What Is People Analytics?

What Is People Analytics?

People analytics is defined as the deeply data-driven and goal-focused method of studying all people processes, functions, challenges, and opportunities at work to elevate these systems and achieve sustainable business success

It can be defined as the deeply data-driven and goal-focused method of studying all people processes, functions, challenges, and opportunities at work to elevate these systems and achieve sustainable business success.

People analytics is often referred to as talent analytics or?HR Analytics?as well. Essentially, gathering and assessing people analytics leads to better decision-making through the application of statistics and other data interpretation techniques.

Smarter, more strategic, and data-backed talent decisions are thus closer at hand, and this is applicable throughout the employee?lifecycle?– from making better hiring decisions and more effective performance management to better retention

The Process of People Analytics

People analytics today is a lot more intuitive and predictive. With that expectation to live up to, the process involves the following steps.

Step 1: Dig data that matters

What data is relevant to our business goals?

set the key performance indicators (KPIs) accordingly. This allows you to save major resources by only investigating areas that need direct monitoring, such as operational tasks within the people management spectrum, and can lead to tangible business success.

If it does not add strategic value, digging that data could be a waste of time. Knowing what to focus on also helps in applying the right statistics, data mining, machine learning, survey management, and strategic workforce management tools.

Step 2: Experiment, explore, enrich

In a crowded and visibly fragmented market, it is imperative to choose a people analytics tool by exploring the market, experimenting with different options, and analyzing which option would enrich the organization the most. Multiple offerings include data mining, data transformation, and data visualization techniques, all merged into a user-friendly self-service interface.

Platforms that offer a wide range of features often require a lot of manual manipulation to access important data, and these aspects can be tested only through systematic experimentation.

Step 3: Have an action plan ready

Once you know what your end goal is, which data is relevant, and what the available options are (based on clear pros vs. cons analysis), create an action plan. Applying big data and predictive analytics to?talent management, leadership development, and organizational capabilities often helps in fine-tuning the action plan.

Moreover, having a well-defined plan of action enables a better understanding of why certain changes may be taking place and where the organization is headed and can thus help garner more stakeholder support.

Step 4: Avoid legal loopholes

Ensuring that legal compliance is maintained in the collection of all data is crucial. Before you start on the analytics project, have a legal team validate the data sourcing techniques and processes. It does not end here.

Once the raw data has been gathered and treated, the results gleaned need to be approved as well before they can be applied or published. In our digital ecosystem, with data protection and privacy laws still evolving, it is prudent to keep abreast of the changes and double-check on legal compliance.

Step 5: Create leaner systems

Irrespective of the complexity of the project at hand, the broader strategy that the processes must adhere to needs to be simple and lean. The basic process of data analysis and interpretation should allow for easy application, updating, and readability.

For example, create the basic outline simplified as intake and design (data collection and the design of the analysis), data cleaning (removing irrelevant or unreliable data), data analysis (quantitative and qualitative exploration), and sharing insights (interpretation and presentation of the data). This can help avoid unnecessary complications such as confusion about the flow of steps involved, time wastage, or repetition of sub-processes that occur with?unstandardized?process structures, while still allowing room for tweaks where necessary.

The idea is to find the right balance between the limited moving parts (people and the dynamism of the environment) and fluid, customizable systems and processes of people analytics. When you have the right team with the relevant?skillset?in place, it is easier to streamline the whole process and apply quality controls.

Step 6: Build a fact-based, measurable HR business strategy

A realistic HR business strategy avoids functional silos and can align talent to business seamlessly. Having clear?KPIs?and?ROI?expectations from people analytics endeavors ensures that the impact is measured often and with transparency. A winning strategy needs to be backed by data and an effective plan of action.

Step 7: Take tech support

Technology is interspersed with every aspect of life today and more so with processes like people analytics, where often a bulk of analytical data is to be treated with little or no room for error. New-age HR tech tools make real-time data easily accessible. And this is an opportunity that needs to be milked because today, agility and real-time intelligence can truly set you apart from the competition.

Benefits of people analytics

• Making data-driven decisions and practicing evidence-based HR?– By analyzing hiring data and improving the recruitment process based on that, for example, organizations can increase recruiting efficiency by?80%?and decrease attrition rates up to 50%.
• Shaping organizational strategy through HR interventions?– People analytics enables organizations to translate data into action and employ evidence-based practices that help improve the overall organizational strategy.
• Improved performance?–?Dashboards?and trends that highlight specific problems, including collaboration, workload, diversity and inclusion, workplace risk assessments, all contribute to optimizing performance. In some instances, the use of people analytics has nearly?doubled?employee output and thus performance.?
• Realizing cost savings?– Organizations can achieve this, for example, through reducing turnover and optimized workforce planning. By using artificial intelligence and people analytics, IBM was able to predict with 95% accuracy which workers are about to quit their jobs. It enabled them to address these concerns and work on other areas, such as future hires for at-risk roles.?
• Closing skills gaps?– People analytics allows organizations to understand workers’ current skills, the future skills needed according to business need and thus?bridge the talent gap. In this way, you can build a pipeline of talent and create development programs based on the future needs of the business.

