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TBH: The AI-powered Time-saving Interview Scorecard
Updated: Wed, Apr 9, 2025
Adejoke (JK) Adekunle
Hiring teams are constantly pressed to make quality decisions faster while delivering exceptional candidate experiences. Traditional interview scorecards—often static, rigid tools that create more friction than flow—are increasingly showing their limitations in today's dynamic hiring environment. This is the opening that presented an urgent need for TBH, an innovative AI-powered solution transforming how teams collect, analyze, and act on interview feedback.
The Breaking Point: Why Traditional Scorecards Fail Modern Hiring Needs
The familiar scenario plays out in companies everywhere: interviews conclude, but feedback lingers in limbo. Traditional scorecards, typically implemented as spreadsheets or form fields within an ATS, create several critical bottlenecks in the hiring process.
First, there's the timing issue. Most interviewers don't complete scorecards during or immediately after conversations. They return to their daily work, promising to fill out assessments "later"—a nebulous timeframe that often stretches hours into days. With each passing moment, valuable observations and nuanced impressions fade from memory, resulting in vague or generalized feedback that provides little actionable insight.
Second, traditional scorecards force unnatural communication patterns. They require interviewers to translate dynamic, multi-dimensional conversations into rigid rating scales and text boxes. This translation process not only consumes valuable time but also flattens rich observations into standardized formats that often miss crucial context and subtlety.
Third, these systems create isolated information silos. When feedback exists across multiple documents or systems, hiring teams struggle to synthesize a cohesive view of candidates. The resulting fragmentation leads to redundant discussions, delayed decisions, and an inability to identify patterns across multiple interviews.
Modern hiring demands tools designed for how humans naturally communicate and make decisions. Teams need solutions that capture authentic reactions without creating administrative burdens—especially when competing for in-demand talent where speed matters.
The Human-AI Partnership: Enhancing Decision-Making in Hiring
The most effective hiring decisions combine human judgment with data-driven insights. AI doesn't replace human decision-making in the hiring process—it amplifies it by removing friction points that prevent teams from sharing their genuine assessments efficiently.
Human interviewers excel at detecting subtle signals during conversations: the thoughtfulness behind a candidate's problem-solving approach, their cultural alignment, and their communication style. These qualitative observations form the foundation of quality hiring decisions but often get lost in translation when forced through traditional documentation methods.
AI technology, particularly advanced natural language processing, excels at scaling what humans do naturally: communicate through speech. When interviewers can share feedback through their preferred communication medium—their voice—they provide more detailed, nuanced assessments without the cognitive load of writing formal evaluations.
This human-AI partnership creates several distinct advantages:
- Preservation of genuine impressions: Spoken feedback captures interviewers' authentic reactions and observations before they're filtered through the constraints of written formats.
- Comprehensive context: Voice feedback tends to include explanatory context and specific examples that might be omitted in written assessments due to time constraints.
- Emotional intelligence: Vocal inflections and emphasis naturally communicate the weight interviewers place on different aspects of candidate performance—signals often lost in written formats.
- Efficiency without sacrifice: Teams can maintain high standards for feedback quality while dramatically reducing the time investment required from busy interviewers.
The most powerful hiring tools don't attempt to automate human judgment out of the process—they create systems where technology handles information collection and organization while humans focus on meaningful evaluation and decision-making.
The TBH Superpower: Converting Voice to Structured Feedback at Scale
TBH's core innovation lies in its ability to transform natural human communication into structured, actionable hiring intelligence without creating additional work for interview teams. This transformation happens through several interconnected capabilities:
Frictionless Feedback Collection
TBH eliminates the primary barrier to quality feedback: the requirement to write detailed assessments. Interviewers simply speak their observations, which TBH captures immediately after the interview when impressions are freshest. This approach aligns with how people naturally process and share information, resulting in more authentic, detailed evaluations.
The platform offers pre-built, customizable templates that provide just enough structure to guide conversations without constraining natural expression. Interviewers can focus on the candidate rather than navigating complex forms or remembering specific criteria.
Intelligent Processing and Organization
Once feedback is collected, TBH's natural language processing capabilities transform verbal assessments into structured data points. The system:
- Extracts key insights and observations from verbal feedback
- Categorizes comments according to relevant competencies and attributes
- Identifies strength signals and potential concerns
- Recognizes patterns across multiple interviews
- Synthesizes individual perspectives into comprehensive candidate profiles
This processing happens automatically and immediately, ensuring that insights are available to decision-makers without delay. The technology handles the heavy lifting of information organization while preserving the richness of human assessment.
Collaborative Decision Facilitation
TBH transforms isolated feedback into collaborative intelligence. The platform:
- Generates clear hire/no-hire recommendations based on collective feedback
- Highlights areas of consensus and divergence among interviewers
- Provides structured summaries that facilitate efficient decision-making conversations
- Ensures all voices within the hiring team are represented in final decisions
This collaborative approach reduces the common problem of dominant voices overpowering more reserved team members in hiring discussions. When every interviewer's observations are captured with equal fidelity, teams make more balanced decisions.
Candidate Experience Enhancement
Perhaps most importantly, TBH closes the feedback loop with candidates. The platform:
- Generates personalized, constructive feedback for candidates
- Provides clear rationales for hiring decisions
- Delivers insights that help candidates understand their strengths and development areas
- Demonstrates respect for candidates' time investment in the process
This feedback mechanism transforms rejection from a disappointing dead-end into a valuable learning opportunity. Candidates receive specific, actionable insights rather than generic rejection templates—enhancing employer brand even among those who don't receive offers.
