HR Analytics

March 4, 2024

Beyond Data Points: Harnessing Storytelling for Strategic Insights in People Analytics

The role of data within organizations has undergone a profound evolution. No longer confined to static dashboards and dense spreadsheets, it now serves as the cornerstone for narratives driving organizational success. This transformation is particularly evident in people analytics, where the fusion of analytics and storytelling is reshaping how data is understood and utilized.

In our recent webinar, titled "Unlocking Insights through Storytelling in People Analytics," we had the privilege of hosting Stephanie Murphy and Tim Brown, alongside our host, Gabe Horwitz. Here are some insights from the webinar.

  1. Dashboards Are Dead

The conventional wisdom that dashboards are the end-all solution for data presentation is rapidly becoming outdated. Today's narrative, particularly in the context of people analytics, emphasizes storytelling over static visualizations. This shift is driven by the need to convey complex data insights in a manner that is both accessible and engaging to executive leadership.

An illustrative example of this shift can be seen in the challenges faced during the COVID-19 pandemic, particularly by companies like Peloton. As demand for home exercise equipment surged, Peloton struggled to keep up. The dashboards and analytics in place failed to adequately explain the situation.

It was only through the development of a storytelling capability, led by a team member who took the initiative to go beyond traditional dashboards, that the company could concisely communicate the issues at hand. This approach distilled the problem into a few images and slides, clearly articulating market capacity, talent availability, and strategic pivots necessary for meeting demand. This method proved far more effective than a detailed slide deck could have been. It facilitated a direct conversation about the problem, its roots, and potential solutions.

Also, viewing people data as business data is a crucial mindset shift. It reframes the data not just as a resource for HR but as a vital component of the business's overall strategy. This perspective starts with a business question or concept, prompting a proactive rather than reactive approach to data analysis.

  1. Simplify to Amplify: Don’t overload your end users

The sheer volume of data in people analytics can be overwhelming. With thousands of potential data combinations at our disposal, the challenge isn't just in analyzing the data but in determining what to present. The key is not to bombard stakeholders with every possible insight but to distill the information down to what is most actionable and understandable.

Our speakers recommend surfacing only three to five key points from your data analysis. This range is not arbitrary; it's grounded in the capacity of most people to effectively absorb and comprehend information. In many cases, even narrowing it down to a single, most impactful insight is advisable. The rationale behind this approach is straightforward: the goal of data analysis, particularly in the context of HR and people analytics, is to drive action. Presenting too many points can dilute the message and lead to inaction.

This strategy is a crucial component of effective storytelling with data. It's not just about reducing the quantity of information; it's about enhancing the quality of communication. By focusing on a limited number of insights, analysts can spend more time explaining the significance of these points, how they were derived, and most importantly, what actions should be taken as a result.

The art of simplification requires a deep understanding of both the data and the audience. People teams must be able to anticipate what information will be most relevant and impactful to their stakeholders. This often involves a process of iteration and feedback, refining the presentation of data until it resonates clearly with its intended audience.

  1. Strengthening Data Teams Through "Communities of Practice"

Creating unity among data teams across an organization can be challenging, but it's essential for ensuring everyone is moving in the same direction. A practical step toward achieving this unity is the formation of communities of practice. This approach has been particularly effective in fostering collaboration and alignment within companies.

Communities of practice bring together individuals from various parts of the organization who are engaged in similar work. These groups can meet monthly or biweekly to discuss their projects, share best practices, and address common challenges. The key to their success lies in open communication, ensuring all members are aligned in their goals and methodologies.

These communities of practice also pave the way for the creation of specialized committees tasked with developing toolkits, standardizing definitions, and resolving methodological discrepancies, such as how rounding differences in data analysis can lead to varying results. Establishing agreed-upon practices, like standard rounding methods, can only happen through regular dialogue and collaboration.

Beyond solving technical issues, communities of practice prevent the confusion that arises when different parts of an organization present conflicting data or interpretations to leadership. They are a proactive measure for ensuring consistency and accuracy in data reporting and analytics.

