Intelligent Forecasting - Network Rail Infrastructure

Using Intelligent Forecasting to transforming reporting for Network Rail Infrastructure Projects.
As the capital delivery arm of Network Rail, Infrastructure Projects (IP) spend £100m per week upgrading and renewing railway assets across England, Scotland and Wales.

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The challenge

Acting as the link between a number of operational divisions they deliver work through a network of contractors, while balancing the budget each year in a much scrutinised and heavily regulated sector.

The client wanted to vastly improve their reporting and intelligent forecasting capabilities. Their incentive for doing this was to avoid potential overspend or underspend, to create a single version of the truth across their business and identify issues earlier while reducing the cost of assurance activity.

Work had already begun on improving their reporting capability, but they were being held back by the limitations of their legacy architecture.

How we did it

Using our Intelligent Forecasting Programme we worked with Network Rail’s existing tools, and selecting the most appropriate applications for the job, we developed a fully scalable data architecture to deliver real-time reporting of all their data in a single environment. At the client’s request this was a fully secured multi-cloud solution.

We successfully integrated a complex array of source systems and proprietary platforms relating to capital programmes and routine maintenance data.

Intelligent analytics was built-in via a scalable Databricks platform, and a Power BI reporting environment was integrated with existing security controls, enabling reporting consumption and analysis.

The foundations were also put in place for the client to build an improved data glossary.

We developed and deployed our solution quickly as a proof of concept to engage the business, safe in the knowledge that everything was rapidly scalable.

The results

  • Within three months of the project going live, the client saw a 54% improvement of ‘in-year forecasting’ and identified significant unexpected underspend.
  • Enhanced board and management-level reporting, less need for excessive cleansing activity and improved confidence in the quality of the data.
  • Rapid improvement in process compliance through greater transparency across the project management lifecycle.
  • A host of actionable insights unearthed.
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