Innovations to its intelligent scheduling engine will enable more time- and cost-effective scheduling to increase productivity and work outputs
Skedulo, the leader in deskless productivity software, announced major enhancements to Skedulo MasterMind, its artificial intelligence (AI) and machine learning (ML) optimization service, enabling organizations to optimize their workforce around the priorities and variables that matter most, including workforce utilization rate, operating cost, travel time and more. The most recent enhancement to the Skedulo Deskless Productivity Cloud, Skedulo MasterMind is powered by MasterMind Solvers, which are scenario-specific optimization algorithms.
According to research from Skedulo published this week, 60% of deskless workers feel their job has become more difficult since COVID-19, and 72% of IT executives claim worker productivity is negatively impacted by their existing technology. The Skedulo MasterMind enhancements enable organizations to automate scheduling based on user-defined variables so scheduling decisions are made smarter and faster. MasterMind Solvers enable users to easily rank scheduling variables by importance and automate schedules accordingly, which can significantly reduce travel time, distance, and cost per hour for deskless workers and organizations while maximizing work capacity, increasing workforce utilization, and best matching worker and job attributes. Through machine learning capabilities, MasterMind Solvers will recognize patterns to make faster and smarter decisions over time.
Marketing Technology News: Techsee Announces Partnership With Salesforce for New Visual Remote Assistant Technology
“By 2025, algorithms and bots will schedule over two-thirds of field service work for field service providers dependent on automated schedule optimization, up from less than 25% in 2019,” according to the Gartner Magic Quadrant for Field Service Management (FSM) published in July 2020.¹
This overhaul of Skedulo Mastermind applies a completely new approach to how AI, ML, and algorithms are applied to a growing number of complex scenarios. Rather than relying on single-pass greedy heuristics or overnight batch processing, individual MasterMind Solvers are oriented toward specific scheduling challenges, such as shift scheduling, route optimization, and on-demand/real-time business models. An additional AI layer observes patterns of how these solvers provide outcomes over time and progressively tunes solvers to be faster and more efficient.
In benchmarking evaluations with 5,000 appointments and a series of variables and constraints, Skedulo Mastermind is over 87 times faster than a traditional field service solution and is able to reach a superiorly optimized solution in 62 seconds versus the typical 90 minutes.
Marketing Technology News: Tinuiti Launches Instacart Acceleration Program
“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, EVP, Technology and Innovation at Skedulo. “COVID-19 has stretched deskless workers thin. Our report, ‘2020 State of Work Report — Defining a New Normal Amid COVID-19,’ found one in three employees is working more hours since the pandemic began. Our recent rollouts to Skedulo MasterMind will better optimize time for companies and their employees alike.”
Additionally, Skedulo has announced the general availability of Dynamic Messaging, an instant messaging service available to both deskless workers and their operations teams natively within the Skedulo web and mobile applications. With the increasing volume and complexity of deskless work, Skedulo Dynamic Messaging empowers organizations with deskless workers to bridge communication gaps through a powerful messaging solution to share job details, solve for real-time work challenges, and address escalations, all within the Skedulo Deskless Productivity Cloud.
Marketing Technology News: Reprise Emerges from Stealth; Announces Demo Creation Platform and $3.2 Million in Seed Funding