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  1. Navigating Data Silos: Building Access and Integration

Accessing diverse types of data across an organization, especially when it's compartmentalized into different departments, poses a significant challenge. The key to overcoming this challenge lies in fostering partnerships and relationships. It's about making deposits in terms of goodwill and collaboration so that when the time comes to withdraw or access data, there's a network of support ready to facilitate it. This approach emphasizes the importance of building connections across the organization to ensure data accessibility when needed.

Centralizing people analytics systems within the HR organization is another crucial strategy. When all relevant data is consolidated in one place, pulling together disparate pieces of information becomes significantly easier. The fragmentation of data across various platforms and departments can hamper the ability to obtain a holistic view of the organization's dynamics. Centralized systems or platforms, like eqtble, serve as a hub for all people-related data, streamlining analysis and insight generation.

However, the reality in many organizations is far from this ideal. Departments may operate in isolation, each using different platforms for data analytics. This disjointed approach makes it difficult to assemble a comprehensive picture. For example, the Total Rewards team, Talent Acquisition, and other departments might use separate systems, complicating efforts to consolidate insights.

Tim's experience at Chobani illustrates a proactive approach to this issue. Upon recognizing the need for holistic data analysis, the priority was to partner with a platform capable of integrating data from across the organization (eqtble). This integration is crucial for uncovering underlying issues that might not be apparent when data remains siloed. For instance, a problem perceived as high turnover might actually stem from attendance issues, a connection that only becomes clear when all relevant data streams are analyzed together.

The goal is to have all data "talking and mingled," enabling a unified narrative that drives strategic decision-making. Rather than expending energy trying to manually bridge data from isolated platforms, finding a comprehensive solution that can harmonize these diverse data sources is more efficient. This integrated approach not only facilitates a deeper understanding of the issues at hand but also supports the development of more effective strategies by providing a complete picture of organizational dynamics.

  1. Tailoring Data Stories: From Technical Teams to Top Executives

Communicating data insights requires a nuanced approach, especially when the audience ranges from technical leaders within specific departments to top executives like CEOs. Understanding how to tailor these communications is crucial for ensuring the message is not only heard but also acted upon.

When engaging with departmental or operationally focused leaders, such as those in engineering, the conversation often demands a higher level of detail. These leaders are deeply embedded in their specific areas of the business and appreciate insights that are directly relevant to their ongoing challenges and projects. They expect the data story to be closely tuned to their specific context, often requiring a subset of the overall data that speaks directly to their operational realities.

Conversely, conversations with CEOs or company founders necessitate a different approach. These high-level executives prefer to quickly grasp the essence of the problem but focus more extensively on discussing potential solutions. They are less interested in the minutiae of the issue and more in understanding what needs to be done to resolve it.

Thus, when presenting to this audience, the emphasis should shift significantly towards actionable insights. The time spent delineating the problem might be minimal, about 10%, with the majority of the discussion dedicated to exploring solutions and what support is needed from top leadership to implement them.

Entering conversations with top executives, the mindset should be centered on the question, "What do you need from me to help you?" This perspective ensures that the storytelling is geared towards eliciting a decision or support, rather than merely sharing updates or insights. For example, a pitch for resources to expand staffing, framed in the context of its potential return on investment, is more likely to be successful when it clearly connects the dots between the immediate needs and the long-term benefits for the business.

The goal of these communications should always be clear before entering the room: what is the desired outcome of this conversation? This forward-thinking approach helps in crafting a narrative that goes beyond a simple status update, which is of limited interest to CEOs. They are looking for the "Now what?"—the next steps that the organization needs to take.

Preparation involves more than just assembling data; it's about testing the narrative, seeking feedback from trusted peers, and being ready to adapt the story based on the executive's response or questions. Such readiness includes acknowledging when an answer isn't immediately available, with a commitment to follow up with the necessary information.

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