Shifts Solved. Teams Thriving.
Shiftly automates shift scheduling for small hospitality and retail managers, instantly matching staff availability to business needs and compliance rules. Its auto-fill engine creates balanced, conflict-free rosters in seconds, slashing scheduling time by 80% and ensuring teams are reliably covered, preventing no-shows and last-minute chaos for smoother operations.
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Detailed profiles of the target users who would benefit most from this product.
- Age 38, manages single-location café in suburban town - Bachelor’s in Hospitality Management, basic spreadsheet skills - Supervises team of eight part-time baristas - Annual revenue ~$350k with tight profit margins
Growing up in a family-owned diner, he learned hands-on hospitality but lacked formal IT training. After taking over the café five years ago, he inherited manual scheduling routines and juggles them alongside customer service, fueling his desire for a user-friendly scheduling solution.
1. Clear, step-by-step scheduling setup guide 2. One-click shift conflict resolution prompts 3. Mobile-friendly interface for on-the-go edits
1. Overwhelmed by cluttered spreadsheets and manual updates 2. Missed shifts due to communication breakdowns 3. Fear of hidden fees in new software
- Cautious about complex technology changes - Values straightforward, user-friendly interfaces - Seeks efficiency to improve work-life balance - Prefers quick, clear step-by-step guidance
1. Facebook Groups – local business forums 2. WhatsApp – staff coordination chats 3. YouTube – quick tutorial videos 4. Email Newsletter – industry tips 5. TikTok – short business hacks
- 42-year-old owner of suburban fashion boutique - Bachelor’s in Business Administration - Employs 12 part-time sales associates - Annual payroll budget under $120k
After climbing corporate retail ranks, Brenda launched her boutique six years ago. Strained by fluctuating foot traffic and budgets, she built Excel models for shifts, driving her demand for automated profit and satisfaction balancing.
1. Automated labor cost forecasting per shift 2. Real-time budget alerts on scheduling changes 3. Flexible shift adjustments without budget overruns
1. Unexpected overtime spikes blowing tight budgets 2. Manual cost calculations draining administrative hours 3. Staff dissatisfaction from inconsistent hours distribution
- Obsessive about cost-control and efficiency - Demands data-driven decision-making clarity - Balances profit focus with team well-being
1. LinkedIn – professional retail networking 2. Slack – team communication channel 3. Google Sheets – DIY budget templates 4. Retail Newsletters – industry cost analyses 5. Instagram – competitor pricing insights
- 30-year-old nighttime bar manager in urban district - Associate degree in Hospitality - Supervises 15 part-time bartenders and servers - Annual revenue peaks at $400k during weekends
Promoted from bartender at 25, Nancy now runs evening operations at a popular bar. After repeated last-minute absences, she seeks reliable scheduling tech to stabilize late-night staffing.
1. Real-time no-show notifications and replacements 2. Quick shift-swap approvals on mobile 3. Nighttime shift pattern optimization insights
1. Late SMS alerts causing uncontrolled gaps 2. Manual calls chasing missing staff 3. Overtime costs from same-day cover requests
- Thrives under fast-paced nighttime pressure - Values immediate problem-solving responsiveness - Prioritizes staff reliability and morale
1. WhatsApp – instant staff group chats 2. SMS – direct shift alerts 3. Instagram Stories – bar promotions planning 4. Facebook Messenger – backup communication 5. Twitter – industry trend updates
- 35-year-old training coordinator at regional retailer - MBA in Human Resources Management - Manages 20 onboarding and mentoring staff - Annual tool budget ~$10k
Starting as a store associate, Oscar transitioned into HR designing onboarding programs over eight years. Burdened by scattered calendars and manual matching, he champions automated scheduling to accelerate staff ramp-up.
1. Automated mentor-trainee scheduling integration 2. Conflict-free training calendar synchronization 3. Clear visibility into upcoming sessions
1. Overlapping training slots causing delays 2. Manual calendar edits eating into training hours 3. Misaligned mentor availability frustrating new hires
- Passionate about staff development and growth - Seeks seamless integration across calendar apps - Values structured, data-driven onboarding processes
1. Google Calendar – core scheduling hub 2. Microsoft Teams – training coordination chats 3. HR Newsletters – best-practices updates 4. LinkedIn Learning – skill development content 5. Email – formal training invites
- 21-year-old marketing student and sales associate - Pursuing Bachelor’s in Marketing - Works 15–20 hours weekly across three stores - Earnings supplement tuition and living costs
Starting as a campus brand ambassador, Paula advanced to weekend retail shifts. Her variable class schedule demands flexible, real-time shift signing to avoid academic conflicts.
1. Real-time shift availability and signup 2. Instant schedule change notifications 3. Flexible shift swap options
1. Last-minute shifts clashing with classes 2. Slow app updates causing signup errors 3. Unclear swap approval statuses
- Values work-study-life balance expressly - Seeks autonomy in shift selection - Embraces mobile-first scheduling convenience
1. Mobile App – primary scheduling platform 2. SMS – urgent shift alerts 3. WhatsApp – peer shift coordination 4. Instagram – employer updates 5. University Portal – availability notices
Key capabilities that make this product valuable to its target users.
Automatically recommends eligible co-workers for shift trades based on real-time availability, skill sets, and location, reducing search time and ensuring smooth handovers.
Develop a rules engine that automatically evaluates co-worker eligibility for shift swaps by analyzing real-time availability, required skills, certifications, and location. This engine ensures only qualified and available staff are suggested for swaps, reducing manual screening effort and preventing scheduling conflicts.
Implement a service that continuously synchronizes staff availability data with the scheduling system in real time. This ensures that swap suggestions are based on the most up-to-date availability information, minimizing failed swap attempts and no-shows.
Build functionality to match shift requirements with co-worker skills and certifications, ensuring that suggested swap candidates possess necessary qualifications. This prevents skill gaps in shifts and maintains service quality.
Add a geolocation-based filter that prioritizes co-workers working at the same or nearby locations for swap suggestions. This reduces commute issues and ensures team cohesion.
Create an automated notification module that alerts potential swap candidates via email, SMS, or in-app push when a swap request is available. It should handle reminders and allow candidates to accept or decline directly from the notification.
Design an approval workflow that routes accepted swap requests to managers for final approval, or automatically approves swaps that meet predefined rules. This ensures managerial oversight and compliance while minimizing delays.
Leverages AI-driven compliance checks and manager-defined rules to auto-approve valid swap requests within seconds, cutting administrative bottlenecks and accelerating confirmations.
