Reviving the travel industry through data analytics
A notoriously low margin business, travel and tourism have been one of the most severely affected industries by the pandemic. While the world slowly opens again, the situation appears to be constantly evolving. Uncertainty remains the biggest barrier, with government advice and individual restrictions to certain countries playing havoc with how travel and tourism businesses can resume operations – most forced to do so at a drastically reduced capacity. This is likely to continue for some time yet, and so the industry must act now or fear facing the same fate as Virgin Atlantic.
Data-driven transformation in a predictive and prescriptive way
Whether you're an airline, cruise line, hotel, or tour operator, making the most out of every single booking will be more important than ever – especially in the coming months and years. The adoption of data science and analytics will be key to the recovery of this sector, playing a pivotal role in helping these businesses understand how to reduce costs and generate the maximum revenue while sticking to strict social distancing rules.
The reality is the travel and tourism industry is sitting on a goldmine of data. Sadly, only a fraction of it is used today. When it is used, it’s primarily used in a descriptive way – condensing large amounts of data into more easily digestible takeaways. While this may provide decision-makers with a level of understanding about business outcomes, the information often arrives too late and lacking any creative insights to action properly.
The industry must work its way out of this rut, moving from a descriptive to a predictive and, even, prescriptive data analytics model to uncover critical intelligence. Data science and predictive modelling is the only way to model scenarios and see into the future in order to deliver real-time business recovery plans that do not impact operations too severely. Now more than ever, the industry needs to know more and be able to predict more about what could happen and what will happen, from a strategic to execution perspective. However, making this move, relies on the companies themselves enabling analytics across the business and building a culture of analytics so data-curious workers can extract these insights across the entire analytic process. All-to-often, we see data analytics bogged down in time-consuming data preparation rather than being able to explore data insights, something that can be easily fixed by automating more of these analytic processes.
It also requires travel and tourism businesses to embrace intuitive, self-service technology, which will allow the entire organisation to access these data insights, ask better questions to predict and react to changing demand and make critical data-driven decisions. As well as giving the travel industry a much-needed boost in the short term, taking this approach can also help to reduce customer churn and provide predictive capacity forecasts for the future based on customer engagement, loyalty and personalisation insights.
Sadly, given the current state of affairs, travel and tourism businesses cannot wait. Much like with offices and digital collaboration for remote working, they have found themselves at a tipping point. Establishing a culture of data analytics is no longer a beacon for future success. Instead, it’s a matter of survival. Travel businesses must look for ways to quickly and easily leverage data science and analytics throughout the entire business – placing information in the hands of every staff member to turn them into ‘data workers’ and extract the value out of data assets.
Helping airlines earn their wings in data science and analytics
There are lots of practical ways that data and analytics can help travel businesses streamline their business, from fare price automation and crew staff scheduling to fuel consumption efficiency.
This, I can tell you from experience.
At Alteryx, we're already helping many businesses in the travel industry to embrace a data-driven culture, including a number of major airlines. For example, by using this data-led method, one major North American airline has saved almost $100m in fuel efficiency. It was able to do this by dramatically increasing its fuel forecasting efficiency. Employing more than 24,000 pilots and flight attendants, the company has also improved the accuracy of its crew scheduling forecasts, enabling it to save hundreds of thousands of dollars in extra costs that previously arose from the failure to anticipate daily changes.
Similarly, a UK budget airline has been able to improve its route planning accuracy to save fuel and fly more efficiently. The carrier, which usually runs 1,400 flights per day in peak summer, is now able to continuously analyse flight data monitoring to pinpoint extra efficiencies in taxiing, take-off, cruising, and landing.
Another UK airline is using a similar method to take care of pricing and demand analysis, based on market dynamics and competitor pricing. This has enabled it to reduce its analytical process down from 19 hours to just under 1 hour. As a result, the airline is able to build statistical and predictive modelling to ensure that it's pricing every single flight at the correct value and not losing money or running flights with too many empty seats.
This major airline has also used data analytics to tailor its email marketing to make it more targeted. For example, the customer's postcode is used to automatically select their nearest airport to include in marketing emails. Data analytics can also help travel businesses to find out more about their customers. In this way, one national airline in Central America has improved customer insight by analysing its customer loyalty scheme. The revamped analysis has enabled it to customise flight schedules and save countless hours of employee time.
