Category: People Analytics

The era of exclusive data access is over; today's businesses thrive by making people data accessible to everyone. Traditionally, this kind of data was only accessible to HR departments and top management. Now, the goal is to extend this access to all employees — including line managers and the wider workforce, across departments. This approach is known as the democratisation of people data. Democratising people data means more than just sharing it. It's about a deliberate effort to ensure data is easy to access, clear, and useful for everyone, no matter their job or data analysis skills. Democratising people data offers many benefits to organisations. Key Benefits of Democratising People Data 1. Boosting Financial Performance Making people data accessible to everyone in the company leads to better financial outcomes. Gartner forecasts that organisations encouraging data sharing surpass their competitors in nearly all measures of business value. This happens because democratising people data fosters data-driven decision making at all levels, and makes managers more efficient and employees more engaged. It leads to higher performance, increased productivity, and low retention — boosting financial performance. 2. Improved Managerial Efficiency Giving managers access to employee data makes them more efficient. Now, managers can make decisions that are more informed by data, less biased, and quicker. A single, reliable source of people data drastically cuts managers' decision-making time, turning what once took weeks into mere seconds. They no longer need to argue about the source or validity of data, or wait for a people analyst to respond to their questions. 3. Increased Employee Engagement Letting employees see their own data like performance metrics, leave data, well-being data, and career development data makes them less reliant on HR. It provides autonomy and lets them take charge of their work life, health, and future, creating a better employee experience. At the same time, managers learn who needs flexible hours, who might be getting burned out, how engaged their team is, and what career paths could look like for everyone. This helps them support their team better, making sure everyone has what they need to do well in their jobs. This makes employees happier and more likely to stay with the company. However, even with its many benefits, people analytics is still mainly used only by HR departments in companies. Here’s why: Key Challenges of Democratising People Data 1. Disparate Data Sources A big issue is that employee data is scattered across different systems. It can be in HR software, ATS, emails, spreadsheets, performance management systems, survey responses, and even in paper files or on social media platforms. Business data, on the other hand, is in disparate data sources as well, such as financial systems, customer relationship management (CRM) platforms, sales tracking tools, project management applications, and operational databases. This means the info that managers and employees need to make decisions is spread out and not easy to pull together. Building a tool that brings all the scattered employee and business data together is time-intensive and costly. You need data infrastructure such as a data warehouse, a business intelligence tool, an ELT tool, a storage solution, and more. Then you need a team of experts to build and maintain the tool. This takes the in-house resources away from focusing on your core product, so it is often not considered a sensible investment. 2. Lack of Data Analytical Skills When only HR and leaders use data, they work closely with the data team. But when everyone in the company starts using people data, it becomes near impossible for the data team to respond to all the queries on time. This means not everyone can get help with data when they need it. But making the data accessible to the employees directly — so they don’t have to depend on the people analytics team — is also not a solution. Not all employees have the skills in data analysis to analyse the data and make sense of what the results mean, to be able to actionably use it in their work. Sometimes, this can even do more harm than good. For example, a line manager might misinterpret data on team absences, assuming a problem with employee engagement, and hastily implement changes that disrupt team morale, when in fact, the absences were due to a common flu season. Here, the skill in analytical reasoning — to not take data on face value, but consider other factors that might influence the data, like external events — would have been helpful. Hence, worry about misuse or misinterpretation of data keeps business leaders and HR from making it available across the organisation. 3. Ensuring Data Security and Compliance Making sure data is private and safe gets harder when all employees can access it. Before, when only a few people had access to the data, there were fewer paths for potential leaks, and managing who could see what information was more straightforward. Now every department needs different info and people at different levels need to see more or less data, so building those security features gets more and more complex. Companies need to ask their engineers to build role-level access, train employees on how to handle data safely, and work with legal and compliance experts to follow rules like GDPR in Europe or CCPA in California. All these steps require time, resources, and ongoing effort to adapt to new laws or threats to data security. This is why democratising people data is usually put on the back burner. However, the benefits far outweigh the challenges. In fact, advances in technology and AI have already made it much easier to navigate these issues. Companies that succeed in data democratisation follow some key steps. Getting Started With the Democratisation of People Data 1. Choosing the Right Tech Choosing the right technology means overcoming the challenges listed above. Buying a comprehensive people analytics tool from an external vendor, instead of building it in-house, makes the process easy and quick. The right tool will allow you to share data across your organisation and unlock its benefits right away. Look for the best tool that provides the following: Scalability and integration options: As the organisation grows and the scope of democratisation expands, the tool should be able to scale accordingly and integrate with other systems to provide a comprehensive view of people data. User-friendly data visualisation and analysis: For data to be accessible and useful to all employees, the tool needs to have human-friendly dashboards that allow users to easily understand and interpret the data without requiring specialised knowledge in data analytics. Controlled access and permissions: The tool should enable administrators to set access levels or permissions so that sensitive information remains protected while still sharing relevant data with employees. Compliance certificates: The vendor has all the necessary compliance certifications for all the regions where you operate. If you are looking for a tool to share data across all departments and levels at your organisation, try Peoplebox. With it, you can: Easily and securely share data with everyone. Get actionable insights with Gen-AI. Quickly build custom reports with real-time data. If you're already using an advanced people analytics tool that works well for HR and business leaders, you may not need new tools but rather adjust the current setup to support democratisation. This could involve reconfiguring access permissions or creating new dashboards or reports that are designed for a broader audience. 