By Tony Bagshaw, Teresa Daulong, and Emily Douglas-McNab
In today鈥檚 data-rich, technology-driven world, being a 鈥渄ata nerd鈥� is cool. Even has said that 鈥渄ata scientist鈥� is the sexiest job of the 21st century. Are we surprised? From who we engage with on social media to what clothes we purchase online to the music we download, people around the world are collecting and analyzing massive amounts of data every day. The exponential growth and availability of data is often described as 鈥渂ig data"--and it has become a critical tool for businesses, governments, and other organizations. Why? As SAS庐 , 鈥淢ore data may lead to more accurate analyses. More accurate analyses may lead to more confident decision making. And better decisions can mean greater operational efficiencies, cost reductions, and reduced risk.鈥�
For example, data can help doctors to better diagnose illnesses to save lives. Grocery stores use the data they glean from various sources to reduce internal foot-traffic jams. Marketing departments use data to target products to customers based on their buying history. Police departments use data to uncover evidence that may help solve cold cases. Even the airline industry uses big data to provide piece-of-mind that your baggage will make it to your destination on time!
Big data doesn鈥檛 necessarily mean more data. It鈥檚 about being able to analyze non-relational data and draw conclusions upon which to strategically act. If used in appropriate ways, HR data can teach us a great deal about an individual鈥檚 drivers and behavior, performance, needs, and their potential.
There is tremendous potential for using big data to help HR departments be proactive in hiring candidates who fit the organization鈥檚 culture, identifying the best benefit package to meet employees鈥� needs, managing employee absences, and more.
If you鈥檙e wondering how to assess the maturity of your own big data use in HR, Bersin and Associates has built a to support your analysis. They describe four levels of maturity:
- Reactive
- Proactive
- Strategic Analytics
- Predictive Analytics
The youngest stage is the Reactive stage--where organizations create reports for measuring efficiency and compliance. This is where many HR departments in K-12 education sit. We believe this is due to the availability of HR data and integrated technology management systems in K-12 organizations.
The next stage in maturity is the Proactive stage. This is where reporting is done, and data are collected for benchmarking and decisions making. Some organization use dashboards to assist in these efforts. A handful of K-12 organizations use scorecards and dashboards to drive change and improvement.
The next step-up is Strategic Analytics. This is where statistical analysis is done to identify root causes, commonalities, and correlations.
Finally, Predictive Analytics means the organization uses big data and algorithms to create predictive models, complete scenario planning, and mitigate risk. This level of sophistication requires the right data, technology, leader, strategy, and a data analytics team.
While many organizations see the benefits of using big data, most organizations have a ways to go in to develop a strong HR analytics strategy. According to a whitepaper by the Harvard Business Review Analytics Services Team, 鈥�,鈥� 71% of CEOs surveyed view their people as the top factor contributing to sustainable economic value. Yet, their top ranked priorities were operations (73%), customers (50%), sales (49%), and HR (43%). Further, when asked where their organizations were making investments in big data, sales and marketing were reported as receiving the largest financial investments when it comes to big data use. HR was the lowest of all 10 options.
For those interested in learning more about data mining or data science, in additional to the mass amount of articles online, universities, such as Columbia, Johns Hopkins University, and the University of Illinois at Urbana-Champaign offer free online courses through platforms like .
While the federal No Child Left Behind Act and other federal and state policies have placed a clear focus on capturing data to measure student performance, districts are also seeing the value in using big data for talent management, process improvement, and customer service to improve educational opportunities for students. Tulsa Public Schools (TPS) Human Capital department has been using big data to foster improvement over the past two years. The District鈥檚 strategic plan laid out a vision for shared accountability, which means that every department has a balanced scorecard with aligned measures and data, a defined reporting schedule and structured Board updates. The Human Capital department has measures around teacher and leader effectiveness, recruiting and retention, and customer service. The department is using this data to improve processes, increase the effectiveness of its hiring practices and provide exceptional service to customers. Using this data-driven improvement approach, the district has seen great success. For example, Talia Shaull, Chief Human Capital Officer, shares that TPS, 鈥渉as seen results, such as a reduction in support staff turnover by 6% in the past year and a 38% reduction in the number of complaints received in our HC department over prior year. Having data allows us to make informed decisions and proactively address issues as we move forward down our path of continuous improvement.鈥�
For those who find Tulsa鈥檚 working interesting and are looking for resources, since 2008, the Harvard University Strategic Data Project (SDP) has partnered with districts and education organizations to 鈥渂ring high-quality research methods and data analysis to bear on strategic management and policy decisions.鈥� Their goal is to improve student achievement and growth by transforming how individuals and districts use data. The SDP has identified strategic performance indicators and a diagnostic for human capital focused on teacher recruitment, placement, development, evaluation, and retention/turnover. Visit to access the SDP toolkit with step-by-step instructions on collecting, cleaning, and analyzing data to run the analysis yourself! They even offer a free 鈥淪trategic Use of Data Rubric鈥� that provides districts the chance to assess their strengths and weaknesses when it comes to using data.
Every day, teachers, principals, and district leaders collect a large amount of data, including student performance, bus-on-time statistics, staff retention, work order response times, open positions. The list of data points seems to keep on growing.
In summary, successful use of big data is not determined by how much data you collect. Success happens when data consumers understand the data and its appropriate uses for improvement. While we are still years away from HR departments in schools having the technology and analytics engines needed to reach Predictive Analytics maturity, we believe big data has a place in K-12 education HR departments. We can learn a great deal from innovators like Tulsa Public Schools and the Harvard Strategic Data Project as well as expert users in other industries. Let鈥檚 keep the conversation going!
Share and grow your K-12 HR and talent management expertise via the Twitter chat. These chats are free to participate in and occur the second and fourth Monday of the month at 9 p.m. ET.
This article first appeared in the American Association of School Personnel Administrators (), 2015 Best Practice magazine. Reprinted with permission of the authors.