Enable managers to define and configure auto-approval rules based on criteria such as shift duration, role requirements, labor laws, and staffing thresholds. The system should provide an intuitive interface for selecting conditions, setting thresholds, and prioritizing rules. This requirement ensures that swap requests meeting pre-approved conditions are identified for instant approval, reducing manual review and maintaining compliance.
Integrate an AI-driven compliance engine that evaluates incoming swap requests against defined rules, labor regulations, and business policies. The engine must process requests in real time, flag exceptions, and return approval decisions within seconds. This integration is critical for automating approvals, minimizing administrative delays, and ensuring all swaps comply with internal and legal requirements.
Establish performance benchmarks and monitoring for the auto-approval process to guarantee response times under two seconds for standard requests. Include load testing, real-time metrics, and alerts for SLA violations. This requirement is vital for maintaining user satisfaction, preventing scheduling bottlenecks, and ensuring the system scales during peak usage.
Implement a comprehensive audit logging system that captures every auto-approval decision, including request details, rule matches, AI engine assessments, and timestamps. Logs must be queryable, tamper-evident, and exportable for compliance audits and dispute resolution. This ensures transparency, accountability, and traceability for all automated approvals.
Provide a manual override workflow allowing managers to review and reverse auto-approvals when necessary. Include notification alerts for overrides, reason capture, and a dashboard for tracking override decisions. This requirement balances automation with human control, ensuring flexibility in exceptional cases and maintaining operational accuracy.
Integrated in-app messaging for quick communication between staff and managers about proposed shift exchanges, fostering transparency and collaboration in real-time.
Enable real-time messaging within the Shiftly app between staff and managers regarding shift swaps. This requirement ensures messages are delivered instantly through a persistent WebSocket connection, allowing users to communicate without delay. It integrates with the app's UI to provide a seamless chat experience, supports text formatting, and displays online presence indicators. The outcome is improved transparency and faster decision-making for shift exchange requests.
Implement threaded message grouping for each swap request, enabling separate conversations per shift exchange proposal. Each thread is linked to the specific shift ID and shows the swap details at the top. Users can view and comment exclusively on that proposal. Integration with the auto-fill engine allows automatic population of shift information. Outcome: organized discussions, easy tracking of multiple swap negotiations.
Allow users to attach and share files, such as photos, screenshots, or documents, within chat messages. Supports common file types (JPG, PNG, PDF). File uploads are handled via secure storage API and displayed inline in the conversation. This integration helps staff share relevant information, like availability documents, and managers to confirm details visually, improving communication clarity.
Integrate push notification service to alert users of new messages or swap proposals in real-time, even when the app is in the background. Notifications include sender name, message preview, and a deep link to open the specific chat thread. This requirement ensures timely awareness of proposals, reducing response delays and improving overall shift coverage.
Provide search functionality within chat history, allowing users to search keywords, filter by user, date, or shift ID. A real-time search index enables quick retrieval of past swap discussions. This feature supports staff and managers in referencing prior exchanges and ensures transparency and accountability.
Display message delivery and read status indicators for each chat message, using presence and message status flags to update the conversation UI. This requirement ensures senders know when their swap proposals have been delivered and viewed, improving communication clarity.
Identifies backup candidates if an initial swap falls through, instantly suggesting alternate staff to maintain coverage continuity and minimize last-minute gaps.
When a scheduled shift swap fails, the system automatically generates a ranked list of available staff candidates based on real-time availability, required skills, and compliance rules. The suggestions update instantly as staff clock in/out or their availability changes, ensuring shifts are continuously covered without manual searching.
The fallback module filters potential replacement staff by checking current availability, maximum working hours, required certifications, break rules, and local labor laws. Only candidates who meet all criteria are presented, minimizing legal risks and scheduling conflicts.
The system prioritizes fallback suggestions by considering each staff member's shift preferences, past reliability scores, and historical acceptance rates. Higher-ranked candidates are more likely to accept, improving fill rates and staff satisfaction.
Fallback candidates receive automatic notifications via email, SMS, and in-app messages when they are suggested for an open shift. The system tracks delivery and response status, allowing managers to see who has received and acknowledged the request.
Managers can manually select a fallback candidate from the suggestion list and record the override action in an audit log. Each decision is timestamped, linked to the user account, and stored for compliance and review purposes.
Provides managers with insights into swap patterns and frequency across teams, highlighting potential scheduling bottlenecks and helping optimize staffing strategies over time.
A centralized dashboard displaying the total number of shift swaps across teams over selectable time periods. It provides real-time counts, trends, and average swaps per week or month, enabling managers to quickly assess swap activity levels. The dashboard integrates with existing scheduling data to ensure up-to-date insights and supports filtering by team, role, and date range for targeted analysis.
An interactive heatmap visualization that highlights days and time slots with high swap activity. The heatmap uses color intensity to represent swap volume, making it easy to spot peak swap periods. It integrates seamlessly within the Swap Analytics module and allows managers to hover or click on cells for detailed metrics and underlying shift details.
Automated alerting system that notifies managers when swap requests exceed available coverage for specific shifts or roles. Alerts are triggered based on configurable thresholds and can be sent via email or in-app notifications. This feature helps managers proactively address potential coverage gaps before they impact operations.
A flexible reporting tool that allows managers to generate swap analytics for any custom date range. Reports include summary statistics, trend charts, and swap distribution by team or role. The tool supports saving presets for frequent time windows and integrates with the main analytics dashboard for seamless workflow.
Functionality to export swap analytics reports in CSV and PDF formats, with options to include charts and detailed tables. Managers can customize report content, apply branding, and share directly via email or download for distribution. This ensures stakeholders have access to actionable insights in their preferred formats.
A predictive analytics feature that forecasts future swap volumes and potential bottlenecks based on historical swap patterns. It uses machine learning models to surface anticipated swap spikes and provides recommendations for shift adjustments. The insights help managers plan staffing levels more effectively and reduce last-minute swap conflicts.
Visualizes a 24-hour projection of no-show risk in an intuitive timeline, allowing managers to see high-risk periods at a glance and plan coverage accordingly.
Generate a horizontal timeline view spanning the next 24 hours that uses a color-coded heatmap overlay to indicate the probability of no-shows based on historical data, current staffing levels, shift patterns, and real-time changes in availability. The heatmap updates dynamically as new inputs arrive and integrates seamlessly into the main dashboard, enabling managers to identify high-risk periods at a glance and make proactive scheduling adjustments.
Allow managers to click or hover over segments of the risk timeline to reveal detailed metrics, including contributing factors like individual staff reliability scores, shift overlap, peak foot traffic forecasts, and compliance constraints. This drill-down should appear in a tooltip or side panel without navigating away from the timeline, preserving context while delivering deeper insights.
