Allowing talent to select their days of week, times of day and shift activity would mean higher satisfaction, reduced absenteeism and increased customer satisfaction.
Qualifying talent by assigning proficiency levels would help obtain confirmation for a retailer that candidates possess the requirements for a role / activity.
When retailers access digital and mobile platforms to communicate with employees and candidates, a new opportunity for more effective training and learning is created.
It’s a market economy. Scaling wages to pay more for the most important times of day, days of week and activities only makes sense for willing, qualified and interested employees.
Digitally enabled real-time customer and manager feedback means that coaching and recognition are continuous. Star-ratings would allow management to set the value of certain skills, and identify employees who could potentially benefit from training to seek to enhance value.
Top talent can be shared across a retailer’s brands. Increased flexibility for workers also means improved nimbleness for retailers to better manage their SG&A line.
Alternative labor models sound futuristic but they have field tested their value in a range of industries and environments. Most people know about Uber’s model – drivers using their own vehicles to provide transportation services during hours they control with pay rates reflective of demand.
What gets overlooked is that TaskRabbit launched the same type of demand-driven approach almost a decade ago: a broad pool of ‘taskers’ specifies their skill range and bids to perform tasks, the difficulty or uniqueness of which helps set their wage. And, although we don’t see them, air traffic controllers have used a bid system for years, one which factors in seniority and differential pay to help verify coverage on less desirable shifts and allows for shift swaps among bidders. All these arrangements match demand and supply in ways that would work for both the principle organization and the individuals doing the work for them.