by Joanne Chin, Head of Product
Data has been an integral part of my job function since I joined AirAsia 9 years ago as a Financial Analyst in the Ground Operations department. (I originally interviewed for Check-in Agent but that’s another story)
Now that I work at Teleport, the data-meets-logistics startup of AirAsia, data becomes even more important as logistics is an industry that thrives on a lack of transparency — it’s easy to find out how much it costs to fly a passenger but the same can’t be said for cargo.
When Teleport first started in 2018, we were dealing with a legacy cargo booking system with no ability for data extraction, non-existent capacity management and an entirely manual reservation process.
Today, 100% of our shipments are booked online via a Cargo Management System, we track everything on automated dashboards, from warehouse operations to sales to our parcels business.
There is a lot more work to be done but we have come a long way and I wanted to document the lessons I learned to-date while dealing with data.
1. Always question what you see
One of my first tasks in AirAsia was to track station expenses across the entire network of more than 130 airports. My predecessor had worked with the ERP system provider to set up airport codes in one of the system dimensions. The monthly expenses reports showed unusually high expenses (per passenger served basis) at a few stations and it had been shrugged off as the stations having a higher unit cost than the rest, causing the Station Managers to be reprimanded during the monthly cost reviews. I asked to see the raw data of all expenses and found out that staff training cost and consumable items, e.g. boarding passes, bag tags were all procured and recorded centrally by the hub stations and these expenses were not apportioned to the other stations. When we apportioned the costs accordingly, the expenses report looked a lot more balanced.
2. Look deeper into how you can use data to improve performance
Data is not valuable unless interpreted to tell us what we need to know.
For example, cargo revenue numbers are not as indicative as yield and utilization when it comes to measuring drivers of performance.
3. Don’t think of data as an ‘outsourced’ task
I noticed many managers are not interested in working on data at all. They often go to a junior analyst and say ‘give me a report’ without being clear on their requirements. While managers shouldn’t have to do all the analysis themselves, they do need to be deeply involved in the process. Analysts have the skills to work on data and visualise data but ultimately it’s the business users who understand what data is important to show and whether the data presented makes any sense.
In Teleport we believe in a data-centric approach, and this means:
- Managers need to be proficient in using data visualisation tools such as Google Data Studio and running basic SQL queries;
- Managers are responsible for building performance dashboards for their respective business units;
- Data plays an important role in systems design/procurement decisions, and managers are expected to ask questions like: Can we connect the system database directly as a data source to build interactive dashboards? Can we customise the data fields to collect the information important to us?
- Team performance are measured on dashboards — fair, transparent and live
(Originally published on the Teleport Blog on January 23, 2020.)
