At Epoch’s Employee Experience Symposium, Keith Choy, Co-founder and COO, and Meg Dietrich, Customer Success Lead at Epoch led an amazing workshop: Build your Dream Data Dashboard. View the full recording here. Scroll on for notes! 👇
Full Suite of Integration
During the workshop, customers suggested a wide range of ideas for potential integrations aimed at improving their data collection processes. Here's a summary:
- Human Resource Information System (HRIS): Integration with HRIS was suggested as a key strategy to consolidate employee data and facilitate better analysis of HR metrics.
- Event Budget: Participants indicated the potential benefits of integrating event budget data, providing valuable insights into spending patterns and efficiency.
- Employee Calendars: Integration with employee calendars was highlighted as a method to monitor employee availability, meeting patterns, and overall time management, which could help in understanding and enhancing productivity.
- Swag Account: Linking a 'Swag' account, where data on promotional merchandise is kept, was seen as a way to understand preferences and the impact of such items on employee morale and engagement.
- Room Allocation Systems: Integrating with in-office room booking systems was suggested to analyze space utilization, assist in efficient allocation, and potentially uncover opportunities for improving the working environment.
- Recognition and Rewards System: Participants recommended integrating with a recognition and rewards system to gather data on employee achievements, motivating factors, and to assess the effectiveness of current recognition strategies.
In summary, the ideas proposed all contribute to a more integrated, data-rich environment, facilitating a more comprehensive understanding of employee behavior, preferences, and productivity, which could lead to strategic improvements across the organization.
Data Filtering and Segmentation
During the workshop, our customers brought forward several ideas to enhance data analysis and increase employee engagement. Key highlights include:
- Enhanced Data Filtering and Segmentation: The participants discussed the importance of refining data segmentation and filtering processes. They suggested categorizing data into various dimensions such as demographics, department, role, team, and organizational level.
- Focus on Generational Differences: Understanding the behaviors and preferences of different generations, especially Generation Z and Millennials, was deemed crucial for practical data analysis.
- Role-Based Insights: Participants emphasized tailoring data breakdown by roles - particularly identifying different needs and perspectives of various positions like the VP of Culture, CFO, and CEO.
- Leader Engagement: The idea was put forward to track leadership attendance at events as a possible measure of setting an example for the rest of the team.
- Employee Engagement Levels: It was proposed to monitor the highest and lowest levels of engagement among employees. Participants suggested conducting follow-up inquiries with highly engaged employees to understand their motivation and with less engaged ones to identify potential issues or roadblocks.
In summary, the ideas generated in the workshop primarily revolve around improved data analysis methods, focusing on role and generational differences, and enhancing both leadership and overall employee engagement.
Data Correlations + Trends
In the workshop, our customers proposed various ideas for exploring data correlations and conducting trend analysis to enhance business performance. Here's a summary:
- Return on Investment (ROI): Participants suggested correlating time and money spent on initiatives to understand their return on investment. The idea was to use ROI as a measure to evaluate effectiveness and justify further investment.
- Sentiment Analysis: By correlating sentiment, ROI, and cost per head, the workshop participants proposed to assess the overall success and efficiency of events or initiatives.
- Engagement and Connections: The group discussed drawing correlations between the level of engagement and the number and quality of connections formed, indicating the possible impact of networking on involvement in activities.
- Retention and Engagement: Customers proposed analyzing the relationship between employee retention and engagement levels, suggesting that higher engagement might lead to lower turnover.
- Event Attendance and Career Progression: Participants expressed interest in tracking whether those attending events are staying longer with the company and if they're being promoted more frequently, to understand the impact of such events on career progression.
- Budget and Timelines: Correlating budget with timelines was proposed to assess project efficiency and effectiveness.
- Connectedness Web: A suggestion was made to create a "connectedness web" – mapping employee connections that were created through events so that to understand trends and patterns.
- Employee Journey and Event Attendance: It was suggested to map event attendance across an employee's journey to understand the impact of these events on employee satisfaction and retention.
- Event Engagement and Performance Metrics: Participants proposed investigating correlations between event engagement and metrics like company confidence, brand pride, and customer satisfaction (CSAT).
- Business Performance Correlation: Lastly, it was proposed to examine the overall correlations of event attendance with business performance to understand the broader implications of such engagement.
In summary, participants put forward a variety of innovative ideas for correlating data points, all aimed at extracting valuable insights to enhance event planning, employee engagement, and overall business performance.
AI - Generated Insights
During the workshop, customers suggested a range of applications for generative AI to streamline their tasks and improve data analysis. Here's a summary of their ideas:
- Data-Driven Insights: Customers were keen on leveraging generative AI to convert raw data into actionable insights. They envisaged a system that automates data interpretation, providing valuable recommendations based on patterns and trends, thus eliminating the need for manual data analysis.
- Automated Data Visualization: Participants highlighted the potential of AI to automatically generate meaningful data visualizations. This would involve translating complex data sets, such as department-wise comparisons of weekly working hours, into easily understandable bar graphs and pie charts, thus enhancing data comprehension and decision-making.
- AI-Generated Communication Templates: The suggestion here was to use AI's natural language processing capabilities to evaluate historical communication data and identify the most effective templates. These templates, having proven to drive high event attendance, could then be used as a basis for future communication strategies.
- Intelligent Scheduling: Customers highlighted the advantage of using AI to integrate public holiday and PTO data from various locations. This would enable the system to advise against scheduling events on days with anticipated low availability, thereby increasing event participation.
- Optimized Event Dates: The concept here was to use AI's predictive capabilities to analyze factors such as other planned events, potential attendee availability, and historical event attendance data. This would allow the system to suggest the most favorable dates for hosting events, minimizing competition and maximizing attendance.
- Branded Reporting: Participants desired a system where AI not only generates data-driven reports but also ensures the reports align with the company's voice and branding guidelines. This would involve training the AI on the company's unique communication style, thus maintaining brand consistency across all outputs.
- Event Engagement Wrap: Drawing inspiration from Spotify's end-of-year wrap, customers proposed a similar model for summarizing event engagement. The AI would generate a comprehensive year-end report detailing key engagement metrics, trends, and insights, providing a valuable retrospective and input for planning future events.
- Event Creation Best Practices: There was interest in utilizing AI to compile a checklist of best practices for event creation. This could include crucial steps, common pitfalls to avoid, and proven strategies, all derived from analysis of past successful events.
- Benchmarking and Crowdsourcing: Participants suggested using AI to benchmark their company's performance against industry standards or competitors. Additionally, the AI could leverage external data sources to identify successful strategies and practices from other companies, which could then be adapted to their context.
- Recommendations and Insights: The idea here was for AI to provide specific, actionable recommendations based on data analysis. For example, after an event, the AI could suggest three key areas of improvement or strategies to enhance future performance, providing direct value for future planning and execution.
In essence, the workshop participants envisaged a system where generative AI plays a central role in automating data interpretation, visualization, and communication, leading to more efficient planning and decision-making processes.
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