Essential Work Sample Exercises for Evaluating Self-Service AI Analytics Skills

Self-service AI analytics has revolutionized how organizations leverage data, enabling business users to independently explore, analyze, and derive insights without relying heavily on technical teams. As companies increasingly adopt these tools, the ability to effectively utilize self-service AI analytics has become a crucial skill for business professionals across various departments. However, identifying candidates who truly possess these capabilities can be challenging through traditional interview methods alone.

Work sample exercises provide a window into a candidate's actual abilities with self-service analytics tools, revealing not just their technical proficiency but also their analytical thinking, problem-solving approach, and business acumen. Unlike theoretical questions that may elicit rehearsed responses, practical exercises demonstrate how candidates apply their knowledge in realistic scenarios they would encounter on the job.

The most effective self-service analytics professionals combine technical tool proficiency with strong business context understanding and excellent communication skills. Through carefully designed work samples, hiring managers can observe how candidates navigate analytics interfaces, formulate questions, interpret results, and translate findings into actionable business recommendations.

These exercises also reveal a candidate's approach to learning and adaptation—critical qualities in the rapidly evolving field of AI analytics. By incorporating feedback opportunities within the exercises, employers can assess a candidate's receptiveness to coaching and ability to quickly implement improvements, which are essential traits for success in roles requiring continuous learning.

The following four work sample exercises are designed to comprehensively evaluate candidates for self-service AI analytics roles. Each exercise targets different aspects of the skill set required, from data exploration and visualization to problem definition and insight communication. By implementing these exercises in your hiring process, you'll gain deeper insights into candidates' capabilities and make more informed hiring decisions.

Activity #1: Data Exploration and Insight Generation

This exercise evaluates a candidate's ability to navigate an analytics platform, formulate relevant questions, and extract meaningful insights from data. Self-service analytics users must be able to independently explore datasets, identify patterns, and generate valuable business insights without relying on data scientists or analysts.

Directions for the Company:

• Prepare a sanitized dataset from your organization that contains realistic business data (e.g., sales figures, customer behavior metrics, operational data).
• Provide access to your self-service analytics platform with the dataset pre-loaded.
• Create a brief business context document explaining what the data represents and 2-3 broad business questions the organization is interested in answering.
• Allow 45-60 minutes for this exercise.
• If using your actual platform isn't feasible, consider alternatives like Tableau Public, Power BI Desktop, or Google Data Studio with a prepared dataset.
• Ensure the dataset is complex enough to require thoughtful analysis but not so complex that it requires specialized domain knowledge.

Directions for the Candidate:

• Review the business context document to understand the data and business questions.
• Using the provided analytics platform, explore the dataset to identify trends, patterns, or insights.
• Formulate at least three specific analytical questions that would help address the broader business questions.
• Use the platform's features to analyze the data and develop answers to your questions.
• Prepare to present 3-5 key insights you discovered, explaining both what you found and why it matters from a business perspective.
• Be prepared to explain your analytical approach and how you used the platform's features.

Feedback Mechanism:

• After the candidate presents their insights, provide feedback on one aspect they did well (e.g., effective use of visualization, insightful business interpretation) and one area for improvement (e.g., overlooking an important variable, not fully utilizing platform capabilities).
• Give the candidate 10-15 additional minutes to refine one of their analyses based on the feedback.
• Observe how they incorporate the feedback and whether they can enhance their analysis accordingly.

Activity #2: Dashboard Creation and Visualization

This exercise assesses a candidate's ability to create effective visual representations of data that communicate insights clearly. In self-service analytics roles, professionals must be able to build dashboards that help stakeholders quickly understand complex information and make data-driven decisions.

Directions for the Company:

• Prepare a business scenario with specific KPIs that need to be monitored (e.g., sales performance across regions, customer acquisition metrics, product performance).
• Provide access to a visualization tool (e.g., Tableau, Power BI, Looker) with relevant data pre-loaded.
• Include examples of existing dashboards from your organization to give candidates a sense of your visual style (if applicable).
• Allow 60 minutes for this exercise.
• Ensure the scenario is specific enough to guide the candidate but open-ended enough to allow creativity.
• Consider providing a brief on the intended audience for the dashboard (e.g., executive team, operational managers).

Directions for the Candidate:

• Review the business scenario and KPIs that need to be monitored.
• Using the provided visualization tool, create a dashboard that effectively communicates the status of these KPIs.
• Include at least 3-4 different visualization types that are appropriate for the data.
• Ensure your dashboard tells a coherent story and highlights the most important insights.
• Consider the needs of the intended audience when designing your dashboard.
• Prepare to present your dashboard, explaining your design choices and how stakeholders would use it to make decisions.
• Be ready to demonstrate how users could interact with the dashboard to explore the data further.

Feedback Mechanism:

• After the candidate presents their dashboard, provide feedback on one aspect they did well (e.g., effective visualization choices, intuitive layout) and one area for improvement (e.g., color scheme issues, missing context).
• Give the candidate 15 minutes to refine one aspect of their dashboard based on the feedback.
• Observe how they incorporate the feedback and whether they can enhance the dashboard's effectiveness.

Activity #3: Problem Definition and Analytics Planning

This exercise evaluates a candidate's ability to translate business problems into analytical approaches. Before diving into data, effective self-service analytics users must be able to clearly define problems, identify relevant data sources, and plan their analytical approach.

Directions for the Company:

• Prepare a realistic business challenge document that describes a situation where analytics could provide value (e.g., declining customer retention, unexplained cost increases, opportunity to optimize marketing spend).
• Include information about available data sources in your organization that might be relevant.
• Provide a template for the candidate to complete their plan.
• Allow 45 minutes for this exercise.
• Ensure the business challenge is specific enough to be actionable but complex enough to require thoughtful planning.
• Consider including stakeholder perspectives or constraints that the candidate needs to consider.