Implement a notification system that triggers alerts when no-show risk crosses configurable thresholds for specific time windows. Alerts can be delivered via in-app banners, email, or SMS, depending on user preferences, and include a direct link to the Risk Timeline view pre-filtered to the relevant time frame, ensuring managers can respond immediately to emerging risks.
Based on the risk timeline and current staff availability, automatically generate and rank a list of qualified replacement or backup staff for high-risk periods. Suggestions should factor in qualifications, availability windows, labor cost implications, and recent workload to maintain fairness. Managers can approve or adjust the suggestions directly from the timeline interface.
Provide an optional overlay on the risk timeline that shows historical no-show patterns for the same day of the week or period in previous weeks or months. This feature helps managers compare projected risk to past events, identify recurring trends, and refine scheduling rules or staffing levels for consistent improvement.
Integrates hyperlocal weather forecasts into no-show predictions, adjusting risk scores based on rain, snow, or extreme heat to help managers anticipate weather-related absences.
Integrate with a reliable hyperlocal weather API to retrieve real-time and forecast data—such as precipitation, temperature, and extreme weather events—for each staff member’s work location. This integration ensures that scheduling algorithms have accurate, location-specific weather inputs to inform no-show risk calculations.
Adjust baseline no-show probability scores by applying configurable weighted modifiers based on forecasted weather factors (e.g., rain increases risk by 10%, snow by 20%, heatwaves by 15%). These modifiers should be adjustable per organizational rules to fine-tune risk sensitivity.
Implement an alert mechanism that triggers notifications when forecasted weather conditions exceed predefined thresholds (e.g., rainfall over 20 mm, snowfall above 5 cm, temperatures below 0 °C or above 35 °C). Alerts should be delivered via the dashboard and optional email or SMS channels.
Continuously monitor the availability, latency, and accuracy of weather data feeds. Generate system warnings or error logs when data freshness falls behind or API errors occur, ensuring that no-show risk calculations remain reliable.
Display weather forecast overlays and no-show risk indicators directly within the scheduling UI. Use icons and color codes to highlight upcoming weather conditions and elevated risk periods on the calendar view and staff profiles.
Automatically identifies and reserves backup staff for shifts with elevated no-show risk, sending instant confirmations to ensure reliable coverage without manual intervention.
Continuously analyze shift histories, attendance records, and contextual factors to identify upcoming shifts with elevated risk of no-shows, integrating seamlessly with the scheduling engine to flag at-risk shifts and trigger backup workflows.
Automatically select and reserve backup staff based on real-time availability, skills match, and compliance rules once a shift is flagged as high-risk, preventing conflicts and ensuring backups are held pending confirmation.
Send immediate SMS and in-app notifications to reserved backup staff with shift details and acceptance prompts, ensuring rapid acknowledgment and reducing uncertainty in coverage.
Sync staff availability from integrated calendar services and internal availability settings in real time to ensure backup reservations reflect up-to-date eligibility and prevent double-booking.
Provide a dashboard displaying no-show risk levels, reserved backups, confirmation statuses, and upcoming shift coverage projections, offering managers a clear overview of staffing resilience.
Sends real-time push, email, or SMS alerts when a shift’s no-show probability crosses a customizable threshold, enabling managers to take proactive steps with one-click backup options.
Enable managers to define custom probability thresholds that trigger alerts. This setting allows adjustment based on business patterns, ensuring notifications are meaningful and aligned with operational risk tolerance. The feature integrates with the probability engine and persists settings per location or team.
Continuously evaluate live shift attendance probabilities and compare them against configured thresholds, ensuring timely detection of high-risk no-shows. The system must process data streams, recalculate probabilities on schedule, and queue alerts without performance degradation.
Support push notifications, email, and SMS channels for alert delivery. Each channel must respect user contact details, deliver messages reliably, and fallback gracefully if a channel fails. Configuration options will let managers select preferred channels.
Provide a single-click interface in the alert that suggests available backup staff and automatically assigns a replacement shift. It must validate availability, compliance rules, and notify the replacement and manager upon assignment.
Offer a dashboard view showing active and historical alerts, their status, and actions taken. Include filtering by date, location, and shift, plus drill-down details on no-show probabilities and backup assignments.
Log all alert events, threshold changes, delivery attempts, and backup assignments with timestamps and user IDs. Ensure logs are stored securely, searchable, and available for compliance and analysis.
Provides historical no-show pattern analysis across days, weeks, and seasons, empowering managers to refine scheduling strategies and reduce future no-shows with data-driven insights.
The system must connect to existing scheduling and attendance databases and automatically ingest historical shift records, attendance logs, and no-show data covering the past 12 months. It should clean, normalize, and store this data in a secure analytics warehouse, running incremental nightly imports and supporting manual backfill for new data sources. This pipeline is essential for ensuring the accuracy and completeness of TrendTracker’s analyses.
Provide an interactive dashboard within the Shiftly UI that displays no-show rates over days of the week, weeks, months, and seasonal periods. It should include heatmaps, line charts, and bar graphs with filtering by location, role, and date range. Tooltips and drill-down capabilities will allow managers to explore specific data points for deeper insights.
Implement a machine learning model that analyzes historical no-show patterns, staff reliability metrics, shift types, and seasonal factors to generate a risk score for each upcoming shift. The risk scores will be integrated into roster suggestions and shift details, enabling managers to proactively assign staff with lower predicted no-show likelihood.
Allow managers to define custom thresholds for predicted no-show risk and configure alerts when those thresholds are exceeded. Alerts can be delivered via in-app notifications and email, with settings scoped by location, department, or team. Managers should be able to modify thresholds and notification channels at any time.
Enable managers to export trend analysis reports and underlying data in CSV and PDF formats. Reports should include selected date ranges, filters, visualization snapshots, and risk summaries. Provide schedule options for automated report delivery via email on a daily, weekly, or monthly cadence.
Instantly visualizes staffing levels against demand across days and shifts using a color-coded grid. Managers can spot overstaffed or understaffed periods at a glance, enabling data-driven schedule adjustments to maintain optimal coverage and control labor expenses.
Implement an interactive heatmap grid that visually represents staffing coverage versus demand across all shifts and days. This feature should use a clear color gradient to indicate overstaffing, optimal staffing, and understaffing zones. Users can hover over each cell to view exact staff count, demand levels, and time frame details. The heatmap must be seamlessly integrated into the scheduling dashboard, allowing managers to access it without navigating away from their primary workflow. By providing an immediate visual summary of coverage gaps and surpluses, this requirement will enable managers to make faster, data-driven scheduling adjustments and maintain efficient labor costs.
