Intelligent Automation Powered by Legion WFM
“Intelligent Automation (IA) is fueling the next wave of digital transformation.”*
What is Intelligent Automation?
A new generation of enterprise applications, powered by AI, is automating decision-making and executing those decisions. Until now, the role of enterprise applications was to provide software tools for users to execute business processes, but the users had to make most decisions outside the software. With intelligent automation, this major evolution frees managers and enables unprecedented productivity and business process automation.
Automated execution of decisions
Continuously improves by learning from data and user actions
Builds trust through transparency
Always allows human control
See It in Action
Legion WFM Enables Intelligent Automation
Transform labor operations and enhance employee engagement.
Forecasting that factors in the past and future
Predict demand across all customer touchpoints and locations. Synthesize thousands of data points including historical data, ongoing operations, and future events like weather and local events to create the optimal labor plan without human intervention.
Automatically generate and manage the optimal schedule
Automatically match labor needs with employee schedule preferences. Continuously learn from manager edits and employee preferences to instantly generate the optimal schedule. Automate schedule maintenance.
Empower hourly employees with gig-like flexibility
Automatically fill shifts based on skills, preferences, and rules. Enable self-service shift swaps and shift claims. Automatically respond to employee schedule requests based on rules.
Reduce human errors and eliminate bias
Automated decision-making and execution removes bias based on gender, race, or age. All decisions are based on employee performance data.
What’s Required to Deliver Intelligent Automation
A modern data pipeline
Automated decision-making requires the platform to collect and analyze trillions of data points. External data, such as weather and local events, are syndicated and operational data is collected. Data is then structured and organized, so models are continuously trained for optimal execution.
Real AI and machine learning
Advanced data science, such as optimization techniques and neural networks are required. Automated ML selects and tunes models, makes iterative adjustments, and reselects models as needed.
A holistic approach
Employee engagement and labor optimization must be addressed simultaneously. Optimization techniques automatically generate the best possible decisions with constrained resources, such as meeting business coverage and compliance needs while maximizing employee satisfaction.
The platform must be self-learning with the ability to adapt to changing patterns in the data without requiring human intervention.
Trust through transparency
To adopt a platform, users must be able to understand the rationale behind the decisions that are automatically made.
The platform must allow human control and learn from users’ positive actions as well as warn them of possible compliance issues.
By 2023, 99% of new WFM application sales will be cloud based.**
Setting Yourself Up for Success
Create a shared vision
Approach automation as a transformation project not administrative or task replication. Ensure all the key stakeholders are aligned and understand the metrics for success.
Get the right team to drive execution
Involve technical resources to help with integration and automation and ensure you have appropriate testing resources.
Enable cultural change
Understand the culture and employee impact. Ensure they understand that intelligent automation will empower them by removing administrative burdens.
Test and iterate
Monitor early results, get feedback, and adjust.