In today’s dynamic business environment, the use of data and analytics is key to effective and informed decision making. This use of data and analytics is not only limited to one or two core front-facing functions. In fact, both front and back-office functions of organizations are relying more heavily on the data collected and stored to make respective decisions for their functions. The function of HR is no exception. HR analytics is now being used to make effective people strategies and take informed decisions to implement those strategies. All this to drive up employee satisfaction, meet cost objectives and in the process become a great place to work. However, a lot of times, HR leaders and professional face 3 critical questions:
Where to start?
What data to use?
Who will do this?
The aim of this blog is to cover aspects of the above three questions.
Where to start and what data to use –
In recent times there has been a lot of emphasis on using HR analytics for the purposes of strategy alignment, execution, organizational effectiveness, and developing competitive advantage on the people agenda. In our view, the HR analytics process cycle is a proactive and systematic approach to building HR analytics capabilities. More importantly, it serves as a proactive and systematic process for establishing a comprehensive portfolio of strategic HR analytics practices, projects, and priorities that enable HR strategy, evidence-based decision making, and the execution of the overall business strategy. A typical HR Analytics process cycle comprises 7 steps. Let us understand each step one by one.
#1. Determine stakeholder requirements – This is the foundation of any data and analytics project. For whom are we doing the project? What kind of analysis are the stakeholders looking at? What kind of decisions will be made by these stakeholders using HR Analytics capabilities? It goes beyond meeting a few influential or vocal stakeholders each year to formulate the annual HR research and analytics agenda. It is about establishing and cultivating a partnership and becoming a legitimate player by adding value to the business.
#2. Define HR research and analytics agenda – Once the stakeholder needs and expectations are identified, it is time to define the Hr research and analytics agenda. An HR research and analytics agenda may be long term or short term. In the day and age of on-demand data aggregation, AI, and automation, the long term is no longer 3-5 years. In our opinion, even 1 year can be considered a long term. Similarly, monthly or quarterly time periods can be considered short term. It is important to note that the short term doesn’t necessarily mean tactical or reactive, nor is long term equated with strategic. Short-term and long-term research requirements can be both strategic and tactical in nature.
#3. Once the HR research and analytics agenda is established, the next step is to identify the sources of data that will help to answer the HR research and analytics questions and hypotheses. Data sources may be either public or private. Public data reside in university libraries and governmental databases (e.g. UK’s Office of National Statistics, U.S. Department of Labour Statistics). Private data includes an organization’s internal employee data housed in its HRIS as well as external benchmarking data from “best-in-class” organizations.
#4. Gather Data – This step involves the actual collection of data using primary or secondary research or mining the internal HRIS of the organization. Primary research may need to be carried out where the research is new and addresses a specific question. Secondary research may reference past research reports, external benchmarks of other organizations, so on and so forth. HRIS will include all the necessary employee-related data that may have to be collected to vary out the analysis in question. Some of the important data used for HR analytics can be as follows:
Other HR Data
Employee survey data
Employee travel data
Employee wellness and wellbeing data
Employee absence data
Other business data
#5. Data transformation is the process of converting data from one format to another. The most common data transformations are converting raw data into a clean and usable form, converting data types, removing duplicate data, and enriching the data to benefit an organization. During the process of data transformation, an analyst will determine the structure, perform data mapping, extract the data from the original source, execute the transformation, and finally store the data in an appropriate database
#6. The 6th step of the HR analytics process cycle involves communicating intelligence results. It is not about just conveying a few numbers or metrics but about the story those numbers and metrics convey. Storytelling can be a powerful approach in communicating data-driven insights, both in words and visually, because it stimulates emotions.
#7. Finally, once the results have been communicated, HR strategy formulation/update/decision making takes place and the process is repeated again with the next project based upon the HR research and analytics agenda.
Competencies for an HR analytics professional (Who will do this?)
HR analysts are responsible for identifying and assisting in solving HR related issues, ensuring these adhere to the organizations’ policies and objectives. Analyzing and evaluating data and reports, feeding back the findings to relevant managers, and advising on changes and improvements are all part of the role. In essence, he/she acts as an internal consultant to the organization. Considering this, the core job competencies of an HR analyst are in a lot of ways similar to those of a management consultant. These include the following:
Business Acumen – This is a must as it’s important to truly understand the impact of the analysis on the overall business.
Data Analysis – This is a no brainer. The individual needs to be comfortable with working with large volumes of unstructured data to solve the business problem
HR Expertise – Sound knowledge of core HR functions like talent acquisition, performance management, compensation and benefits, learning and development, HR policies amongst others is key to be successful in the role of an HR Analytics professional
Consultative Communication – Since this role is akin to that of an internal consultant, the individual should be comfortable in communicating results to key stakeholders in a manner that enables well-informed decision making
Stakeholder Management – this role does not work alone. All the work done as part of this role will be consumed by a number of stakeholders across the organization. Expectation management is a requirement for analytics success. In addition, you need to keep the business involved in your analytics project and keep them up to date in progress and potential setbacks
HR Systems Implementation – HR data comes from HR systems, often referred to as the Human Resources Information System (HRIS). These transactional systems contain most of the data that the HR analyst works with. Implementing, maintaining, and updating these systems is part of the analyst’s responsibility.
Author / Educator – Devam Malhotra, Co-founder & COO, Zekardo Automotive Solutions
Lately, Devam has embarked on his entrepreneurial journey. He is also the Co-founder and Managing Partner of Positive Vibes Consulting where he pursues his passion of mentoring young students, professionals, and entrepreneurs.