Ensure the heatmap reflects live data by automatically updating staffing levels and demand metrics as changes occur in availability, shift assignments, or forecasted demand. The system should push updates to the heatmap within seconds of any data change without requiring a page refresh. This continuous synchronization ensures that managers always see the most accurate representation of coverage needs, preventing decisions based on outdated information and reducing manual refresh effort.
Provide customizable threshold settings for color bands within the heatmap, allowing managers to define what constitutes understaffing, optimal staffing, and overstaffing based on their unique business rules and labor goals. The configuration UI should enable setting minimum and maximum coverage percentages or absolute headcount values for each threshold. These custom thresholds should be saved per location or shift pattern, facilitating granular control over how visual alerts are represented across different contexts.
Integrate zooming and filtering capabilities into the heatmap interface, enabling managers to focus on specific date ranges, days of the week, or shift periods. Users should be able to zoom in to view hourly breakdowns or zoom out for weekly summaries. Filters should allow selection by employee role, location, or demand category. These controls must be intuitive and performant, ensuring smooth navigation even with large datasets, thereby empowering managers to conduct detailed analysis quickly.
Enable exporting of the heatmap view and underlying data to common formats such as PDF and CSV. The export function should capture the current visualization settings, including applied filters, zoom level, and custom thresholds. Additionally, provide a shareable link feature that grants view-only access to stakeholders without requiring a user account. This functionality will facilitate collaboration and reporting, allowing managers to share coverage insights with teams and higher management efficiently.
Provides a real-time gauge of labor costs versus budget targets, with dynamic projections of expected spend by shift. Users monitor cost fluctuations directly on the dashboard and take immediate action—such as reallocating hours or trimming shifts—to prevent overspending.
Compute labor costs for each shift instantly by aggregating employee hourly rates, scheduled hours, and overtime rules. Integrates seamlessly with the scheduling module to deliver accurate, up-to-the-second cost figures, enabling managers to make informed staffing decisions and avoid budget overruns.
Monitor cumulative labor spend against predefined budget thresholds and trigger configurable alerts when projected costs approach or exceed limits. Enables proactive decision-making by notifying managers via dashboard notifications and email so they can adjust shifts or reallocate resources before overspending occurs.
Display detailed cost breakdowns per shift, including base wages, overtime, taxes, and benefits. Visual components like bar charts and tables provide clarity on cost drivers, helping managers identify high-cost shifts and optimize staffing configurations for maximum efficiency.
Generate dynamic projections of expected labor spend for the upcoming week or month based on current forecasted schedules. Interactive charting tools let users explore different scheduling scenarios and immediately view how adjustments impact overall labor costs.
Provide actionable suggestions to reduce labor spend, such as reallocating hours to lower-cost employees, trimming non-critical shifts, or adjusting break schedules. Recommendations leverage historical data and compliance rules to balance cost savings with coverage requirements and staff satisfaction.
Leverages historical patterns and upcoming events to predict staffing needs up to two weeks in advance. The AI-driven forecast recommends proactive shift adjustments to preempt shortages or surpluses, reducing last-minute scheduling changes by up to 50%.
The system must ingest and normalize at least two years of past shift data, including staff schedules, coverage levels, business performance metrics, and no-show records, to build a robust data foundation for accurate forecasting. This integration should handle data from existing scheduling modules, CSV imports, and third-party HR systems, ensuring data consistency, handling missing values, and enabling efficient querying.
Forecast Flow must integrate with external calendars (Google Calendar, Outlook) and event management systems to import upcoming events (holidays, promotions, local events) automatically. This integration should support real-time synchronization, allow mapping event types to staffing impact levels, and provide an interface to manage event data within Shiftly.
Implement an AI-driven forecasting engine that leverages time series models, machine learning algorithms, and business rules to predict staffing requirements up to two weeks in advance. The engine should consider historical patterns, upcoming events, staff availability, and compliance constraints, generating shift-level demand forecasts per role and location. Output should be available via API and internal services.
Provide proactive recommendations for shift adjustments when the forecast predicts surpluses or shortages. The system should generate suggestions such as adding shifts, reassigning staff between locations, overtime proposals, or schedule swaps, along with estimated impact and compliance checks. Users should be able to review, accept, modify, or reject suggestions.
Design a dashboard that visualizes forecasted staffing demand and capacity over time. It should display key metrics (predicted coverage gaps, surpluses), interactive charts for different roles and locations, trend lines, and event overlays. The dashboard should allow filters for date ranges and export of charts and data to CSV or PDF.
Enables managers to filter and segment staffing and cost data by location, role, or time frame. This granular analysis uncovers specific inefficiencies—like underutilized roles or peak demand gaps—empowering targeted scheduling strategies that boost productivity.
Provide managers with an intuitive interface to configure filters by location, role, and time frame. The UI integrates seamlessly with the core scheduling dashboard, allowing users to select multiple parameters, save custom filter sets for quick access, and reset to defaults. This feature enhances usability by streamlining the process of narrowing down large datasets to the most relevant information, improving decision-making efficiency.
Enable the system to segment staffing and cost data by individual roles. The backend aggregates and breaks down metrics per role across selected filters, providing both shift-level and cumulative views. This segmentation highlights underutilized positions and cost imbalances, guiding targeted scheduling adjustments and resource allocation.
Implement flexible time frame options including preset ranges (daily, weekly, monthly), custom date pickers, and peak hour intervals. The selector interfaces with all filters and visualizations, dynamically updating results. This flexibility supports detailed analysis of staffing trends over various periods, enabling more strategic scheduling decisions.
Create an interactive heatmap to visualize staffing demand gaps and peaks across locations and time slots. The visualization overlays intensity gradients on a time-location matrix, with hover and click interactions revealing exact metrics. This graphical representation quickly highlights coverage shortfalls and overstaffing, driving actionable scheduling insights.
Allow exporting of filtered and segmented staffing and cost analyses in CSV and PDF formats. Exports include both tabular data and embedded charts, with customizable headers and footers. This feature supports sharing insights with team members and stakeholders, facilitating collaboration and record-keeping.
Allows custom alert thresholds for staffing anomalies and budget variances. When thresholds are crossed—such as a 10% labor overspend or an unfilled role—managers receive real-time notifications with one-click recommendations to re-balance schedules and mitigate risks instantly.
