After the T’s recent collapse, the Globe asked management specialists at local business schools for recommendations to put the system on track (and maybe on time).
Sean R. Martin: Teams perform smoother when trust flows freely
This historic winter has wreaked havoc on the thousands of commuters who rely on the T. It also has highlighted dysfunctional dynamics among Governor Charlie Baker, MBTA general manager Beverly Scott, and Keolis, the French contractor that runs the commuter rail.
To be fair, I am looking at this from the outside; all I can do is analyze the comments reported in the media. Still, this saga underscores a recurring theme: the importance (and apparent lack) of trust and open communication among various leaders, people, and groups involved. It’s a problem that afflicts all too many organizations.
Research suggests that leaders are more effective when they have timely, high-quality information from peers and subordinates. But information doesn’t always flow freely, which seems to be the case here. For example, before resigning, Scott announced a 30-day plan to get the Massachusetts Bay Transportation Authority back online, but Baker was apparently unaware of this plan. Several days later, he was similarly surprised by Scott’s abrupt resignation.
Meanwhile, the state sent mixed messages to Keolis regarding the fines the contractor may face for the many service delays in violation of their “no excuses” contract. Scott intimated that Keolis may not be responsible for all the fines, given the extraordinary circumstances. State Transportation Secretary Stephanie Pollack held firm on holding Keolis to its full obligations. Keolis representatives remarked that they had not discussed potential fines with state officials.
It may be obvious to most people, but during difficult times, it’s especially important for people to act as a team, share information, identify problems, and find solutions. So, what are the factors that inhibit communication, and how can people remove those barriers?
Two factors influencing information sharing are a) whether people perceive it to be safe, and b) whether they believe it can lead to productive change. From Scott’s perspective, her job would hardly seem safe. She was appointed by then-Governor Deval Patrick and her position has a notoriously short tenure — an average of about three years since 1980.
As far as believing that sharing information can lead to change, the MBTA has experienced neglect, crippling debt, and an ever-tightening operating budget. The new governor espouses conservative fiscal policies and shows no hesitation in publicly criticizing people he thinks aren’t up to snuff.
So for someone in Scott’s position, it’s hard to see how openly sharing information about the needs of the T would lead to change and not threaten her job.
Baker is in an unenviable position as well. He inherited a long-neglected transportation system during a historically terrible winter. And to give him credit, he appears to be taking constructive action — appointing a commission to investigate the root causes behind maintenance, financial, and service issues plaguing the T and having personal meetings with Keolis.
But several of the governor’s recent statements in the media, such as, “I’m sort of done with excuses,” (in reference to Keolis), and, “It’s pretty clear they need a new operating plan,” (referencing MBTA management), make it hard for someone to feel safe sharing information and debating ways to improve the system.
Finally, Keolis operates under a contract that provides no incentives to be open. A “no excuses” contract that imposes fines for poor performance may appear on paper to incentivize fewer mistakes, but it can also encourage people to hide problems because openness can cost money. Indeed, studies suggest that steep penalties for mistakes simply lead people to cover them up.
In sum, the winter has highlighted an all-too-common organizational phenomenon. A combination of structural issues (contracts, role responsibilities) and personal actions (leaders sending combative signals) create environments where information doesn’t flow. Thus, when collaboration and information-sharing are most crucial, they don’t happen.
This occurs frequently in organizations when leaders criticize employees publicly, when cultures, rules, and regulations reward those who hide mistakes, and when people fear for their jobs.
It’s a shame that in this situation, the ones paying the price are the citizens of the Greater Boston area who depend on the trains.
Sean Martin is an assistant professor of management at Boston College’s Carroll School of Management.
Steven J. Spear: Anticipate problems, then practice responses
The MBTA was walloped by January’s and February’s snow, and capital, technological, and urban planning ideas are being floated to prevent future disruptions.
For instance, the Commonwealth acquired two snow melters capable of processing 100 tons per hour to clear tracks and streets. There will certainly be calls for fleet modernization and maintenance, given the blame assigned to older equipment. Longer term planning has a role in ensuring the right type of vehicles are purchased and available to meet commuter needs.
While helpful, and even necessary, these actions won’t be sufficient. Necessary, too, is developing a high-speed problem- solving capability characteristic of the world’s most resilient organizations.
It is not just the Massachusetts Bay Transportation Authority that manages complex operations in complex and challenging environments. Airlines, shipping and trucking companies, manufacturers, hospitality providers, and military units all have their own versions of complex systems in complex settings. Some, however, are far better able to weather the storms that they face, demonstrating a consistency and adaptability in delivering value at speeds their counterparts can’t match.
Several factors allow exceptional performance:
■ Regularly seeing and solving low-level difficulties before they can contribute to large-scale disruption;
■ Stress-testing the system (in mock-ups and controlled simulation) to find potential failure modes when subjected to high levels of pressure;
■ Practicing crisis recovery so large-scale, high-speed recovery skills don’t have to be simultaneously developed and deployed on the fly.