2. Hold Training Programmes for Analytical Thinking and Data Literacy Running training sessions on how employees can understand, interpret, and utilise data effectively is important to avoid data misinterpretation and misinformation. Data literacy educates employees on the following: Data storage basics: Knowing where and how data is kept. Data formats: Understanding the different ways data can be presented. Understand key analytical concepts such as the following: Cause and effect: Knowing how one thing can lead to another. Correlation vs. causation: Recognising that two things occurring together doesn't imply one causes the other. Probability vs. likelihood: Understanding the odds of something happening. Interpreting driver analyses: Identifying what factors most influence outcomes. Recognising outliers: Noting data points that stand out from the rest. Benchmarking and indexing: Comparing metrics against standards or averages. Asking the right questions: Knowing what to ask to dig deeper into the data. Spotting and understanding trends and patterns: Seeing the trends or repeated outcomes in the data. Reading data visuals: Being able to look at charts or graphs and understand what they're saying Data-driven decision making: How to interpret data insights and apply them to make informed business decisions. Ethics and privacy: Understanding the ethical considerations and privacy laws related to data handling. These trainings often involve assessing company needs, developing a customised curriculum, incorporating practical exercises, and post-training evaluation and support. These training sessions can be provided by: In-house data experts External consultants hired specifically for this, or Utilisation of online courses from platforms like Coursera, Udemy, or LinkedIn Learning Depending on the number of employees and the specific data skills gaps in your company, data literacy sessions can vary in format and duration: Short sessions of 1-2 hours that focus on specific concepts Extended workshops lasting from half a day to a full day for a deeper dive Multi-day courses spread over several weeks or months 3. Change Management for Cultural Shift Rolling out access to people data should be done in small manageable steps, for example: Establishing clear policies for data access and use in partnership with privacy teams, Piloting dashboards at a small scale before wider implementation, and Simplifying processes to ensure adoption, increasing complexity over time. However, after initial success, scaling democratisation of people data requires strategic change management. Successful change initiatives require not only managing the technical aspects of change but also addressing the cultural dynamics that can either facilitate or hinder the transformation process. Enterprise architect Nadeem Malik notes that a lack of change management can even nullify technology investments. In the context of democratising people data, change management includes guiding an organisation through a transition to a data-driven culture. That’s because democratising data isn’t just about the tools and the data literacy; it is about integrating data into the very fabric of the organisation's culture. Here is how you can foster a data-driven culture across your organisation: Get executive support Instilling a company-wide culture shift often goes beyond HR and requires working closely and getting support from people across the organisation, particularly the leadership and executive team. They need to be on board on the importance of cultural change. Although it might seem like a big task, most progressive companies are already investing heavily in data and the leadership would probably be open to supporting you in this endeavour. Leadership Communication Get business leaders, like the CEO and COO, to champion the data democratisation project. A fractional COO might support the company's data-driven efforts part-time in smaller organizations. Encourage them to not only promote this specific initiative but also to frame their communication within the broader narrative of the importance of being data-driven as a core company value. When they talk openly and spark excitement about using data, it signals to everyone that this initiative is crucial for the entire company, not just HR. This approach is effective because culture often starts at the top and trickles down. Incorporate Data into Your Company Values Make data-driven decision-making a core part of your company's values. For example, one of Netflix company values is “Use data to inform your intuition and choices”. It shows the employees that basing their decisions in data is a big part of having a great career there. Promote the Value and Use of Data While data literacy trainings are important, “they are not enough on their own to change company culture on a deeper level,” notes HBR. Companies have to keep talking about how important data is, using things like internal communication channels as well as events, newsletters, and podcasts “to increase employee confidence and stimulate demand for data”, observes HBR. This helps employees gradually accept and adapt to change. Celebrate Employees Embracing Data Culture Publicly acknowledging and spotlighting employees who are using data effectively reinforces the value placed on data in the company. It shows everyone what's important and how things should be done, inspiring everyone else to do the same. “One smallest but most powerful tactic that I have seen, to propel that culture a bit forward, is celebrating individuals for embodying what you want to be amplified across the organisation. So, we try and celebrate individuals who are exhibiting this data-driven culture in all-hands call with our CHRO and other forums,” says Anshul Sheopuri, Vice-President and Chief Technology Officer at IBM Workforce. Measure the ROI of democratising data Lastly, it's important to measure the impact of using people data across the company, and share the success stories. “By publicising your successes, you can encourage more employees to use the data insights available to them and further reinforce the data culture – it’s a cyclical process,” says Andrew Pease, North Europe CTO, Data Platform at Salesforce. Since culture change isn't a one-time deal, the above steps need to be ongoing — especially as people strategy continues to evolve, and new employees join the company. Conclusion As is clear, data democratisation is an extensive process, going beyond the one-time implementation of tools to educating employees and managing cultural change. However, the benefits of increased financial business outcomes, better managerial efficiency, and improved employee experience are worth the effort. Additionally, using built-for-you people analytics software makes the process smooth, quick, and effective — offering data integration, easy-to-understand dashboards, access controls, compliance certifications, and scalability from a handful to a multitude of employees. Ready to embark on your data democratisation journey? Take the next step with Peoplebox.