Enable managers to define and adjust custom alert thresholds for staffing anomalies and budget variances. This includes setting percentage overspend limits, minimum staffing levels per role, and time-based triggers for unfilled shifts. The system should validate inputs, provide default recommendations, and save configurations per location or department. Integration with the scheduling engine ensures thresholds are evaluated in real-time against live roster data, empowering managers with precise control over alert criteria.
Implement a real-time notification system that monitors roster data against defined thresholds. When a threshold is crossed, the system pushes notifications via email, SMS, or in-app alerts. Notifications should be formatted clearly, include relevant metrics (e.g., current overspend percentage), and provide direct links back to the schedule overview. Ensure reliable delivery with retry logic and support user preferences for notification channels and frequency.
Provide managers with one-click recommendations to rebalance the schedule when anomalies occur. Upon threshold breach, the system analyzes staff availability, skill sets, and compliance rules to suggest optimized shift swaps, additional hires, or reassignments. Recommendations should appear in a modal window with options to accept, modify, or reject, updating the roster instantly upon confirmation.
Expand the dashboard with visual indicators of current staffing and budget status relative to set thresholds. Use color-coded gauges, trend lines, and alert badges to highlight approaching or breached thresholds. Interactive elements should allow managers to drill down into specific roles, dates, or cost centers. This visual context helps managers proactively monitor risks and understand the impact of alerts at a glance.
Maintain a detailed audit log of all alert-related events, including threshold definitions changes, triggered alerts, notification deliveries, and manager actions on recommendations. Each log entry should include timestamps, user IDs, and before/after states. Provide a searchable, filterable interface for administrators to review alert histories and ensure accountability and compliance.
Automatically pairs new hires with the most suitable mentors by analyzing availability, skill sets, and workload. Ensures balanced mentor assignments, prevents overbooking, and accelerates relationship-building for a seamless onboarding experience.
Implement an algorithm that evaluates potential mentor-mentee pairs by analyzing profiles, skills, experience, and interests to generate a compatibility score for each match. This ensures more effective relationships, accelerates onboarding, and increases participant satisfaction by pairing individuals with the highest alignment.
Integrate with both mentor and mentee calendar systems to automatically retrieve and synchronize availability windows. This prevents scheduling conflicts, reduces manual coordination, and ensures that mentorship sessions are set up at mutually convenient times.
Monitor mentors’ current assignments and workload in real time, enforcing configurable capacity limits to ensure equitable distribution of mentees. This prevents mentor overbooking, maintains quality of guidance, and balances support across the team.
Analyze new hire profiles against role requirements to identify individual skill gaps. Recommend mentors with complementary expertise to address these gaps, optimizing learning outcomes and ensuring focused, goal-oriented onboarding.
Generate notifications and automated reassignment suggestions when a mentor’s availability changes or workload exceeds thresholds. This maintains continuous support for mentees, minimizes disruptions, and ensures consistent mentor engagement.
Provides a real-time, interactive calendar that visualizes training sessions, mentor availability, and potential conflicts. Enables managers to adjust schedules on the fly, ensuring conflict-free rosters and transparent planning.
The roster calendar automatically updates in real time whenever staff availability, shift assignments, training sessions, or conflicts change, eliminating the need for manual refresh. By integrating with the backend scheduling engine and data streams, it ensures managers always see the most current staffing information and can make timely decisions based on live data.
Scheduling conflicts such as overlapping shifts, unavailable staff, or missing certifications are flagged directly on the calendar with color-coded indicators and informative tooltips. The system pulls conflict data from the business rules engine, helping managers quickly identify, understand, and resolve issues without navigating away from the roster view.
Managers can adjust shift assignments by dragging and dropping shift blocks or staff availability directly within the calendar. Changes such as moving, extending, or swapping shifts are instantly validated by the system to prevent conflicts, with support for undo/redo actions to streamline on-the-fly adjustments.
Training sessions appear as overlay elements on the roster calendar, blocking staff from shift assignments during session times. Managers can toggle the overlay visibility and click on session elements to view details such as instructor, duration, and required attendance, ensuring training commitments are factored into scheduling.
A filter option allows managers to display only mentor or supervisor availability on the calendar, based on skills, certifications, and scheduled availability. This ensures critical roles are staffed appropriately and helps managers quickly identify qualified personnel for supervisory shifts.
The roster view interface is fully responsive on mobile devices, adapting its layout and controls for smaller screens. Touch-friendly interactions enable managers to view, drag and drop shifts, and resolve conflicts on the go, ensuring schedule management is accessible from any device.
Aligns training modules with mentors’ areas of expertise and new hires’ learning goals. Automatically recommends optimal time slots for each session, guaranteeing targeted skill development and reducing redundant scheduling efforts.
Implement a system to capture and categorize mentors’ skill areas and proficiency levels, creating a searchable expertise database. This requirement ensures accurate matching between training modules and mentors, streamlining the assignment of sessions to the most qualified staff. It integrates with the user profile subsystem and supports future expansions for dynamic expertise updates.
Develop an interface to import, categorize, and update training modules within Shiftly, including metadata such as duration, prerequisites, and learning objectives. This requirement ensures that all available modules are centrally stored and easily accessible for scheduling, enhancing content management and reducing manual data entry.
Build an engine that automatically recommends optimal time slots for mentor-led sessions by considering mentor availability, trainee learning goals, and business staffing requirements. The scheduler should generate a conflict-free timetable and allow manual adjustments. This functionality reduces redundant scheduling efforts and ensures targeted skill development.
Implement real-time checks to identify and flag scheduling conflicts such as overlapping sessions, mentor overbooking, or business coverage gaps. Provide actionable suggestions to resolve conflicts, including alternative mentors or time slots. This requirement maintains schedule integrity and prevents resource clashes.
Design a user-friendly dashboard for trainees that displays upcoming sessions, completed modules, mentor profiles, and personalized recommendations based on learning goals. The dashboard enhances engagement by providing visibility into progress and next steps, and integrates with notification services for reminders.
Monitors onboarding milestones and training completion in real time, sending automated alerts and suggestions for next steps. Keeps managers and mentors informed, reduces delays, and ensures consistent onboarding momentum.
This requirement defines a dynamic dashboard that visualizes each new hire’s onboarding milestones and training completion status in real time. It integrates seamlessly with the core Shiftly system to pull live data on progress, highlighting completed, pending, and overdue tasks. By presenting this information in an intuitive interface, managers and mentors can quickly identify bottlenecks, ensure consistent momentum in the onboarding process, and intervene proactively to address delays.
