HR teams everywhere rely on data for decision-making, but the dream of flawless data is rarely a reality. Despite our best efforts, data will always contain some level of bias, inaccuracy, or gaps.

So, how can we  leverage this imperfect data to its fullest potential? The secret lies in storytelling.  Even flawed data can reveal insights that go far beyond numbers and spreadsheets.  Understanding the limitations of data is the first step. This article will show you how to turn those limitations into narratives that drive action and better decisions.

1. Embrace the Imperfection

It might sound daunting, but great storytelling starts with embracing imperfections in data. Instead of seeing these imperfections as a weakness, view them as opportunities to uncover valuable insights for compelling narratives.

In people analytics, the process typically starts with gathering data from various sources, such as employee surveys or feedback forms. The amount of information can be overwhelming, with thousands of comments from diverse perspectives. Sorting through all this data to find key insights is challenging but crucial. It's similar to searching for gold—you need to look closely to find the valuable pieces that can form a great story.

In large companies, the vast scale of data can make finding meaningful stories even more difficult. However, the effort to navigate through this data, despite its imperfections, is vital for discovering useful insights. While some tools can help streamline this process, the key lies in our ability to interpret the data and extract meaningful stories from it.

How to Work Effectively with Imperfect HR Data

• "Perfect" in HR is Subjective: What constitutes perfect employee engagement or high performance? These are fluid concepts. Instead of fixating on "perfect" numbers, focus on trends and patterns over time. Are specific areas of the employee experience improving? Do any departments consistently have different results than others? This comparative analysis is richer than striving for a single universal target.

• Context is King: Data doesn't exist in a vacuum. A dip in survey scores might correlate with a busy season, a new policy implementation, or industry-wide trends. Look beyond just the numbers for the 'why' behind changes.

• Qualitative + Quantitative = Richer Stories: Numbers give you WHAT is happening. Combine them with open-ended survey questions,  interview insights, or even informal feedback to gain a much deeper understanding of the HOW and WHY behind the data.

• Progress, Not Perfection: The goal shouldn't be flawless data, but rather using the data you do have to drive improvements, however incremental. Reframing imperfection as the starting point of a journey can be immensely empowering.

• The Power of 'Good Enough':  Sometimes, you need a directional answer fast, not a six-month analysis project. Learn to be comfortable with 'good enough' data when it gets you closer to timely decisions that benefit your employees.

Let's illustrate this with a scenario:

Imagine your employee surveys show an overall satisfaction score of 78%. Aiming for 100% is unrealistic.

Instead, embrace the imperfection and ask:

• Trend: Is this 78% an improvement over last year?

• Context: Did other companies in your industry see a similar score?

• Qualitative: Look at open-ended comments: What themes emerge?

• Progress: Can you isolate actions to address these themes? Even a small improvement is meaningful.

• 'Good Enough': Do you need more data to pilot a new benefits program that aligns with those themes?

2. Find the Narrative Arc:

No one likes a story with a bad plot and gaping holes in it. So, creating compelling stories with imperfect data requires a structured approach. It starts with the simple task of assessing the quality of available data. Conducting a thorough data quality assessment helps identify potential issues with data reliability, completeness, or relevance. This is to ensure that insights are based on accurate and relevant information. 

This brings us to something very important: - exploring diverse data sources and enriching existing data sets. Remember how we talked about gathering data from a wide range of relevant sources? This helps you conduct a more thorough analysis, making it easier for you to uncover clear and relevant stories that resonate with stakeholders. 

Visualizing data beyond graphs and numbers is another way to make the insights relatable and engaging to different stakeholders at different levels. No matter how many dashboards, insights, and reports you have, viewing data as a reflection of people and their choices can lead you to analyze it differently, resulting in more insightful decision-making. 

Once you have successfully found the narrative arc for your report, how do you build one?

Here’s a quick guide to help you build a narrative arc:

1. The Hook: What's the surprising trend, the unexpected outlier, or the persistent theme that emerges from your data? This opens your story powerfully.

2. The Conflict: Every good story has tension. What are the opposing forces in your data? Are benefits popular, but work-life balance scores low? This tension creates a need for resolution.

3. The Stakes: Why does this matter to your company?  Translate trends into potential business consequences – lost talent, productivity problems, missed innovation opportunities – to raise the stakes of your story.

4. The Path Forward: Imperfect data can still suggest directions. What areas does your story highlight as needing more investigation? Where's the opportunity to test potential solutions?

3. Never Lie About Data:

When dealing with data sources in HR, issues such as sampling bias, measurement bias, and confirmation bias are common. It's important not only to recognize these issues but also to address them with integrity, ensuring your storytelling is both accurate and ethical. Here's how to handle imperfect data while building trust:

1. Transparency with Data Limitations: Be upfront about the limitations in your data. Clearly explain the nature of any gaps, why they exist, and how they might affect your interpretations. This honesty helps set realistic expectations and prevents misunderstandings.

2. Prioritize Actionable Insights: Focus on what the data tells you well enough to recommend specific actions or further investigation. Rather than dwelling on the unknowns, use the available information to guide practical decisions.

3. Combatting Biases: Actively seek out data that challenges your initial assumptions to strengthen your analysis. This approach demonstrates thoroughness and commitment to unbiased decision-making. It’s crucial to critically assess all data and avoid framing it in ways that might inadvertently push an agenda. Let the trends and patterns speak for themselves without being skewed by subjective interpretations.

4. Collaboration for Comprehensive Analysis: Collaborate with managers, employees, or other teams who may have firsthand experiences or insights that can fill gaps in your data. This not only enriches your analysis but also fosters a culture of inclusivity and shared understanding.

5. Check and Enrich Data: Implement thorough checks and processes to verify data accuracy and integrity. To address any gaps, consider integrating data from external sources, conducting surveys, or leveraging third-party data providers. These methods enhance the depth and breadth of your analysis, making it more robust and reliable.

6. Ethical Data Handling: In HR, building trust is paramount. Ensure that every step of your data handling prioritizes ethics and integrity. This includes being transparent about data limitations, focusing on actionable insights, combating biases, and collaborating for better context.

Remember, the goal isn't to eliminate data imperfections but to navigate through them in a way that aligns with your strategic objectives. By adopting a mindset that values progress over perfection and storytelling over mere data reporting, you can transform your HR practices and contribute to the overall success of your organization.