London North Eastern Railway Builds a Fast Track to Insights with Alteryx + Tableau

London North Eastern Railway (LNER) knows a thing or two about getting millions of passengers efficiently from point A to point B, and it does the same for millions of data points.

The British train company carries over 21 million passengers a year, with about 150 train services a day and five trains an hour that travel to key destinations throughout England and Scotland.

It’s a lot of trains to keep on track, and Rob Taylor, Business Analysis Manager at LNER, helps the company uncover insights that keep LNER informed and nimble in the fast-paced railway industry.

Re-Routing the Data Strategy: From Limited Spreadsheets to Rich Visuals

LNER’s analytics team started their journey in Excel, with one analyst doing manual analysis and reporting limited to the 65,000 rows of the spreadsheet format. The data was only updated weekly, and it was highly aggregated – which meant the LNER team didn’t have the detailed, real-time information it needed to react more proactively to a rapidly changing industry.

LNER then adopted Tableau to aid visualization and make insights more accessible. Rob found that Tableau helped non-data-savvy employees get more interested in data findings.

“With Tableau we found we could really visually show them the data and give them the ability to see what they were looking at, and understand what changes they needed to make,“ Rob said.

But Tableau introduced new challenges – once people were more engaged in the data, they had more questions and craved deeper insights (a good problem to have as an organization improves its analytic maturity). LNER needed an analytics platform that could answer those deeper questions.

Alteryx Designer and Server: The Engine Powering the Train

LNER selected Alteryx for its ability to process large volumes of data, handle different data types, and power through complex analytical challenges. With easy connectivity to Tableau, Alteryx provides the perfect complement: LNER can leverage the power of Alteryx to discover, prep, blend, enrich, and analyze data, before sharing insights at scale with beautiful Tableau visuals.

If the data process is a train, Tableau is the railcar serving the passengers, while Alteryx is the powerful ingestion, transformation and analytics engine.

“This changed the business massively,” Rob said. “Alteryx is the power behind the scenes, as our team calls it, because it gives us the ability to manipulate everything we want to do.”

Rob quickly started seeing the positive business impacts. Because Alteryx removed the ETL constraints and saved a huge amount of time, the team was able to go from weekly reporting to daily – and with better insights.

“It gave us a bigger level of detail, it was more data, it was more often, and it was easier for people to compare things and get the answers to the questions they had,” Rob said.

But once again, there were more people consuming data, which led to more questions and more demand for fast results. So the next logical step was to get Alteryx Server. Server allowed the LNER team to automate many of the processes they were running manually, including cleansing and refreshing data automatically.

“The analysis was produced and fed back to the business before analysts even got into the office in the morning,” Rob said.

From Door Sensors to Tableau Dashboards in Minutes

Rob has found many creative ways to combine Alteryx and Tableau to get new insights. One recent example of the cutting-edge use cases LNER takes on with Alteryx is analyzing door sensor data.

A forward-thinking railway company, LNER has adopted technology that improves its ability to gather information, like high-tech Hitachi trains that make it possible to collect IoT data.

LNER has sensors on the external and internal doors that show passenger traffic as they get on and off the train or move between cars. The data is sent every time a train leaves the station, and the raw JSON file is sent to an AWS S3 bucket.

The team set up three Designer workflows that leverage tools like Amazon S3 Upload and Tableau Output, and custom-built macros. The workflows check whether a file is new, puts it in a usable format, joins the files with additional data sources like train types and bookings, and pushes to Tableau Server.

The Alteryx workflows take the JSON data from messy, semi-structured, unreadable text, to clever, interactive visualizations in Tableau, like a route map with colored dots that show the status of each station.

With this process, LNER can refresh the Tableau visuals every few minutes, giving LNER staff the information they need at a glance to take actions — like guiding passengers along the platform to spread them out based on which coaches are more crowded. This is especially helpful for staying on the strict deadlines for running trains; increases in delays can start costing thousands of pounds!

“The ability to have an Alteryx workflow that can run every five minutes with the latest data refreshed, push straight to Tableau and have the Tableau feeding off that live data, it just means that the staff and teams are able to make real-time decisions if they need to,” Rob said.

Helping Train Staff Check for Fraud at 125 MPH

Here’s another example that Rob calls “fraud checking at 125 mph,” because that’s how fast the LNER trains can travel. LNER has guest train passes that are allocated to people who need to do work for LNER, for instance, or need to travel on LNER trains to an office.

Before creating a process with Alteryx, there was no efficient way of tracking who was using the passes, how many passes were out there, or how much it was costing the business.

The analytics team stepped in, using Microsoft Forms for guest pass requests to make it easier to collect data in a standard format. Using a Designer workflow, the team brings in the form data, parses it, combines it with other relevant data like dates, and joins approvals with the corresponding guest pass details before outputting the information to Tableau.

Staff on the train can click a link to Tableau, which opens up the PDF with the signed approval that shows the guest pass details. Thanks to Alteryx and Tableau, LNER staff can access information right from their mobile device, prevent incorrect use of the guest pass, and answer questions for passengers – all while going 125 mph.

The Next Stop: Exploring New Use Cases in Data Science and Machine Learning

The LNER team is always looking into more data science use cases, like forecasting and geospatial analytics. LNER covers a vast geography with a broad spectrum of stations across England and Scotland, and Rob wants to dig into how the team could use spatial insights from Alteryx to explore GPS data. LNER also has a new machine learning team that can start getting up to speed on Alteryx.

Ready to follow LNER’s route? Watch the webinar to hear more about how LNER combines Alteryx and Tableau to solve train-mendous data challenges.