This requirement specifies the development of a rules-based alerting engine that triggers automated notifications when onboarding milestones are approaching deadlines, missed, or delayed. Alerts can be delivered via email, in-app notifications, or SMS based on user preferences. The engine should allow configurable thresholds and escalation rules to ensure timely follow-up and prevent onboarding delays.
This requirement involves implementing a recommendation module that analyzes trainee progress and performance data to suggest context-aware next steps. Suggestions may include specific training modules, one-on-one mentoring sessions, or peer-shadowing opportunities. The module should learn from historical data to improve recommendation accuracy and help mentors guide new hires effectively.
This requirement covers the creation of analytic reports and visualizations that provide insights into overall onboarding efficiency. Key metrics include average time to complete milestones, task completion rates, and comparative performance across cohorts. The analytics component should support filtering by role, location, and time frame, enabling managers to identify process improvements and ensure consistency.
This requirement enables administrators to configure and customize onboarding workflows by defining milestones, associated tasks, durations, compliance checkpoints, and assignment rules. The interface should support drag-and-drop workflow design, template creation, and version control. Customizable workflows ensure that onboarding aligns with varied roles, regulatory requirements, and organizational best practices.
Integrates in-app feedback collection after each training session, instantly adjusting future schedules based on satisfaction and performance metrics. Promotes continuous improvement and tailors the onboarding journey to individual needs.
The system must automatically deliver a feedback solicitation to staff immediately upon completion of each training session, ensuring timing relevance and maximizing response rates. It involves scheduling prompt notifications in-app, via email, or SMS, integrating with session completion events, and supporting customizable timing and frequency settings.
Design and implement a user-friendly feedback form within the app that guides staff through rating scales, open-text responses, and performance metrics. The form should adapt to different training types, support multi-language, validate input, and minimize friction to encourage high participation.
Build a robust backend capable of storing, indexing, and retrieving feedback data. It should securely persist satisfaction scores, performance metrics, timestamps, and metadata. The system must support data querying, history tracking, and integration with existing databases, while ensuring compliance with data protection regulations.
Enhance the auto-fill scheduling engine to incorporate feedback metrics, adjusting future shift assignments or training sessions based on individual satisfaction and performance. This includes defining weighting rules, updating algorithms, and validating schedule changes against compliance and availability constraints.
Develop an analytics dashboard for managers that visualizes aggregated feedback trends, performance distributions, and satisfaction levels. The dashboard should offer filters by date, team, training type, exportable reports, and actionable insights to guide training improvements.
Provides a real-time sandbox where managers can tweak shift times, roles, and staffing levels before publishing. Instantly displays projected labor costs for each adjustment, empowering data-driven decisions to stay within budget without trial and error.
Ensure the What-If Simulator ingests and synchronizes all scheduling data (staff availability, existing shifts, compliance rules, and labor budgets) in real time, eliminating data latency. This requirement guarantees that any adjustments made within the sandbox are based on the most current information, preventing conflicts and ensuring accuracy when projecting staffing levels and costs.
Implement an engine that recalculates projected labor costs instantly with every modification to shift times, roles, or staffing levels. The module should account for pay rates, overtime rules, and budget constraints, displaying the updated cost immediately to support data-driven decision making without trial-and-error.
Provide a drag-and-drop timeline interface within the simulator to adjust shift start/end times, roles, and headcounts visually. The editor should offer snap-to-interval guidance, real-time conflict alerts, and contextual tooltips to streamline scenario modeling and minimize manual input errors.
Enable users to create, name, save, load, and compare multiple What-If scenarios. Include versioning, side-by-side comparison views, and the ability to revert to previous states. This requirement facilitates iterative analysis and collaborative review before finalizing schedules.
Implement permission controls to define who can view, edit, or publish What-If scenarios. Integrate with existing user roles in Shiftly to ensure that sensitive scheduling data remains secure and that changes are auditable.
Automatically flags potential overtime hours in draft schedules and suggests alternative shift assignments or shorter blocks. Reduces costly premium pay by reallocating hours to underutilized staff while ensuring full coverage.
Automatically analyze draft schedules to flag shifts where assigned hours exceed an employee’s contracted limit or trigger overtime pay, ensuring managers are alerted to potential premium pay liabilities before finalizing schedules.
Provide context-aware recommendations for reassigning flagged overtime hours to qualified staff members with available capacity, presenting options ranked by minimal impact on coverage and labor costs.
Continuously monitor staff schedules and availability to identify employees with slack in their work hours, highlighting those eligible for additional shifts to balance workloads and reduce overtime.
Enable managers to initiate and approve shift swaps directly from the scheduler interface, facilitating quick reassignment of hours between employees while maintaining compliance with role qualifications and availability constraints.
Run a final validation on adjusted schedules to confirm that all time slots remain fully covered after overtime optimizations, alerting managers to any gaps or conflicts that require manual resolution.
Analyzes availability and cost rates to propose shift swap combinations that lower total labor spend. Maintains staffing levels and skill requirements by recommending moves that yield the greatest budget savings.
Integrate staff cost rate data from payroll systems and timesheets, including base pay, overtime rates, and allowances. Ensure data is normalized, validated, and updated in real time via APIs or manual entry, with error handling and reconciliation logs. Provides accurate cost inputs for swap calculations.
Develop an algorithm that analyzes staff availability, qualifications, and individual cost rates to identify swap combinations that maintain required coverage and minimize total labor spend. The engine must honor compliance rules, skill requirements, and run efficiently for typical roster sizes.
Create an interface that displays recommended shift swaps with clear indicators of potential cost savings, skill matches, and compliance status. Include filtering and sorting by savings amount, and provide one-click apply and rollback features for seamless decision-making.
Build a dashboard showing projected labor spend before and after applying swaps, total and per-department savings, and historical trends. Enable interactive visualizations for tracking cost reduction over time and identifying high-impact scheduling patterns.
Implement functionality that allows managers to review, edit, or reject suggested swaps with configurable approval workflows for high-impact changes. Capture override reasons and require secondary approvals for exceptions, ensuring accountability and control.
Offers a one-click solution to apply approved budget-friendly adjustments—such as trimming or shifting hours—across the entire schedule. Ensures final rosters align with budget targets instantly, eliminating manual tweaks.
Enable managers to define and adjust budget constraints—such as total labor cost, maximum hours per employee, and department-specific spending limits—within the Auto-Balance feature. This configuration ensures that the auto-generated schedule adheres to financial targets and staffing policies. Managers can save multiple budget profiles, apply them to any schedule, and receive real-time validation against compliance rules and alerts for potential breaches.
