It is Mark Powell’s job as director of baggage operations to make sure that bags and suitcases travel through the airport from check-in or bag drop and on the plane, or from the plane on to the right carousel in the arrivals hall as quickly as and as accurately as possible.
For him, it is important to understand the world behind the data and in this context of luggage and baggage, this means getting out onto the concourses of the airport terminals to see the bags moving through the system and the equipment they travel on. “It’s about sharing the data being able to match up that data side with the reality,” said Powell.
The most useful things he does on the ground are relationship building, seeing how the data is collected and properly understanding the questions he is trying to find answers to. This can reassure those working at the coalface of airport baggage that their views are being properly taken on board and any misunderstandings can smoothly be rectified.
Powell’s most interesting data challenge is a current one in which he and his team are looking at how they make use of the capacity in the system to reliably get bags through whilst volumes increases due to higher passenger numbers.
“The historic way of doing this is predicting, so looking at what do we think the demand is going to be, what do we need and what is the current capacity. Then needing to build something,” said Powell.
In contrast, now Powell and his team – the baggage data analysis team, thought this is not the official title - aim to use data to avoid building something new but change the process to make more efficient use of it.
“Data is becoming the solution. It is not just highlighting the problem.”
“Data is becoming the solution. It is not just highlighting the problem,” said Powell. An example of this is seeing how many more flights they can fit efficiently into one make-up area – a packing point for bags before they end up on a flight. With robust operational data, he is able to predict at a granular level the volume of bags coming through and when they will turn up.
By operationalising data into the process, he and his team can have a good forecast every day and adapt their plan depending on the specifics of what they are expecting that day, whether that be the number of flights coming in, the number of passengers on connecting flights and even whether those flights are early or late. He asked: “Does that allow us to adjust how we do it? The answer is yes.”
One of the tasks that Powell finds most interesting is looking retrospectively at years of baggage data and seeing if correct predictions could have been made by applying certain algorithms.
"Because of the scale of historical data, we can make changes with certainty."
He said: “We’ve got changes we can make with enough certainty now because of the scale of data we’ve got historically. Our prediction will be good enough to allow us to make that efficiency and that results in quite big financial savings.”
He and his team are working with vast volumes of data. In 2018, 80 million passengers passed through the airport. If there every three passengers bring two pieces of checked luggage, that is 120 million bags to process.
In the past, they used to get three or four tracking points per bag whereas now that number is 500 to 100 tracking points. Some of those points are individual counters that sense whether or not a bag is blocking a small beam of light. The exact journey of each bag is tracked throughout the system and is recorded in the data repository.
They work alongside the operations team as an immediate customer who might request a specific piece of information or in turn suggest an interesting piece of information the data baggage team could use. Sometimes they work side by side if there is a special event like a cycling event that could affect the amount of oversize luggage they have to deal with.
If bag data wasn’t Powell’s bag, he’d still be looking at transport data in some form, such as passenger journeys through the airport or retail spend in the restaurants and duty-free shops or plane figures. “I am genuinely fascinated by all the transport data. I started my career looking traffic data in London so flows in and out of the congestion area. There are so many interesting data that’s at Heathrow,” said Powell.
Mark Powell is a member of the DataIQ 100 2019 edition.