts can be developed to boost organizational effectiveness and productivity.
HR and Big Data
While many business functions are increasingly making good use of Big Data analytics (a recent survey found two-thirds of organizations are increasing Big Data spending and have applications in production), HR has been slow to make use of this new tool.
However, CEOs and CHROs are beginning to see how workforce analytics can lead to better talent decisions and better business results. Indeed, applying Big Data to workforce behaviours and data is the next step in the evolution of workforce analytics (which started with 1950s “time and motion” studies and later applied to office workers with 1990s-era “Business Process Re-engineering” initiatives).
People accept that companies like Google, Netflix and Amazon gather massive amounts of data to service “us” better. And, in The Decoded Company, authors Segal, Goldstein, Goldman and Harfoush argue that many companies now know more about their customers than they do about their own employees. But with employee-related expenses representing more than half of an organization’s costs (over 80 per cent if you factor in office space and IT), businesses should be leveraging Big Data to learn more about how they can make employees more effective and productive.
Big Data: who does what?
Many organizations struggle with where to place Big Data responsibility. Who owns it? The business? IT? Or the business functions that use Big Data?
Organizations must recognize that Big Data is a tool to provide new or better insight. It is an enabler. Initially, most organizations hire “data scientists” to gather data and explore questions. Typically, these specialists possess skills in math and statistics; programming and databases; domain knowledge and soft skills; and communications and visualization skills.
The challenge is that once hired, these individuals need to learn the intricacies of the organization’s business and culture. To be effective, they need to be teamed with other individuals with deep business and process knowledge, and together they will develop the hypotheses to be tested. Generally, organizations test hypotheses and over time, those that provide good value will be brought into production.
Decision-making and who will use the Big Data?
People make decisions differently. On one extreme are those who rely on their intuition or “gut feel.” Their decision-making is based on a combination of their experience and their own opinion. The opposite are those who rely on evidence-based analysis. They do not question data, evidence or the rules they have previously used to make their decisions.
Between these two groups are those who apply intuition to facts and data. They are the “collaborators” – individuals who gather both opinions and data from different sources and make their decisions. If the decision goes contrary to established process, they will question and possibly push for change. Although in most organizations, this group is not yet the majority, they are increasing their numbers and more and more organizations are including this dynamic when hiring and training their people. More HR professionals are recognizing that it is these people who will drive better, faster and less costly decisions and solutions. It is this group who will be Big Data users.
How does culture impact big data initiatives?
Warning: before embarking on a Big Data initiative, be sure to know where your organizational culture sits on the spectrum. Where your organization is on this spectrum will determine the possible side effects of a Big Data initiative, especially if it involves HR-related data.
On one end of the spectrum are organizations which are closed, do not share, are unaligned, secretive and where lone efforts prevail. On the other end of the spectrum are organizations that have strong leadership, are open, trusting, sharing and are collaborative in nature. How a Big Data initiative is perceived will be very different depending on where you are on that spectrum.
In the “negative” environment, any initiative using HR data will be received as too much “Big Brother” and be seen as a weapon to control and punish, and also be viewed as a loss of privacy.
In a more “positive” environment, it will be seen as a tool to help improve the organization’s effectiveness and boost productivity – something that’s part of the organizational learning journey and that will improve employee engagement.
A new horizon for HR: measuring organizational collaborative performance
More and more organizations are recognizing the importance of collaboration, not just within teams, but also team to team and across departments.
Many organizations recognize collaboration as a collective skill that is critical to improving organizational effectiveness and boosting productivity – but they wrestle with what it is, and why it does and doesn’t happen.
Organizations striving to benchmark the collaboration performance involved in different projects must do so through costly and lengthy consultations. It’s a complex challenge as collaboration spans many facets: how well does an organization use its collective experience, expertise and knowledge, not just within a particular team, but also team to team or across departments? How frequently do people communicate and how – one-on-one or in groups? Is information being made accessible, are people searching for available information for their decisions and does the organization have the appropriate tools to facilitate information exchange? Does the social environment en- courage connections and exchanges?
Big Data and collaboration in practice
This is where Big Data enters the scene. Typically, most organizations use four or five primary collaboration tools: email, telephone, document repository, social/community, web-conferencing and perhaps a project management app. Each of these applications maintains an activity log recording who did what, when and who else was involved.
This “metadata” functions as the basis on which individual, team and department collaborative performance is measured. Each interaction, by each individual, is “mapped” against the four collaboration quadrants: sharing, communication, social and search. The nature, intensity, direction and balance of each element between individuals will lead to the identification of Collaborator Types *(an example of which is a “remote catalyst” – an individual who is able to initiate and drive a team remotely).
Being able to measure collaboration would have great value for organizations:
- Benchmark their performance against other organizations
Assess how well collaboration takes place within teams and from team to team
Assess how, and how well, IT tools are being used and where additional training or functionality is required
Optimize where people sit, and in which areas remote workers who come into the office from time to time should sit (to the point of even making them aware of where their collaborative network is in the office)
Configure team membership optimally in order to ensure the team will collaborate effectively and immediately (based on previous collaborative working relationships and different “collaborator types”)
Peter Smit is the founder of Collabogence, an organization that uses Big Data analytics to measure collaborative performance on multiple levels.
The Human Resources Professionals Association (HRPA) is in the midst of a thought leading research project with Collabogence and with the sponsorship of Cisco Canada. The resulting White Paper, documenting the findings and conclusions, is scheduled to be published in spring 2015.