People analytics examples

Uber

The company achieved this in three steps. Firstly, Uber ensured that the right people had access to the necessary data and dashboards. They empowered managers to have access to their people analytics solutions, and not only the HR. Secondly, the HR team took a user-oriented solution by asking leaders what they needed and then designed their people analytics solutions around that.

Finally,?Uber optimized their employee dashboards to provide clear insights into a specific question. Therefore, all unnecessary visuals and dashboards were removed, making it simple for anyone to interpret and decide. Before, managers at?Uber?would have a two-week turnaround time for a talent decision because they had to go via HR. However, with real-time data available, they were able to make timely decisions and improve their effectiveness.

NASA

NASA?is building knowledge grapes to show the relationships between people, skills, and projects. The people analytics project aims to connect employees to training, and identify skills, knowledge, and technology and translate it to make sense.

These various ‘dots’ are connected, and that’s where the knowledge graphs play a role. This allows employees to understand their career path and how to change their careers as well. It also allows for greater alignment of people strategy across the organization.?

Microsoft

Microsoft launched a tool called “Manager Hub.” This is a one-stop hub for managers to get information and is seen as an insights generation platform. The platform gives suggestions for managers to take specific actions and why they need to take those actions.

It contains timely prompts based on real data, such as whether managers have one-on-one discussions with employees and have ‘connect sessions.’ The tool is managed via push notifications which are linked to the work calendar.

How can HR start building People Analytics capabilities?

Define your analytics strategy

?The first step is to align your people analytics strategy with your business strategy. From this, you need to understand what you want to create and what insights you want to gain.

There are seven pillars as a starting block to build people analytics capabilities in the workplace:

• Get an overview of your team’s capabilities?– You need to figure out the existing skillset of your organization. As?basic?people analytics skills, your team will need to have:?
• Data governance and architecture
• Data science
• Behavioral science
• Business acumen
• Change management

Once you have plotted your team’s strengths, you can now start training where there are apparent skills gaps. Besides the hard skills, your training should also contain ‘the importance of data’ and ’emotional intelligence and people analytics. This can be done through workshops, online training, and specialized classes by the data science department.?

• Fostering data-driven culture –?You need to develop a culture where people make business decisions based on data. Instead of ‘gut’ decision making, slowly start to move decision-makers to use more data instead. This requires the necessary data to be readily available and valid to change the culture. It needs to be evident in all HR processes, such as recruitment, onboarding, offboarding, talent management, learning and development, organizational development, and workforce management.?
• Acknowledge that it’s a process?– You won’t build an advanced people analytics capability overnight. With anything new, there will be an initial resistance and complaints, which is natural. It is important to continue to improve and keep adding to your people analytics repertoire. Solution providers are creating new and advanced people analytics solutions every week, so it is essential to keep an eye on what is new and useful.?

Four Key People Analytics Trends

1. Transforming what HR is and does

2% of HR organizations have mature people analytics competence to bank on. There is thus quite a heavy first-mover advantage for innovative, intelligent organizations that are trying to tap into this space.

With people analytics changing how recruitment is conducted, how performance is measured, how compensation is planned or growth is mapped, and how learning and retention can be managed better, people analytics is quickly changing how HR operates.

According to recent studies by?Deloitte, increasing job offer acceptance rates, reducing HR help tickets, and optimizing compensation are just a few ways in which people analytics is quickly becoming the new currency of HR. Moreover, with HR processes evolving to keep pace with business needs, people analytics is moving from being a one-time initiative to becoming a real-time, easily modifiable tool that HR has immense benefits to draw from.

2. Transforming HR business interactions

With recent trends in the work ecosystem, the interaction between HR and business stakeholders (both internal and external) has been undergoing a transformation as well. People analytics needs to change in keeping with the latest trends in leadership. More transparency is a key trend emerging here, and intelligent insight is the need of the hour.

Businesses today need to be able to make sense of seemingly unrelated data streams and find meaning, correlation, and maybe even interdependence between one or more factors to predict and manage work better. People analytics has the potential to provide actionable recommendations to enable strategic planning and execution processes.

3. Transforming the HR-employee relationship

Employee expectations today are consumer-grade. People analytics is providing organizations with the ramp to upgrade the?employee experience. Every interaction that a candidate or an employee has with an organization is a data point and could be utilized to glean interesting insights. The idea is the need to transform the relationship that the HR has with employees – to help HR become and be perceived as more than just a support function.

4. Transforming the quality of insights

The quality of insights that are expected on a daily basis has changed over the course of the last couple of years. People analytics can live up to these expectations if you focus on two key aspects: analytics literacy and data security.

More employees will need to become analytics literate to decrease dependence on technical staff and to allow more perspectives to flourish. As people analytics becomes a staple at organizations, data integrity and data security will need to be upgraded and maintained for all listening channels and pulse checks.

We discussed legal compliance, but data security should ideally go deeper than that and become a cultural trait within the organization rather than being superficial check just for the sake of being compliant.

Conclusion:

Organizations need people analytics capabilities to make better decisions. HR professionals need fundamental people analytics skills to be relevant to organizations. By building these capabilities and skills, both companies and HR professionals will improve their competitiveness.