Skedulo, the scheduling and management application provider, has announced additional enhancements to its Skedulo MasterMind - to meet the growing demand and complexity in the deskless workforce.
Skedulo MasterMind, the company's intelligent scheduling engine that works through artificial intelligence (AI) and machine learning (ML), is now adapted to allow organizations to optimize their respective workforces better. The improved platform helps managers sort through workforce utilization rates, operating costs, travel time, and more. The improvements are made possible with MasterMind Solvers, scenario-specific algorithms that further optimize the platform.
In a study published by Skedulo, titled "The 2020 State of Work Report - Defining a New Normal Amid COVID-19," illustrates that up to 60 percent of deskless workers feel that their job has become more difficult since the start of the coronavirus pandemic. Meanwhile, 72 percent of IT executives say that their workforce's productivity has been negatively affected by existing technology.
With Skedulo MasterMind, leaders and executives can automate the scheduling of work tasks based on predefined variables, increasing efficiency, and reducing lead times. With the integration of machine learning systems, its MasterMind Solvers will soon identify patterns and make informed decisions over time.
According to the Gartner Magic Quadrant for Field Service Management, published in July 2020, algorithms and bots will be behind scheduling up to two-thirds of field service work dependent on automated schedule optimization by 2025. This estimate marks a sharp increase from less than a quarter back in 2019.
A Marked Increase in Performance
The recent enhancement of Skedulo MasterMind implements AI and ML in response to varying and increasingly complex scenarios. Individual MasterMind Solvers are specifically trained to tackle specific challenges in scheduling automation - route optimization, shift scheduling, and even adapting to on-demand business models. Unlike other automation systems, Skedulo does not depend on heuristics, or processing shortcuts, and overnight batch processing, allowing its system to adapt and adjust to specialized requirements.
Additionally, an extra AI layer oversees and observes potential patterns on how the algorithms decide for an outcome, progressively tuning the solvers to make them faster and more efficient.
In its benchmarking phase, Skedulo evaluated the overhauled MasterMind against 5,000 appointments and varying constraints and variables. The upgraded platform showed to be 87 times faster compared to traditional field service solutions, boasting an ability to arrive at an optimized solution in just 62 seconds, compared to the average 90-minute lead time.
"Our advancements to Skedulo MasterMind and MasterMind Solver algorithms empower organizations to increase work outputs and reduce overhead, like travel time and utilization," said Paul Schulz, Skedulo's Technology and Innovation EVP. He added that "COVID-19 has stretched deskless workers thin." Citing their report, Schulz noted how one in three employees work more hours since the pandemic's onset.
Aside from the upgraded Skedulo MasterMind, the company also announced Dynamic Messaging: its instant messaging platform that connects deskless workers with their operation team. The messenger works entirely inside the Skedulo web and mobile apps, adding to the scheduling automation platform's holistic solutions. With Dynamic Messaging, organizations effortlessly bridge communication gaps, allowing a real-time exchange of ideas and responses to work challenges.
Learn more about the Skedulo Dynamic Messaging below:
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