These are just a few examples of how a self-service analytics platform can help airlines. Other real-world use cases include revenue forecasting, enhanced decision-making for targeted overbooking, cleaning rotation, and scheduling - the latter being especially important right now. While most airlines face a similar range of challenges, a data-driven platform can also be tailored for niche use cases.
And it's not just airlines that can benefit from this approach. A French travel management company uses the system to streamline its operations. Booking plane, train, and hotel reservations on a single platform, its biggest challenge is integrating data from various sources and creating invoices in different formats to suit customer needs. Previously, it took two full-time employees to consolidate these complex invoices, but now it takes just one person one day of the week to complete the task, freeing up their time to generate more revenue.
The benefits of cultivating a culture of data and analytics can help many areas of the travel and tourism industry, including airports, hotels and restaurants. Whether its automating seating and room prices or optimising staff and supplies for extra cleaning and hygiene rotation scheduling, data will help these businesses to build themselves back up and enable them to stay more resilient in future.
To do this, however, requires finding the right mix of democratising data, automating business processes, and elevating human ingenuity to turn every data worker into a discoverer of marginal profitability. In tough market conditions, this combination will be ever-more vital for transformative business outcomes – especially as the pandemic ebbs and flows in different locations.
Automating business processes to grant even novice-level knowledge workers with direct self-service access to business-critical data insights at speed will enable travel businesses can get more from their key resources – data and people. Freeing up time for people to learn more skills to answer bigger challenges and apply the data-driven insights they gain will be key to making the most out of every single seat and booking to enable travel businesses to get back on their feet.
The power of analytics extends far beyond the travel and tourism industry’s ability to weather the storm but can serve as a critical driver to identify and prepare for future vulnerabilities.
By Alan Gibson, VP EMEA, Alteryx
SAS: Improving the British Army’s decision making with data
SAS’ long-standing relationship with the British Army is built on mutual respect and grounded by a reciprocal understanding of each others’ capabilities, strengths, and weaknesses. Roderick Crawford, VP and Country GM for SAS UKI, states that the company’s thorough grasp of the defence sector makes it an ideal partner for the Army as it undergoes its own digital transformation.
“Major General Jon Cole told us that he wanted to enable better, faster decision-making in order to improve operational efficiency,” he explains. Therefore, SAS’ task was to help the British Army realise the “significant potential” of data through the use of artificial intelligence (AI) to automate tasks and conduct complex analysis.
In 2020, the Army invested in the SAS ‘Viya platform’ as an overture to embarking on its new digital roadmap. The goal was to deliver a new way of working that enabled agility, flexibility, faster deployment, and reduced risk and cost: “SAS put a commercial framework in place to free the Army of limits in terms of their access to our tech capabilities.”
Doing so was important not just in terms of facilitating faster innovation but also, in Crawford’s words, to “connect the unconnected.” This means structuring data in a simultaneously secure and accessible manner for all skill levels, from analysts to data engineers and military commanders. The result is that analytics and decision-making that drives innovation and increases collaboration.
Crawford also highlights the importance of the SAS platform’s open nature, “General Cole was very clear that the Army wanted a way to work with other data and analytics tools such as Python. We allow them to do that, but with improved governance and faster delivery capabilities.”
SAS realises that collaboration is at the heart of a strong partnership and has been closely developing a long-term roadmap with the Army. “Although we're separate organisations, we come together to work effectively as one,” says Crawford. “Companies usually find it very easy to partner with SAS because we're a very open, honest, and people-based business by nature.”
With digital technology itself changing with great regularity, it’s safe to imagine that SAS’ own relationship with the Army will become even closer and more diverse. As SAS assists it in enhancing its operational readiness and providing its commanders with a secure view of key data points, Crawford is certain that the company will have a continually valuable role to play.
“As warfare moves into what we might call ‘the grey-zone’, the need to understand, decide, and act on complex information streams and diverse sources has never been more important. AI, computer vision and natural language processing are technologies that we hope to exploit over the next three to five years in conjunction with the Army.”
Fundamentally, data analytics is a tool for gaining valuable insights and expediting the delivery of outcomes. The goal of the two parties’ partnership, concludes Crawford, will be to reach the point where both access to data and decision-making can be performed qualitatively and in real-time.
“SAS is absolutely delighted to have this relationship with the British Army, and across the MOD. It’s a great privilege to be part of the armed forces covenant.”