Provide a single-action control that triggers the Auto-Balance engine to apply approved adjustments across the entire schedule. Upon activation, the system recalculates staff hours—trimming, shifting, or reassigning shifts as needed—to meet the defined budget profile instantly. The feature displays progress indicators, notifications upon completion, and logs of each change made for transparency.
Offer an interactive preview panel that displays before-and-after budget metrics—such as total labor cost, variance from target, and individual department spend—prior to committing Auto-Balance changes. The preview highlights proposed adjustments on the schedule grid, enabling managers to approve or tweak the suggestions before finalizing the roster, reducing the risk of unexpected budget overruns.
Implement a set of configurable rules that resolve scheduling conflicts—such as minimum shift lengths, required rest periods, and skill coverage—during the Auto-Balance process. The system evaluates each proposed adjustment against these rules, automatically prioritizes higher-importance constraints, and provides warnings or alternative suggestions if a conflict cannot be fully resolved within budget.
Maintain a detailed audit log of all changes made by the Auto-Balance feature, including timestamps, affected shifts, original and adjusted hours, and the user who initiated the process. Provide a rollback function that allows managers to revert the schedule to its previous state in one action, ensuring accountability and enabling quick recovery from unintended adjustments.
Delivers a concise visual overview of draft schedule expenses against budget thresholds, broken down by location, role, and time period. Highlights hotspots and underutilization at a glance, so managers can quickly spot and address budget variances.
The system must aggregate draft schedule expense data including wages, hours worked, breaks, overtime, and benefits across all scheduled shifts in real time. This involves pulling data from the scheduling engine, applying pay rates, calculating total costs per shift, and updating expense totals whenever changes occur. Accurate and up-to-date expense information serves as the foundation for the Budget Snapshot feature and integrates with both the scheduling and payroll modules to ensure consistency across the product.
Provide a concise, interactive dashboard that displays total draft schedule expenses against predefined budget thresholds. The dashboard will feature visual elements such as bar graphs, heatmaps, and trend lines to represent costs by location, role, and time period. Users can quickly identify overspending hotspots, underutilized slots, and budget variances at a glance. This requirement integrates with the data aggregation engine to ensure visualizations reflect live data.
Implement dynamic alerts that notify managers when draft schedule expenses approach or exceed budget thresholds. Alerts will appear as visual cues within the dashboard, in-app notifications, and optional email notifications. Managers can customize threshold levels for each location and role, enabling proactive adjustments to staffing before overspending occurs. This requirement ties into both the aggregation engine and the dashboard UI.
Enable users to filter Budget Snapshot data by location, role, shift time period, and custom date ranges. Provide drill-down capabilities to view detailed cost breakdowns at the individual shift level. Filters should be intuitive, and visualizations should update instantly to reflect selected criteria. This requirement enhances data exploration and integrates directly with the dashboard’s data query layer.
Allow users to export Budget Snapshot data and visualizations into PDF and CSV formats. Provide customization options for report content and layout, and enable sharing via email directly from the application. This functionality leverages the dashboard’s data structures and ensures managers can easily distribute budget insights to stakeholders.
Innovative concepts that could enhance this product's value proposition.
Enables staff to instantly propose and confirm shift trades, auto-validating compliance and availability to slash administrative approvals by 70%.
Predicts likely no-shows 24 hours ahead using attendance history and weather trends, alerting managers to arrange backups and avoid coverage gaps.
Visualizes real-time staffing trends and labor costs in a dynamic dashboard, highlighting overstaffed or understaffed periods to optimize budgets instantly.
Automatically syncs new hires with mentors’ schedules, creating conflict-free training rosters that cut onboarding time by 40%.
Sends real-time alerts when draft schedules exceed labor budgets, proposing cost-saving shift adjustments before publishing.
Imagined press coverage for this groundbreaking product concept.
Imagined Press Article
City, State – 2025-06-14 – Shiftly, the leading AI-driven shift scheduling platform for small hospitality and retail managers, today announced the launch of its highly anticipated What-If Simulator feature. This innovative tool enables managers to model multiple scheduling scenarios in real time, assess labor costs, and make data-driven roster adjustments with confidence—eliminating costly guesswork and ensuring schedules remain on budget. Introduction In environments where razor-thin margins and unpredictable demand are daily realities, scheduling decisions carry significant financial risks. Recognizing this challenge, Shiftly’s What-If Simulator provides an intuitive sandbox where managers can experiment with shift assignments, roles, and hours before officially publishing rosters. The result: optimized coverage, balanced labor costs, and greater peace of mind. Feature Overview What-If Simulator delivers a dynamic, interactive interface that instantly forecasts total labor spend based on proposed schedule modifications. Managers can: • Adjust shift start and end times with drag-and-drop accuracy • Reassign roles or swap team members to address skill requirements • View projected overtime and labor-cost variance by shift • Compare multiple scenarios side-by-side • Lock in preferred configurations with a single click By visualizing the financial impact of scheduling choices up front, What-If Simulator empowers users to avoid budget overruns and redundant manual calculations – all within the same platform they already trust for automated shift fills. Key Benefits Reduce Budget Surprises Eliminate fragmented spreadsheet work and last-minute corrections. What-If Simulator projects labor expenses in real time, alerting managers before they exceed budget thresholds. Accelerate Decision-Making Draft, compare, and finalize rosters rapidly. The instant feedback loop lets managers iterate freely, driving schedules to optimal coverage in minutes rather than hours. Enhance Collaboration Share scenario snapshots with regional leads or finance teams. Transparent visuals and cost breakdowns foster cross-departmental buy-in and swift approvals. Drain the Guesswork Managers no longer need to estimate overtime risk or manually tally labor spend. The system flags potential issues and offers corrective suggestions, boosting confidence in published schedules. Customer Quote "What-If Simulator is a game changer for our crews," said Maria Castillo, Owner and Manager of The Coastal Café in Santa Monica. "We used to juggle spreadsheets and hope we didn’t overspend on labor. Now, we can fine-tune shifts in real time and see exactly how each tweak affects our bottom line. It’s streamlined our entire planning process.” Industry Impact According to recent studies, small retailers and hospitality venues spend an average of 6 hours per week on manual schedule adjustments, costing thousands in hidden labor overhead. By automating scenario analysis, What-If Simulator has the potential to save businesses up to 50% of the time currently allocated to roster planning and reduce unplanned labor expenses by 15%. Availability and Pricing What-If Simulator is included in Shiftly’s Advanced and Enterprise plans at no additional cost. Existing subscribers can access the feature immediately via the web dashboard or mobile app. Shiftly is also offering a 30-day free trial for new users who sign up at www.shiftly.com/free-trial by July 31, 2025. About Shiftly Shiftly is the #1 AI-powered shift scheduling solution for small hospitality and retail managers. With its patented auto-fill engine, compliance safeguards, and data-driven insights, Shiftly reduces scheduling time by up to 80%, prevents coverage gaps, and slashes labor costs. Headquartered in City, State, Shiftly serves thousands of stores, restaurants, and bars across North America. Media Contact Emma Rodriguez Head of Public Relations, Shiftly press@shiftly.com (555) 123-4567 ###
