Predictive scheduling: Benefits, best practices, and business impact
The rise of the distributed workforce has added new challenges to project scheduling. You may manage employees in San Francisco and Seattle alongside workers in New York City and Chicago on the same project. Project managers need a tool that accounts for varied time zones, resource availability, and worker needs to create a realistic and flexible schedule that produces deliverables on time and within budget.
Thankfully, predictive scheduling solutions can help. If you’ve worked in the retail, hospitality, or food service industry, you’ve likely already encountered predictive scheduling. These systems review variables and available data to create a work schedule that achieves stakeholders’ goals and provides advanced notice of employee availability.
What is predictive scheduling?
Predictive scheduling applications use advanced algorithms to review historical data and ongoing trends to predict staffing needs for a specific period or project. These insights allow managers to adjust staffing levels to meet anticipated demand, improving resource utilization and efficiency.
Compliance with predictive scheduling laws and fair workweek ordinances isn’t the only reason to use methodologies. Project managers can use this approach to create dynamic project schedules with flexible start and delivery dates, then adjust milestones and deadlines based on actual progress and resource availability.
Predictive scheduling is especially effective for project teams operating under an framework that demands adaptable timelines based on resource constraints, availability, and dependent tasks.
Predictive scheduling vs. pick-a-date scheduling
Predictive scheduling relies on an analysis of data and trends to establish a project’s start and end dates. The system’s inherent flexibility allows the project manager to build in time buffers, accommodating schedule changes and dependent task timelines without impacting the ultimate delivery date.
Project managers relying on pick-a-date or fixed-date scheduling set firm deadlines and base their timelines on . These are often generated without evaluating historical project data. Without considering dependencies, there’s no clear way to determine how delays will alter milestones and deadlines.
When to use predictive scheduling vs. other scheduling methods
Project managers generally use pick-a-date scheduling when clients or stakeholders have hard and fast due dates for delivery. In this case, it’s up to the project manager to work within these constraints to deliver the project on time.
Predictive scheduling typically occurs during portfolio planning. Initially, the schedule predicts delivery in three- to six-month increments. Once the project manager receives more details, they can refine the schedule, setting firmer timelines and more realistic deadlines.
Benefits of predictive scheduling for team management
A more flexible benefits an organization in multiple ways:
Improved work-life balance
Predictive scheduling provides visibility into employees’ workloads, allowing them to plan their activities based on project demands. Project managers are aware of heavy workloads in advance and can plan accordingly to avoid assigning additional hours, safeguarding team members’ work-life balance.
Mitigates scheduling conflicts
Long-term predictive scheduling reduces the likelihood of time crunches. When team members have visibility into project milestones and deadlines, they can plan their workloads to avoid last-minute pressure. They can plan vacations and PTO when it’s least likely to disrupt timelines and impose stress on their colleagues.
Increased operational efficiency
With historical data backing it up, predictive scheduling can strategically allocate resources based on project requirements. Trend analysis shows project managers how much support they’ll need and when, allowing them to avoid over- or understaffing, streamline operations, and maximize cost efficiency.
Key components of predictive scheduling
Project management systems require the following components to implement predictive scheduling:
1. Accurate data gathering
A predictive project schedule depends on the accuracy of the historical data used to train the algorithm. Therefore, project managers must gather all available records about past projects, employee availability, and resource allocation patterns.
2. Data modeling
Predictive scheduling works best when paired with a robust forecasting model that can identify trends and correlations within historical data. Based on this analysis, the technology can reliably predict resourcing requirements, ensuring informed scheduling and allocation decisions.
3. Real-time adaptation
The dynamic nature of project management frameworks like Agile at Scale and Kanban demands a predictive scheduling solution that can adjust in real time. A responsive system mitigates risks by optimizing available resources to maintain productivity and efficiency.
Challenges and solutions for predictive scheduling
As with any new initiative, predictive scheduling has its own set of challenges. But with every hurdle, there’s a strategy to address it. Here are some common issues you may face and their solutions.
1. Data accuracy
The challenge: Inaccuracies surrounding resource demand, availability, and scheduling patterns lead to unrealistic predictions.
The solution: Establish a rigorous data collection process to ensure access to up-to-date information. Use digital solutions that integrate with your predictive scheduling application to capture historical information and store it in an accessible location using a logically organized structure.
2. Team availability and preferences
The challenge: Contractors, in-office employees, and remote workers all have different demands on their time. Organizing a project schedule around their working hours can be complicated.
The solution: Implement a scheduling solution that adapts to different working scenarios. Encourage team members to input preferred working hours and time-off requests so the application’s algorithm can establish a realistic schedule that balances staff requests while promoting operational efficiency.
3. Unforeseen events
The challenge: Even the best-planned schedule can’t predict sudden illnesses, personal emergencies, and exceptional circumstances. Unless addressed, these disruptions will diminish productivity and potentially delay project delivery.
The solution: The best way to address these scenarios is to build flexibility into the schedule through contingency plans. Consider cross-training new employees in additional duties so they can step in for team members facing a crisis.
Best practices for implementing predictive scheduling
These best practices will improve the reliability of predictive scheduling:
Involvement: Consult stakeholders and team members as part of the design and implementation of predictive scheduling practices.
Communication: Communicate changes in the scheduling process to team members, stressing their benefits. Ensure they understand their role in creating the project schedule.
Training: Train project managers, team members, and stakeholders to use the new system effectively. Address questions and concerns in a timely, respectful manner.
Feedback: Establish a feedback channel for team members to provide input on their schedules, identify issues, and suggest improvements to the predictive scheduling process.
Adjust: Regularly review the predictive scheduling model and adjust it as needed. When assessing prediction accuracy, account for new employees or changes in business processes.
Stay flexible: Predictive scheduling is supposed to encourage flexibility, so embrace it. Accommodate unexpected circumstances whenever possible and implement mitigation policies to address unplanned absences.
Streamline your workforce planning with Tempo
With Tempo, you can leverage the power of portfolio management capabilities and predictive scheduling in a single application: .
Portfolio Manager uses a sophisticated algorithm to generate predictive schedules that balance the workloads of even the most complex projects. The platform also delivers automatic resource leveling, task prioritization, and dynamic visualizations directly to users’ dashboards, so there’s no question about when tasks are due.
Tempo’s Portfolio Manager makes project scheduling chaos a thing of the past.
Note: Retail businesses and fast food franchises often use predictive scheduling technology to oversee employee schedules and on-call shifts while managing last-minute changes. However, it can apply to any industry with flexible work schedules. It also ensures management complies with employment laws governing good faith estimates of work schedules, predictability pay, and rest periods for minimum wage workers.