Directions for the Candidate:

• Review the business challenge document carefully.
• Define the problem in analytical terms, identifying specific questions that need to be answered.
• Create a plan that outlines:
• Key metrics you would analyze
• Data sources you would need to access
• Analytical approaches you would use (e.g., trend analysis, segmentation, correlation analysis)
• Potential challenges or limitations you anticipate
• How you would validate your findings
• Timeline for completing the analysis
• Explain how your analytical plan connects back to the business challenge and how the insights would inform decision-making.
• Be prepared to discuss alternative approaches you considered and why you chose your specific plan.

Feedback Mechanism:

• After the candidate presents their plan, provide feedback on one aspect they did well (e.g., comprehensive approach, clear connection to business outcomes) and one area for improvement (e.g., overlooking an important data source, not addressing a key stakeholder concern).
• Give the candidate 15 minutes to refine their plan based on the feedback.
• Observe how they incorporate the feedback and whether they can enhance their analytical approach.

Activity #4: Communicating Findings and Recommendations

This exercise assesses a candidate's ability to translate analytical insights into clear, actionable business recommendations. Even the most sophisticated analysis is only valuable if it can be effectively communicated to stakeholders who may not have technical backgrounds.

Directions for the Company:

• Prepare a pre-analyzed dataset with clear findings that could lead to business recommendations.
• Create a brief that includes:
• Business context and the original question that prompted the analysis
• Key findings from the analysis (with supporting visualizations)
• Information about the audience who will receive the recommendations (e.g., executive team, marketing department)
• Provide a template for a recommendation document or presentation.
• Allow 45-60 minutes for this exercise.
• Consider including some ambiguity or competing priorities in the findings to test the candidate's ability to make judgment calls.
• Ensure the scenario is realistic for your organization's decision-making processes.

Directions for the Candidate:

• Review the analysis findings and business context provided.
• Develop 3-5 specific, actionable recommendations based on the analytical insights.
• Create a brief presentation (5-7 slides) or document that:
• Summarizes the key findings in business terms
• Presents your recommendations clearly
• Explains the rationale behind each recommendation
• Addresses potential implementation challenges
• Suggests how to measure the impact of implementing your recommendations
• Tailor your communication to the specified audience, using appropriate language and level of detail.
• Be prepared to deliver your presentation as if speaking to the actual stakeholders.
• Consider potential questions or objections stakeholders might have and be ready to address them.

Feedback Mechanism:

• After the candidate presents their recommendations, provide feedback on one aspect they did well (e.g., clear connection between insights and recommendations, effective storytelling) and one area for improvement (e.g., not considering implementation feasibility, using too much technical jargon).
• Give the candidate 15 minutes to refine one of their recommendations based on the feedback.
• Observe how they incorporate the feedback and whether they can enhance the clarity and impact of their communication.

Frequently Asked Questions

How should we adapt these exercises for candidates with different experience levels?

For junior candidates, consider providing more structured templates and clearer guidelines. You might also use simpler datasets and more straightforward business scenarios. For senior candidates, increase the complexity of the business problems, add constraints or competing priorities, and expect more sophisticated analyses and recommendations.

What if we don't have our self-service analytics tools available for the interview process?

If you can't provide access to your specific tools, consider using widely available alternatives like Tableau Public, Power BI Desktop, Google Data Studio, or even Excel. The key is to test the candidate's analytical thinking and approach rather than specific tool proficiency. Alternatively, you can create a scenario where candidates explain their approach without actually implementing it.

How do we evaluate candidates who use different approaches than we expected?

Focus on the effectiveness of their solution rather than whether they followed a specific approach. Consider: Did they address the core business question? Are their insights valid and valuable? Did they communicate clearly? Different approaches often bring fresh perspectives, which can be valuable to your team. However, if their approach violates best practices or company standards, this should be noted.

Should we provide these exercises before the interview or during it?

Both approaches have merit. Providing exercises beforehand allows candidates to showcase their best work without time pressure but may not reflect their day-to-day capabilities. Conducting exercises during the interview gives you insight into how candidates think and work in real-time. Consider your priorities: depth of analysis (beforehand) or authentic problem-solving process (during).

How can we ensure these exercises don't disadvantage candidates from diverse backgrounds?

Review your exercises to ensure they don't require specific industry knowledge that would disadvantage candidates from different backgrounds. Provide clear context and background information. Consider having diverse team members review the exercises for potential bias. Focus evaluation on analytical approach and problem-solving rather than familiarity with specific business contexts.

What if a candidate struggles with the technical aspects but shows strong analytical thinking?

Consider the specific requirements of your role. If the position requires independent use of self-service tools, technical proficiency is important. However, if the role focuses more on defining problems and interpreting results, with technical support available, you might value analytical thinking more highly. Also consider the candidate's learning potential and your organization's training resources.

Implementing these work sample exercises will significantly enhance your ability to identify candidates who can truly leverage self-service AI analytics to drive business value. By observing candidates as they explore data, create visualizations, plan analytical approaches, and communicate insights, you'll gain a comprehensive understanding of their capabilities that goes far beyond what traditional interviews can reveal.

Remember that the goal of these exercises is not just to assess current skills but also to evaluate a candidate's potential for growth and adaptation in this rapidly evolving field. The feedback components of each exercise provide valuable insights into how candidates respond to coaching and their ability to quickly implement improvements—critical qualities for long-term success.

For more resources to optimize your hiring process, explore Yardstick's suite of AI-powered tools, including our AI Job Descriptions, AI Interview Question Generator, and AI Interview Guide Generator.

Build a complete interview guide for self-service AI analytics skills by signing up for a free Yardstick account