Many factors, beyond your forecast and labor standards, influence the right labor hours to schedule. However, many workforce management systems treat them as afterthoughts. Logile enables retailers to build a better store-specific staffing plan with full transparency upstream of scheduling.
Evaluate Cost of Business Requirements
Visualize what labor hours are being driven by your staffing constraints versus your true demand
What-If Simulation
Analyze the impact of applying different staffing constraints
Workforce Planning
Improve employee headcount planning via store-specific, long-term forecasts that recommend the mix of employees needed to meet your business requirements
Deliver Superior Service
Apply staffing rules directly to your labor model to visualize how your “all in” labor hours build up.
- Apply a broad set of staffing rules to fine-tune your service goals, beyond simple minimums and coverage ranges
- Understand where your staffing rules are adding extra labor hours, beyond your raw demand, and use that insight to drive labor efficiency
- Easily apply store-specific coverage models without the need to configure each store independently
Future-Proof Business Planning
Improve your ability to evaluate potential impacts of changes to your business rules through what-if simulation.
- Quickly model new staffing rule scenarios in a sandbox environment, without affecting production, and analyze impact on your labor hours
- Drive continuous improvement by easily testing scenarios to more effectively rebalance labor across the day
Ensure Your Workforce Reflects Your Business Needs
Gain a clear understanding of what your optimized schedule should look like, based on your business demand, to make proactive and informed decisions to address staffing gaps.
- Automate the process of forecasting your scheduling needs for the coming seasons
- Identify and address potential staffing gaps before they impact operations
- Significantly reduce time spent on administrative tasks that could be used for critical frontline tasks