Measuring the ROI of AI-powered Interview Feedback Tools
Implementing new hiring technology requires justification through tangible return on investment. TBH delivers measurable improvements across several key performance indicators:
Time Savings and Process Acceleration
The most immediate impact comes from dramatically reduced time-to-feedback. Traditional written scorecards often take 15-30 minutes to complete properly. Voice-based feedback typically requires just 2-5 minutes, representing an 80-90% time savings per interview.
For organizations conducting hundreds or thousands of interviews annually, this efficiency translates into hundreds of reclaimed work hours. A company conducting 1,000 interviews annually might save 250-400 hours of interviewer time—equivalent to 6-10 weeks of full-time work.
Additionally, eliminating feedback delays accelerates overall time-to-hire metrics. When decisions that previously took days or weeks can be made in hours, organizations secure top talent before competitors can extend competing offers.
Quality Improvements in Hiring Decisions
Beyond speed, TBH enhances decision quality through:
- Richer information capture: Voice feedback typically contains 3-4 times more content than written assessments, providing deeper insights for decision-making.
- Reduced recency bias: Immediate feedback collection minimizes the cognitive biases that occur when evaluations are delayed.
- Improved pattern recognition: Structured data analysis identifies consistent themes across multiple interviews that might be missed in manual review.
- Enhanced objectivity: Standardized processing of all feedback ensures consistent evaluation across different interviewers and roles.
Organizations implementing AI-powered feedback systems typically report 15-25% higher confidence in hiring decisions and measurably improved quality-of-hire metrics over time.
Cost Reduction and Resource Optimization
The financial benefits extend beyond time savings:
- Decreased cost-per-hire: Faster processes mean fewer resources dedicated to each hiring decision.
- Reduced opportunity costs: Accelerated hiring minimizes productivity losses from unfilled positions.
- Lower interviewer burnout: Eliminating administrative friction increases interviewer willingness to participate in hiring, distributing the workload more effectively.
- Improved retention through better matches: More comprehensive candidate evaluation leads to better role fit and higher retention rates.
For mid-sized companies, these improvements often translate to $2,000-3,000 in savings per hire when accounting for all direct and indirect costs.
Enhanced Candidate Experience and Employer Brand
Perhaps the most significant long-term ROI comes from candidate experience improvements:
- Feedback provision: 78% of candidates say they want feedback after interviews, but only 25% typically receive it. TBH bridges this gap.
- Reputation enhancement: Candidates who receive thoughtful feedback are 4 times more likely to consider the company for future opportunities.
- Referral increases: Candidates who report positive experiences—even without receiving offers—are 2-3 times more likely to refer others to the company.
These experience factors create compounding returns, reducing future recruiting costs and improving access to passive talent pools.
Transforming Talk into Action: Real-world Impact of TBH
The theoretical benefits of AI-powered interview scorecards manifest in tangible outcomes for organizations across industries. Companies implementing TBH report several consistent patterns:
- Feedback collection rates increase dramatically. Teams that previously struggled to get 50-60% scorecard completion often achieve 90%+ completion rates when using voice-based feedback.
- Decision timelines compress significantly. Hiring processes that previously took weeks can be completed in days, with same-day feedback becoming the norm rather than the exception.
- Interviewer satisfaction improves. Team members report greater willingness to participate in hiring processes when administrative burdens are removed.
- Candidate satisfaction scores rise. Even rejected candidates report positive experiences when they receive thoughtful, personalized feedback.
- Data-driven hiring practices emerge. With structured feedback consistently collected, organizations gain insights into which attributes truly predict success in different roles.
Integration Into Modern Hiring Workflows
TBH doesn't require complete process overhauls to deliver value. The platform integrates seamlessly with existing workflows:
- ATS compatibility: TBH connects with major applicant tracking systems to maintain centralized candidate records.
- Calendar integration: The system works with scheduling tools to automatically prompt feedback after interviews.
- Communication tools: Feedback summaries can be shared through existing team collaboration platforms.
- Mobile accessibility: Interviewers can provide voice feedback from any device, anywhere.
This flexibility ensures that organizations can implement the solution with minimal disruption while maximizing adoption rates among busy interviewers.
Beyond Traditional Alternatives
For organizations considering feedback solutions, TBH offers distinct advantages compared to alternatives like Screenloop, Metaview, and BrightHire. While all address aspects of the interview feedback challenge, TBH's focus on voice-to-structure transformation creates unique efficiency benefits without sacrificing quality.
Organizations seeking deeper comparisons of these tools can find detailed analyses in dedicated comparison articles:
- Screenloop vs TBH
- Metaview vs TBH
- TBH vs BrightHire
The Future of Interview Intelligence
As hiring processes continue evolving toward greater efficiency and effectiveness, tools like TBH represent the leading edge of interview intelligence. The combination of natural human communication with AI-powered analysis creates a system greater than the sum of its parts—preserving human judgment while eliminating unnecessary friction.
Organizations ready to transform their hiring processes can explore how TBH might integrate with their specific workflows and objectives. The resulting improvements in speed, quality, and candidate experience create competitive advantages in increasingly challenging talent markets.
In a world where both time and talent are precious resources, TBH helps organizations make the most of both—turning interview insights into hiring intelligence without the traditional tradeoffs between speed and quality.
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