Putting Big Data to Work for Airports

The airport industry has its priorities. Managing operating costs, avoiding potential disruptions and improving passenger experiences all land at the top of the list. But it may be missing a critical player in its operations: big data.

The amount of data worldwide has been increasing exponentially each year. Fully 90% of data ever created has been generated in the past two years alone, and 30% of it potentially contains valuable information. Despite this, less than .5% of data collected is actually being analyzed and monetized. Most ends up dormant and unused.

Andrew Schmahl Andrew Schmahl is a principal with Booz & Co. who focuses on air, road and rail clients. Most recently, he has worked with several global airports on operational resilience, technology enhancement and organizational improvement projects. Schmahl holds a B.A. in Economics from the College of William & Mary and an M.B.A. in Finance & Strategy from the Kellogg School of Management at Northwestern University.

Big data methods — analyzing and monetizing these “sleeping giant” data sets — may be the key to creating more efficient and productive airports. This allows businesses to generate fact-based, individualized, real-time answers rather than relying on the intuitive, general, retroactive realizations of traditional research.

While the idea of using big data for monetization may be relatively new, it’s already helping companies enhance their quality of information, generate insights into their customer bases, implement “private label” capabilities and create new data and products.

Other industries are already making strides in taking advantage of big data insights. UPS and other parcel delivery companies use big data methods to provide real-time, in-transit service offerings for customers. Consumer credit cards such as American Express, Visa and MasterCard leverage big data to generate new business via customer acquisition and marketing campaigns. Insurance companies like Progressive use big data to create new pricing models based on customers’ driving habits. And Citi has created new products — macro economic indexes — based on transactional data.

Companies in a variety of industries have been reaping the benefits of using big data. So how can the airport industry learn from these examples and take advantage of its own big data opportunities?
Health Management Associates, a healthcare facilities company, provides a relatable example. It leveraged data to address a common personnel problem: understaffing clinicians jeopardizes patient care, but overstaffing increases costs. The company analyzed its historical trends to identify visit patterns and combined that information with external data from local hospital communities. By doing so, it was better able to match staff supply with service demand — and lowered costs while still maintaining a high level of patient care. In the airport industry, this same big data method could be applied to optimizing maintenance and customer service staffing — offering similar benefits for airports and travelers.

These methods can also increase productivity, as was the case with Bosch. Big data allowed the engineering and electronics company to increase the maintenance efficiency of its industrial facilities. Similarly, by analyzing data from ground and baggage handling equipment, airports can identify patterns of activity and preplan for fluctuations — reducing downtimes and, as a result, increasing productivity.

The benefits big data can offer the airport industry are clear. The next step, then, is executing a plan to achieve what we call “big data maturity.” Our approach involves three steps: evaluate, establish and evolve.

First, evaluate. Assess what and how big data is relevant to your specific airport, and then prioritize the opportunities. Baseline your data capabilities, project future business demand for data and analytical services, identify gaps and determine how to address them, and build a business case for implementation.

Second, establish. Detail a pilot business opportunity; define the pilot approach and team; and develop metrics to measure its success. In this stage, you may want to identify and implement technology solution partners to aid this effort. Then measure the success of the pilot and create a long-term agenda based on the results.

Finally, evolve. Based on the pilot results, review business opportunities, identify changes to the operating model, define the roadmap, implement any necessary changes, and continue to monitor the plan’s progress.

The time to act on big data is now. In the next decade, data will grow by a factor of 40. There is an immediate opportunity to learn from the big data successes in other industries, and a need to harness the information that’s available to address what matters most for airports: managing costs, avoiding disruptions and improving passenger experiences.