Access to high-quality data empowers success across all areas of the automotive industry. Data lets organisations understand their position within a global market and enables informed decision making. With the adoption of new technologies and a constantly changing marketplace, there are ever-growing sources of data that become available and can influence strategies and company direction.

However, despite this huge rise in access to data, both the volume and significant variation across manufacturers, importers, retailers, and markets creates a huge challenge for data teams trying to translate all this information into actual value.

Before data becomes useful, standardisation is a vital step. It aligns information from multiple sources into a wider data architecture with consistent structures and definitions so that it can be understood and analysed.

The benefits of data standardisation

When done well, standardisation establishes a common framework for organising and representing information that is crucial to analyse data effectively. It improves clarity, reliability and efficiency in both manual and digital analysis.

Some of the key advantages that data standardisation unlocks are:

• It supports understanding

  At the most basic level, transforming data into consistent, uniform formats and definitions makes it easier to understand, identify patterns and use. It facilitates interpretation of content and reduces the time it takes for teams to develop accurate insights.
  
  

• It enables direct comparison 

  When data conforms to a single standard, it’s easier to make clear interpretations and comparisons across different sources. Comparing like-for-like data ensures a fair and accurate evaluation using consistent metrics and parameters.
  
  A key example in automotive today is the charging of electric vehicles. With no accepted standard for measuring the ability to recharge, each OEM uses its own definitions which don’t allow consumers to draw comparison between cars. At JATO, we have standardised specific scenarios to help enable side-by-side comparison.
  
  

• It removes data silos

  Across the automotive industry, teams and organisations create data structures that are aligned to their own operations and business needs. Without an over-arching approach to creating common definitions or data architecture, it means data often stays where it was created. Standardisation allows for data to be brought out of those silos and integrated into a consistent usable form that can be shared; it unlocks the value of data to benefit the wider group.

• It improves alignment between teams

  How many data science or BI teams create their own bespoke calculated fields which then conflict with values presented by other teams? Often analysis from different departments within the same organisation don't correlate, as different definitions or interpretations of data lead to mis-aligned outputs. Data standardisation helps ensure consumers of data from across an organisation start from a shared set of definitions and structures. It means outputs are based on consistent understanding and allows teams to collaborate more effectively.

The impact of AI

One of the big new technologies impacting the automotive industry is also one of the drivers behind the need for data standardisation.

Artificial Intelligence has immense potential to create new insights and content which transform ways of working throughout the automotive supply chain, and the interactions that enable future mobility. While AI can process vast quantities of data and identify correlations, the large language models (LLMs) used still rely on consistent, well curated data to be effective.

AI does not remove the challenge of combining data from multiple different sources into a consistent, consumable form. In fact, in order to be truly useful, AI increases the need on data teams to integrate, master and standardise data to obtain meaningful outcomes.

A single truth for automotive business intelligence

Many businesses partner with a data specialist to normalise the information they work with. Typically, the process involves both automated and manual steps. At JATO, this combination allows for the inclusion of industry knowledge and ensures we add further value for customers, rather than just digital re-processing.

Within mobility data specifically, standardisation can cover a huge range of elements, including:

• Normalising naming conventions and creating clear definitions
• Harmonising technology capabilities across different brands
• Aligning measures used on numeric values
  
  

At JATO, we help businesses make smarter decisions, faster. We are automotive intelligence experts, with more than forty years of experience collecting information from a range of brands and markets, which gives us an advantage when standardising data.

Our specialists have a thorough understanding of both analytics and the automotive market, which means we’re experts in processing data at every step.