The transition from manpower to brainpower
In the late 1990’s, airlines around the world faced a significant challenge. As they began rapidly expanding their networks to carry passengers to ever more and more distant destinations, their growing ranks of crew members required safe, reliable lodging for rest and recovery between flights. In addition, the FAA and other regulatory bodies around the world began strengthening guidelines for mandated crew rest, requiring airlines to conduct business with an added layer of complexity in their operations. The confluence of these developments produced a critical and urgent need for programs and processes centered on booking and managing thousands of hotel and transportation reservations for airline crew members; and a new market was born. The response was an industry-wide push to develop in-house crew hoteling departments and equip them with the latest technology of the time. So armies of agents were hired and provided phones, spreadsheets and email accounts to communicate directly with hotels to ‘put heads in beds’.
By the 2000’s, technology had improved, and with new levels of storage capacity and processing speed, software companies could now provide real value to the airlines, helping them reduce operating costs by deploying (locally initially, then eventually SaaS-based) systems that would improve booking accuracy and drive efficiencies in reservation management. At the time, airlines were facing unfavorable economic conditions and ballooning costs. They were posting regular losses and were under significant pressure to find operational efficiencies due to cutbacks in corporate business travel, tough labor agreements and rising fuel prices. Transitioning crew hoteling and transportation to a third-party provider enabled them to simplify their operations, find material productivity improvements and realize cost savings in sourcing and contract negotiation. Yet while this new model leveraged state-of-the-art systems that could process transactions at high volume, in reality they still required agents to handle the bulk of the workflows manually. Most required tasks were still being completed outside of the system, by agents, who fed their decisions and required actions into the systems for execution. Despite the promise of technology, not much had changed from the previous era.
It’s time for a better way.
As we know from Moore’s Law, the speed and capabilities of technology are accelerating at an exponential pace, while the cost of deploying such technology decreases in parallel. And so the relentless introduction of new tools, features and functionality is dramatically changing the way we travel and raising expectations for our travel experience. We travel smarter, lighter and faster, while enjoying a convenient, comfortable and personalized experience along the way. All while using a variety of mobile-enabled applications that empower us to take charge of our own journey. For professional travelers, it’s not much different. Airline crew members today expect more from their layover experience, and so the intersection of expectations from crew with the pressure to manage operations productively and cost effectively by airlines has ushered in the next phase of market evolution:
Crew Logistics Management
We’ve all heard the age-old adage that businesses that do not evolve do not survive, and this has never been truer than it is today. Airlines must now balance traditional CLM workflows with an ever expanding list of related yet still critical processes, such as irregular operations, distressed passengers, virtual vouchers and payments, real-time positional tracking and route optimization, and financial reconciliations, just to name a few, that are pushing existing systems to their limits. The math problem has gotten bigger and even more complex and can no longer be solved by just throwing more and more agents at it.
Automation + Augmentation = Transformation
Fortunately, there is a new approach that sees this challenge as an opportunity to move the market forward transformitively, by embracing emerging technologies that promise an exponential leap forward in performance. Flexible, adaptive advances like open standards, service enablement, microservices-based architectures, artificial intelligence, machine learning algorithms, natural language processing, block-chain methodologies, and predictive analytics offer previously unattainable levels of speed, agility and security in CLM workflows while fundamentally altering the role of the agent. The next wave of technology solutions for CLM reduce human bias and error through AI-powered automation for low-complexity tasks, and augment a smaller but more intelligent cache of agents with machine-learned insights, recommendations and analytics where human judgement is required for making data-driven decisions. All while empowering professional travelers to personalize their experience via their preferred channels and touchpoints and providing the airline complete transparency into its operations and performance.
The bar has been raised, but you should expect that the evolution in CLM solutioning will continue. Salim Ismail said that an invention needs to make sense in the world in which it is finished, not the world in which it was started. Taken from this perspective, CLM is just beginning.
 In 1995, the FAA proposed a rule to change flight time and rest limits. transportation.gov
 The movement to target pilot fatigue began in 1992 after several incidents like the Colgan Air Crash which preceded strict regulations being implemented by the FAA in 1995.
 Tom Hansson, Jürgen Ringbeck, and Markus Franke, “Flight for Survival: A New Operating Model for Airlines,” s+b enews, December 6, 2002.
 “Cramming More Components Onto Integrated Circuits” by Gordon E. Moore; Electronics; Volume 38; Number 8; April 19, 1965.
 Based on Accenture’s whitepaper “Turning Artificial Intelligence Into Business Value. Today”, written by Bataller, C. & Harris, J. (2016).
 “Exponential Organizations: Why new organizations are ten times better, faster, and cheaper than yours (and what to do about it)“; by Salim Ismail; Diversion Books; October 2014.
By Jeffrey Humin
The Future of CLM Is Now
Learn more about how data, analytics, and Artificial Intelligence (AI) have enabled a new era of intelligent Crew Logistics Management (CLM).
- Crew Hoteling and Transportation
- Crew Logistics Management
- CLM Market Transformation