In terms of the MBTA, high-speed problem seeking and solving means train and bus crews, mechanics, engineers, and the like should all start each day with a clear definition of what an ideal experience will be — safe, on time, clean, and so forth. It also means developing an eye to detect even micro aberrations from that ideal and investigating the root cause of disruptions, so countermeasures can be developed and their recurrence prevented.
This approach of seeking and solving problems that arise in the course of even “normal’’ operations is a part of the reason some airlines are more successful than others in terms of gate turnaround times, luggage handling, lower costs, and more affordable fares, all leading to greater customer satisfaction and profitability.
Stress-testing the MBTA means creating simulations, mock-ups, and other virtualization — power failure, equipment breakdown, large-scale events, outlier-level ridership, inclement weather conditions — to see where the system will crack when challenges are thrown at it. In training crews, for instance, the Navy regularly throws a variety of challenging environmental conditions to see at which point vessels might fail or the skills and training of sailors would be strained too far.
This gives insights well beyond those gained from normal operating difficulties as to where investment has to be made in people and equipment.
Stress-testing reveals conditions that may require longer term fixes as well as potential crises that require immediate mitigation. In the case of the MBTA, running a power failure scenario not only sheds light on infrastructure that must be more robust, it also creates opportunities to practice constructing alternative approaches for responding to crises. Those responses might include diversion of workforce and physical assets, adjustments to schedules and availability, and changes in communication and information approaches.
Colleagues at NASA explain that when preparing for a mission, leadership will run mock-ups of system failures — from just a few to dozens — while giving the team limited time to respond, only with resources available in the moment. Building skills in these contrived situations means that actual flights present fewer and less severe complications, which can be dealt with as if routine.
Long and short, the Legislature will be debating budgetary actions to prevent future system collapses. That said, the executive branch will not only have to spend that money wisely but also have to develop these dynamic capabilities to assure that it is put to the best and most effective use.
Steven Spear is a senior lecturer at MIT in the Sloan School of Management and the Engineering Systems Division. He is author of “The High Velocity Edge,’’ 2010.
John Macomber: Technology can help balance cost equation
The MBTA faces the same problems that confront every transit system in the world: Riders want to pay less in fares and taxpayers want to contribute less in subsidies. In exchange, everyone wants to receive more safety, more reliability, more frequency, longer routes, and later hours.
These opposing financial forces never add up. But new technologies and modern business models, many invented in Massachusetts, could vastly improve the balance of this age-old equation. Let’s enhance the T’s tool kit using technologies that involve sensors and tracking to make the most of resources; use big data and transparency to assure money is spent well; and encourage dynamic pricing that charges more during peak periods to balance loads and match customer preferences.
Consider passenger miles. In 2015, the MBTA will carry us about 1.8 billion passenger-miles. (The annual budget of the T is also about $1.9 billion – about a dollar per passenger-mile. Only one-third of this money comes from fares). Passenger-miles are an archaic way to measure transit, stemming from the old days when accountants could only look back and add up the totals in hindsight.
But not all miles have the same cost — and not all passengers have the same preferences. Today, in the era of smart cars, smart thermostats, smartphones, and even smart refrigerators, we have another generation of tools to deploy in the cost/revenue equation.
Sensors and tracking can address the cost side and how to best use equipment the T already has. How about dispatching buses and trains when they are needed, based on who is approaching the platforms, and using an app that anticipates passenger needs, such as Waze or Google Transit? Or measuring, tracking, anticipating, and fixing high problem routes, equipment, and mechanics using statistically proven schedules, parts, and training? This is how we already track and rate industries in the rest of our lives.
Big data and transparency help us to think about revenues and who gets how much value from their use of the T. Or the inverse — who loses value from bad transit? During recent storms, businesses, schools, and hospitals complained loudly about revenue lost and costs incurred because personnel (and customers) could not get in. Employees lost pay.
These organizations should invest in public transit to mitigate future disruptions. In the old accounting days, we’d worry this money would be wasted. In the new era of smart investment tracking (pioneered by local mutual fund companies such as Fidelity and State Street) we can verify that designated assessments go where they are intended. In Bogota, Colombia, for example, businesses directly contribute to the construction of rapid transit routes because they benefit directly.
Dynamic pricing is made possible by the marriage of sensors, tracking, big data, and transparency. We all are accustomed to car services and sports teams varying prices based on demand — just look at Uber rates or StubHub markups. The T could collect a premium for riding buses and trains during high congestion periods to move ridership off peak.
Similarly, it’s conceivable to charge a premium for late night riding, reflecting the much higher cost per passenger when trains and buses are partially full. The billing technology is available and ubiquitous; your mobile phone already has it.
But do we want to price transit out of reach of lower income people, many of whom need reliable public transit to survive? Of course not. Do we want to tax residents into oblivion to subsidize public transit? Of course not. Cities such as Singapore charge close to the full cost for a ride but also subsidize individuals who need help. This is a more enduring way to allocate the cost of transit — as a function of the relative value the rider is willing to pay.
We can expect the customary gnashing of teeth over state subsidies for the T and the same old management fights. But we can also arm the T with modern data, sensor, and tracking tools to better serve us all.
John Macomber is a senior lecturer at Harvard Business School.