Imagined Press Article
City, State – 2025-06-14 – Shiftly, the industry’s leading workforce management platform, today launched two breakthrough no-show mitigation features—WeatherGuard and Backup Beacon. These innovations equip small hospitality and retail managers with predictive insights and instant backup staffing to avoid last-minute coverage gaps driven by weather, unexpected absences, or on-site demands. Background No-shows and last-minute call-outs cost businesses an estimated $3,600 per store each month, according to the Retail Scheduling Institute. Adverse weather events and unpredictable staff availability only compound these losses. To address the challenge head-on, Shiftly’s new WeatherGuard and Backup Beacon features harness AI and real-time data to proactively forecast risks and secure alternative coverage. WeatherGuard: Hyperlocal Forecasting Meets No-Show Prediction WeatherGuard ingests minute-by-minute weather data for each scheduled shift location—rain, snow, extreme heat, or severe storms—and recalibrates no-show risk scores accordingly. Managers can now: • View a 48-hour weather-adjusted risk timeline • Receive alerts when shifts cross predefined risk thresholds • Prioritize coverage for high-risk blocks preemptively “During sudden storms or heatwaves, we’d often be left scrambling for substitutes,” said Omar Nguyen, Manager at Lakeside Grill. “WeatherGuard’s live updates let us know ten hours in advance which shifts need immediate attention. That lead time is priceless.” Backup Beacon: Instant Backup Staff Reservations The new Backup Beacon feature automatically identifies and secures confirmed backup staff the moment a shift’s risk score breaches the manager’s set threshold. Key benefits include: • One-click backup confirmations via push notifications • Tiered backup lists based on skill sets and location proximity • Automated compliance checks to ensure legal working hours “Our store’s no-show rate dropped by 60% within the first month of testing Backup Beacon,” reported Laura Kim, Regional Supervisor for Urban Wear Co. “Knowing that a replacement is already on standby removes so much stress and ensures our customers always find a fully staffed location.” Integrated Workflow WeatherGuard and Backup Beacon seamlessly integrate into Shiftly’s existing Risk Timeline and Fallback Finder views. Managers can toggle weather overlays, track backup confirmations, and see coverage adjustments—all from a unified dashboard or mobile app. Quantifiable Impact Early adopters of the combined WeatherGuard and Backup Beacon toolkit have reported: • 40% reduction in emergency call-outs • 25% decrease in overtime spend • 85% improvement in shift coverage reliability Pricing and Access WeatherGuard and Backup Beacon are bundled in Shiftly’s Pro and Enterprise plans. Current subscribers can enable both features via their dashboard settings. Interested businesses can schedule a personalized demo or start a free 14-day trial at www.shiftly.com/weather-guard. About Shiftly Shiftly’s mission is to simplify workforce management for small hospitality and retail operators. By combining an intelligent auto-fill engine, robust compliance safeguards, and real-time analytics, Shiftly slashes scheduling time by 80% and prevents coverage chaos. The company is headquartered in City, State, and serves over 5,000 locations across North America. Media Contact David Patel Director of Communications, Shiftly media@shiftly.com (555) 987-6543 ###
Imagined Press Article
City, State – 2025-06-14 – Shiftly, the premier AI-powered scheduling solution for small hospitality and retail managers, today unveiled significant enhancements to its Forecast Flow feature. The upgraded Forecast Flow now delivers reliable two-week demand predictions that empower managers to proactively align staff coverage with anticipated customer footfall and events—reducing last-minute adjustments by up to 50%. Scheduling Challenges in Dynamic Environments Hospitality venues and retail outlets grapple with highly variable demand driven by seasonal peaks, local events, and emerging trends. Manual forecasting often leads to either overstaffing or critical coverage gaps. To remedy this, Shiftly’s Forecast Flow leverages machine learning to analyze historical sales, foot traffic data, and external calendars, offering an intelligent staffing blueprint up to 14 days in advance. Enhanced Forecast Flow Capabilities The latest version of Forecast Flow introduces: 1. Event-Aware Predictions: Auto-import of public holiday, concert, and festival schedules to fine-tune staffing needs around local happenings 2. Granular Role Breakdown: Shift-level forecasts by position (e.g., barista, server, cashier) to ensure the right skill mix 3. Confidence Intervals: Visual indicators showing prediction certainty levels, enabling managers to plan contingency coverage when needed 4. Seamless Roster Integration: One-click application of recommended staffing levels into draft schedules, with real-time labor cost impact analysis Quote from Product Lead “By combining demand forecasting with real scheduling actions, Forecast Flow bridges the gap between insight and execution,” said Priya Shah, VP of Product at Shiftly. “Managers can now trust not only what they’ll need in two weeks, but also deploy rosters instantly—ensuring their teams are ready when customers arrive.” Customer Success Stories • Riverside Boutique, Portland, OR: Utilized Forecast Flow to scale staffing ahead of a citywide street fair, resulting in a 30% increase in sales without adding excess labor spend. • Seaside Bistro, Miami, FL: Reduced last-minute shift changes by 60% during spring break by proactively adjusting schedules based on student tourism forecasts. Operational Advantages Proactive staffing based on reliable data confers multiple benefits: • Cost Efficiency: Up to 20% reduction in unnecessary labor hours • Team Morale: Fewer surprise schedule changes and more predictable shifts • Customer Experience: Consistently optimal coverage improves service speed and satisfaction Access and Pricing Forecast Flow enhancements are available now to all subscribers on Shiftly’s Growth, Pro, and Enterprise plans. New users can test the feature during a free 30-day trial by visiting www.shiftly.com/forecast-flow. About Shiftly Shiftly empowers small hospitality and retail operators with AI-driven scheduling, compliance, and analytics tools. The platform’s patented auto-fill engine builds balanced, conflict-free rosters in seconds while dynamic insights ensure cost control and coverage reliability. Serving over 5,000 businesses across North America, Shiftly is headquartered in City, State. Media Contact Aisha Thompson PR Manager, Shiftly press@shiftly.com (555) 222-3333 ###
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