Malaysia Airlines Managers Could Have Had Better Data at Their Fingertips

Unprecedented disasters nearly always yield 20/20 hindsight, and lead to narrowly-conceived, “never again” style reforms. But sometimes the lessons are more broadly useful.  In the case of Malaysia Airlines Flight 370, the most impressive fact few reporters choose to explore in any depth is that the Boeing 777’s engine was capable of communicating long after the pilots went silent. And the tragedy is that all the information it was able to convey was not actually transmitted.

If the news media were more tech-oriented, they would report this as an Internet of Things (IoT) story. The term refers to the fact that billions of sensors and devices are connected to the web, automatically transmitting, receiving, and taking action on data. Now that, in fact, they far exceed the number of connected humans on the planet, we have an Internet of “things” more than people.

The data that eventually showed that Flight 370 continued for hours after voice transmissions ended came from satellite pings, most notably provided by Inmarsat. But more precise data could have come more directly from the plane’s Rolls-Royce Trent 800 jet engines – almost all Rolls-Royce engines produced in the recent past are IoT-enabled. While many major industries have yet to create “IoT” products, that’s not the case with jet turbines. Thanks to their cost, the very strong interest in running them efficiently, and the enormous safety implications of their maintenance, it has been easy to justify the added costs of  building in sensors that transmit information about the engine’s operating conditions to the ground in real time. All manufacturers now routinely include 60 or so such sensors on their models. (Evidently these engines, because they were older, had add-on sensors, not the built-in ones, but the point is the same.)

This data allows the manufacturers and their customers to do things that were simply impossible in the past. Instead of scheduled maintenance, whose intervals are typically based on imprecise measures such as mean-time-to-failure, they can now offer airlines “predictive maintenance,” which is done when each individual engine actually needs it, as indicated by real-time data from the engine such as detection of a hairline stress fracture that may not be visible. That’s not only cheaper, but can also avoid a catastrophic in-flight failure.

The IoT turbine also offers the manufacturer a marketing option: instead of selling the turbine, they can instead offer an airline a lease where the price is determined dynamically, based on the precise data about how far the engine is flown, or they can offer fixed-price maintenance agreements that work because the company can avoid unscheduled repairs.

So why didn’t engine data help in the search? Because the airline had the option, but declined, to pay about $10 per flight for real-time access to it. Had it chosen to make the investment, it might have done so in order to tweak the engines for maximum performance – but in doing so, it would also have gained the ability to keep tabs on a wayward plane.  Looked at in this light, the terrible delay in finding Flight 370 can be seen as a failure of management practice to keep up with new technology.

IoT experts I’ve consulted about this idea think it’s likely that the data from the Rolls-Royce engine was probably in an “open” (vs. proprietary to the company) format that would have allowed it to have been shared, as it was generated, with the airline, and even the flight controllers. That would have meant that, when voice contact ceased, they could have switched to the engine data. Because they would have seen that the plane was still flying, there might even have been time to take measures to avert loss of life. Instead, this data only surfaced days later: still critical, but not actionable.

My take on this lapse is that there’s a gap between the power of IoT technology, and management’s ability to conceive strategies to capitalize on it, which I refer to as “IoT Thinking.” In particular, managers have yet to wrap their heads around a new design imperative: That as we design things to be part of the Internet of Things, we must constantly ask: who else could use this data?  Many of the potential benefits of real-time IoT data can only materialize if we envision multiple users.

Here’s a simpler example to illustrate what I am saying. I recently saw a vending machine prototype enabled by IoT technology, mainly with customized marketing in mind. It can recognize a customer, offer her a special package (perhaps a price break on a soda plus chips) based on her past buying choices, and even adjust prices dynamically based on outside air temperature. (Someday you might regret saying, “I’d pay anything for a cold drink right now!”). However, the developers didn’t stop there: they asked what I think has to be a fundamental question with the IoT (and one we just haven’t asked in the past, when proprietary data was the route to fame and fortune): “ who else might have use for this real-time data?” In this case, they realized that the machine’s sensors could also detect when the inventory level in the machine was low. If that data were relayed (again, in real-time) to a distributor, it could be feasible for a delivery truck to have its route dynamically rerouted to replenish the machine. One data stream, many uses.

Similarly, manufacturers will be able to dramatically improve supply-chain integration and their distribution, while optimizing assembly line efficiency by building in sensors throughout the assembly line, and spreading that data to everyone, from assembly line workers to supply-chain partners, who can use it.

Given this new reality, aviation safety authorities should consider mandating that engine manufacturers in the future routinely provide the data stream to airlines and the flight controllers — and that the companies monitor it. (That’s quite simple: all they need to do is program alerts for the relatively rare exceptions when the data deviates from norms).

Smart airlines may take the initiative and demand the data now. My sources in the industry say that some airlines use this real-time data to tweak engine performance, a competitive advantage. (After the BP blow-out disaster, I suggested that the same approach would be applicable to drilling platforms. And it would be ideal in the event that the Obama Administration approves the Keystone XL pipeline: a built-in sensor could detect a stress fracture before any visible evidence, then automatically trigger a shutdown. Not a drop of oil would be spilled and the company would know exactly where to go, speeding repairs and restarting the pipeline quicker.)

The Internet of Things’ ability to share real-time data among many users simultaneously has many advantages to everyone who has access to it. Not least of these is the potential to save lives.

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