Human Resources is changing to adapt to the explosion of data and analytics now available, however, it’s changing slower than any other business department. For more information on where HR is compared to other departments, HR is Lagging: A Guide to HR Analytics and Data Science goes in depth into the current state of HR analytics. This lag is in part due to lack of skills and lack of technology, but this article will look to help guide through how to improve both aspects in your department so you can begin to harness the power of HR analytics.
- Identify Your Current Situation
Before creating a plan of action to move your department towards greater analytical capability, you first need to assess where the department’s current state of analytics, both with technology and people.
Some questions to ask as you’re looking into the technology of your department are:
- What data do we collect and how is it stored?
- What systems or softwares do we use to collect and store data?
- Who oversees data quality and management?
Once these questions are answered, you can begin to think about the gaps in the current system and where to improve and update in the future.
The other aspect of the department is the people. For understanding the current comfort level of analytics for the employees, a couple outside inventory assessments can help. The first is called the Data Fluency Inventory from Data Fluency by Gemignani, et. al. which is an in-depth personal and departmental assessment for determining data fluency in an organization. The full assessment can be found here.
The second is an article from HBR, How to Develop a Data-Savvy HR Department, which categorizes HR professionals as Analytically Savvy, Analytically Willing, and Analytically Resistant. Each of these provide a way to look at current employees’ and potential future employees’ comfort with analytics.
- Get your Data Together
A common issue of analytically lacking departments is data is dispersed across multiple systems, spreadsheets, and softwares. Before any of this data can be used, the data must be removed from their silos and aggregated to create a single data source. This creates a more efficient way to use data and a company-wide single source of truth. Along with unifying data, all future data needs to be entered into the consolidated source accurately and consistently by applying data governance principles.
This data can then be used to identify performance indicators in employees and relate employee data to business outcomes to create data-driven solutions. Dashboards can also be beneficial as they allow for visual representation of performance data to monitor crucial indicators and gain insight into success measures for your company. However, while mostly clean and accurate data is helpful, you will likely not be able to reach perfectly clean data so start applying analytics before reaching 100% clean data!
- Build your Data-Driven Department and Culture
Before you decide to hire all new talent with analytical skills, build within the current department. Step 1 above provides self-assessment tools to determine the analytical ability of the department and individuals which can be a great resource to figure out where to begin. HR excels at bringing in appropriate training programs company-wide, but don’t neglect training your own department also.
Start with teaching everyone the basics to establish a department-wide baseline understanding of analytics and the importance of analytics for the company. Over time, a good understanding of potential applications will lead to people creating innovative ways to solve problems and apply analytics to current processes. This will also set the foundations for a data-driven culture which prioritizes data-based decision-making rather than gut feeling or opinions.
There are many options for providing training for an existing team, some options include internal training if the company has strong data analysts, or externally through open online courses, university programs, or specialized organizations. While there is a lot of potential data analytics content to train in, the core topics should be quantitative and mathematical skills, data gathering, survey design, root cause analysis, hypothesis testing, and data visualization. These topics provide basic skills on how to collect, clean, analyze, and present data used for creating impactful presentations with workforce data.
- Hire Analytically Minded People
Along with building up the skills of current employees, another way to add analytical capability to your department is to hire new people who already have relevant skills. While this doesn’t have to be an entire restructuring of your department, supplementing the new skills of current employees can help to increase the capability of the department as a whole and continue to push for data-driven culture. Hiring this talent can be especially difficult for HR, however, since they need to be able to balance both the human and technical aspects of the job.
To find the right talent, screening measures related to analytical ability need to be put in place during the interview process. For screening analytical ability, this can include formal education, psychometric tests, and informal education from open-source courses such as Coursera, edX, or Codecademy. Additionally, screening for potential analytical savviness and commitment to the company’s culture through personality tests such as measuring “investment traits” which look at ability to engage in complex thinking and openness to new experiences. For more ideas on how to find technical talent see the article Top Tips for Sourcing Technical Talent.
- Put Analytics into Practice
Lastly, data analytics can be put into practice for your department. While this is listed as the last step, these practices can be started before the data is fully ready and you have all the skills. The data will never be perfect, and skills take time to build so start early and improve as you learn! Implementing continuously can help put training into practice and create a strong foundation for further down the road. For a list of potential analytics tool, check out the article Top 7 Tools for HR Analytics.
Start by identifying business areas currently collecting data and potential problems that can be solved. Some HR related analytics could be improving employee retention, high-performance identification, company culture satisfaction, or cost analyses related to employment and retention. Analytics will be most successful when linked to a key business outcome, especially ones most important to your organization. Conducting impact vs. effort analyses can help determine which outcome is the quickest and most effective to work on first.
Once analytical practices are in place, drive continuous improvement efforts to remove errors, inefficiencies, and recurring issues. Not only will this make current systems faster, but it will also allow you to build into more complicated analytics, such as predictive analytics, later.