Data and Disaster: What Businesses Can Learn from Flight 32


In any industry…in any situation, data overload – especially if it involves undifferentiated data – quickly becomes unmanageable, impossible to use, and often a distraction that can severely impact outcomes. Remember Quantas Flight 32?

On November 4, 2010, Flight 32 was carrying 469 people from London to Sydney Australia when disaster struck. The Airbus 380’s number two engine turbine disc disintegrated and ripped through the engine and the fuselage, causing severe structural damage and massive systems failures.

According to the ATSB report, 22 of the 24 flight-critical systems, and 54 error messages screamed out for attention. The crew, who were quickly overwhelmed, didn’t know what to do, where to look or, more importantly, what data to trust.  Fortunately for Flight 32, Captain Richard de Crespigny did know what to do. He told his crew to ignore every alarm and every control that was not critical to flying the aircraft. Incredibly, by doing this, the crew were able to bring the stricken airliner back under control and landed it safely.


Flying Blind or the Danger of “Democratic” Data

The lessons learned from the miracle flight can also hold true for businesses,  as having too much data can be dangerous in that setting as well. Good data is essential, but a mass of undifferentiated data is unmanageable and detrimental. Instead of a beacon of insight guiding executives to sound business decisions, it becomes a dense cloud of luminescent fog, distracting decision-makers and obscuring the path ahead. For most businesses, the latter is often the case.

According to an Ernest and Young report“Exponential data growth is a fundamental problem that is continuing to overwhelm most businesses, and it is accelerating. New digital business models are increasingly more complex…companies that are able to effectively manage that complexity will clearly maintain a competitive advantage.”

Running a successful supply chain (or business for that matter), is, in a lot of ways, like flying a plane. You need to anticipate and plan for a certain volume of sales, then move products from point A to point B to get them to customers quickly and efficiently. You need to continuously monitor demand, decide how much inventory to carry and where, and determine which is the most effective way to move it. To do this effectively, you need to continuously monitor sales, supply, capacities and logistics, and adjust your course as things change. Then, no matter how well you do that, there’s a good chance factors outside your control such as a trading partner mishap or the weather will interfere with your carefully laid plans.

Therefore, it is important that your “flight deck” has certain key features. This starts with a “flight path,” or global view of your extended supply chain, from source materials to sold goods, with demand at one end and inventory positions and lead times back through each leg and through N-tiers of suppliers. Many companies operate mainly in the dark, with visibility to certain data within their four walls, but with little access to their partner’s data. This is akin to flying without key data like, airspeed, altitude, or heading. So, while there are many lessons one can take away from Quantas Flight 32, a few important points stand out and are needed to achieve a successful flight plan:


Complete Visibility: Just like a pilot needs access to data beyond just the cockpit and fuselage to determine  things such destination, heading, weather, etc. a business needs access to  information beyond its own four walls. Examples include data about customers, suppliers, logistics providers, commodity prices, manufacturing capacity, orders, shipments, and much more. After-all, what’s the point of running an expensive promotion if your supply network can’t deliver the product offered?


Real-Time Data: Imagine the results if Captain de Crespigny had trusted the erroneous data from the failed systems, or if he had used the previous days’ flight data in lieu of the missing information. Sounds crazy, yet many businesses are driven by stale, inconsistent or missing data, compounding bad decision on bad decision. In today’s fast changing world, data must be real-time if it is to be of much use. Decisions are only as good as the data they’re based on, and in business, a lot changes in 24 hours. Therefore, it’s critical that all business partners in the supply chain function from a single, real-time version of the truth.


Execution: The pilot of a plane can not only monitor conditions outside and inside the plane, he can also exert control over the throttle, rudder and the flaps to adjust course in response to changing conditions. Likewise, businesses must execute decisions, anticipate problems, and address them as they arise. It’s important that planning, execution and collaboration be based on real-time data, because delays drive up costs and lower the chances of solving supply chain problems. As we all know, the sooner a problem is identified and addressed, the more options you have and the cheaper it is to fix. For example, if your projected inventory view shows an impending stock-out, the sooner it is caught and corrected, the more likely you are to fix it with the next scheduled shipment, thus avoiding expediting product, or worse, an actual stock-out that can result in lost sales or a plant shut-down.


Hierarchical and Configurable Dashboards: One of the most fascinating aspects of the miracle flight story, is how much data Captain de Crespigny ignored. Data is invaluable, but it must be effectively managed, filtered, prioritized and presented in the appropriate context if it is to drive optimal decision-making. Like Captain de Crespigny, executives can’t give equal importance to all data. They need to be selective and focus on those that matter in terms of their context and to their role. Like de Crespigny’s insight to envision a much simpler Cessna cockpit, executives don’t need reams of data and reports to execute most decisions. What they need are configurable and customizable dashboards that highlights the essential key performance indicators (KPIs) that reveal business performance and serve as a basis for sound strategy and decisions.


Auto-Pilot and Managing by Exception: Under normal conditions, the plane flies itself. The pilots are not fretting about every indicator and manually adjusting the plane second by second. They often let the autopilot and/or auto throttle handle the basic flight trajectory, while they look at the big picture, keep an eye on a few key indicators and watch for alerts that could signal trouble. Supply chains, to a large extent, can now run autonomously too. With the help of IoT, machine learning, and intelligent agents, running on a network, many processes can be autonomously optimized and managed. For example, sales data can be propagated back up the supply chain to drive forecasts and orders, while drones can update inventory and dock doors and resources can be scheduled and updated according to GPS and telematics data from delivery vehicles. In turn, intelligent agents can monitor the network for potential issues, and in many cases, resolve them autonomously.

Human involvement will always be needed, especially when something goes wrong or is beyond the abilities of the system to manage. In such cases, intelligent agents can escalate the issue and human managers can intervene. Decision-support is critical at this point, and intelligent agents are invaluable, as they can supply recommendations based on historical data and insights gathered from analyzing thousands of similar situations across the network to identify the resolutions attempted, and the outcomes. They can recommend the optimal solution but allow human planners to approve the suggested resolution, or override it with their own solution.


Data: The Key Ingredient for Digital Transformation

There seems little doubt that if Captain Richard de Crespigny wasn’t aboard Quantas Flight 32, the flight would have ended in disaster. His extraordinary decision to ignore most of the data coming at him, combined with his ability to focus on the fundamentals of flight, almost certainly saved the lives of all 469 passengers and crew members.

Today, we have the technology at our disposal to get a better view of the business and run operations much more efficiently based on a comprehensive and intelligent view supported by real-time data from across the supply network. This unified, live view is possible with a multi-party business network that connects all trading partners to a single version of authoritative, real-time data. Using this single system for planning and execution, all parties enjoy full visibility and more efficient operations across functions and trading partners. Supplemented with intelligent agents, businesses can run many operations on autopilot and make better use of their limited resources to provide optimal service to their customers.


Nigel Duckworth is a senior strategist at One Network Enterprises, provider of a AI-enabled business network platform that enables all trading partners to manage, optimize and automate complex business processes in real time.