How NS International dramatically reduced MTTR to improve the customer journey

NS International Customer Review

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NS International

The rail operator NS International provides sales and service of international inter-city and high-speed train connections to Belgium, France, Germany, and Switzerland. Based in the Netherlands, it is part of the Dutch Railways, also known as the Nederlandse Spoorwegen (NS). The organization operates on the busiest railway network in the world and transports about 1.2 million people every day, with an annual revenue of five billion euros.

Netherlands
Transport

Double the number of travelers

NS International experienced some reputation issues after onboarding a new high speed train that, ultimately, never went into long-term operation. The lack of additional transportation services negatively impacted travelers' experience. NS International set an ambitious goal: to double the number of international travelers by 2030. To achieve this, the company had to change its mindset and focus on improving the customer journey (literally).

Making use of data to optimize customer experience 

To optimize the customer journey, data analysis and data science became crucial for measuring the indicators and outcomes of experiments and regular business. NS set up multiple business-oriented growth teams in a T-shaped profile, supported by seven different DevOps teams. Their hybrid on-premise and cloud IT landscape was monitored by several monitoring solutions - Logz.io, Elastic, Nagios, AWS Cloud Watch and Google Analytics. 

The challenge: gain insights with observability, reduce time to market

NS International was rapidly experimenting and scaling new solutions to deliver the best customer experience. The real problem was shortening the time to market of new initiatives within this complex IT landscape. Platform operations needed to be super-efficient so the majority of the IT resourcing could instead focus on development inside the DevOps teams. To support the rapid experimentation of new initiatives, the DevOps and business-oriented growth teams needed to perfectly align. 

The following questions had to be answered:

  • How to create a shared understanding of the entire IT stack across teams and tools

  • How to create a rapid feedback loop from the business team to the DevOps team?

  • How to get more control over critical business processes?

  • How to decrease mean time to discover (MTTD) and mean time to remediate (MTTR) for major incidents?

  • How to predict the business impact caused by IT operations by using proactive monitoring?

Bringing all data together into one observability platform...

In order to answer these questions, it was imperative for NS International to break down the silos between data generated and stored within their current environment. That's where StackState came in: all of the monitoring data from their existing systems came together within StackState's observability platform. With this data, StackState generated full-stack visibility and shared understanding across teams and tools.

StackState acts as a lens where our data is focused on a single cross-domain perspective and analysis. This ensures higher productivity and rapid experimenting across our Business and DevOps teams, while maintaining stability and business performance.

... and using those observability insights to improve productivity and efficiency

StackState delivered cross-domain actionable insights to the DevOps and growth teams, improving team efficiency and productivity. NS International accelerated its root cause analysis with StackState, which resulted in a significantly lower Mean Time to Discover and Mean Time to Remediate. StackState's own tracing agent enabled end-to-end insight and performance analysis, generating the broadest context possible to make faster (business) decisions.

Google Analytics is integrated into StackState as a top-level business metric. This ensures that the DevOps teams understand the impact they have on important business metrics, for example, the impact on tickets sold per hour.

Their observability implementation enabled rapid experimenting of new initiatives while maintaining stability and business performance throughout the organization, with fast feedback loops across teams. As a result, they have minimized downtime and increased revenue.