In this three-part blog series, we’ve been looking at your options when it comes to your SAP data and where to house it. In this final part, we share how INEOS Automotive structured its SAP data strategy as it brought a brand new 4x4 vehicle to market, disrupting the industry and planning for a future of AI, IoT and machine learning.
It’s not often that a company decides to build a new vehicle and brand from the ground up to challenge the long-established players in the market. But that’s just what INEOS Automotive did. Following a meeting at the Grenadier Pub in London in 2017, founder Jim Ratcliffe decided to create a new off road, 4x4 vehicle to challenge long standing players. He invested £1 billion pounds and set to work creating the Grenadier, a rugged off-roader with excellent reliability and great looks. Every aspect of the company’s engineering, manufacturing and commercial information technology was meticulously chosen to meet the needs of a dynamic and ever-changing business landscape.
From the start, the company chose SAP Hana and SAP Cloud for Customer as its ERP and CRM systems respectively, using the finance, inventory management, order to cash, procure to pay, warehouse management and CRM modules. The question was what to do with the data?
Sailash Patel was brought in as a head of data and analytics. As this was a new vehicle the company had no insights into what sales would be like or what the vehicle could do. He had to design a data strategy for something that didn’t yet exist. Added to that, budgets were tight and they did not have a lot of time, with just two years before the car was to be launched.
With a blank piece of paper, he kept his data strategy simple, focusing on four key themes:
Using this as a guide, he looked into solutions that were the best fit to deliver on the capabilities needed. At the time, while the car concept was there, the manufacturing hadn’t been devised. Multiple decisions were being made concurrently with pressure on the procurement team as the car accelerated towards production. One of the ideas discussed was to have a connected car - potentially with real-time analytics - which would generate masses of unstructured data that would have to be integrated with the structured corporate data in the SAP system.
So, with an SAP infrastructure that had already been provisioned, a lean team, small budget, the need for structured and unstructured data that could scale as the company grew, and fast time to market, Sailash worked with an Enterprise Architect to devise a data analytics solution strategy that would work closely with SAP.
SAP Data warehouse Cloud (now DataSphere) wasn’t considered because it was not natively built for the cloud, is not designed for unstructured data and they wanted to avoid vendor lock in. After conducting an RFP, the overwhelming response was to use Data Factory and Data Bricks on Azure. But this would be a multi-year, multi-million pound project. INEOS didn’t have the time or budget for that.
Then Sailash discovered Qlik which offered out of the box Extract, Load, Transform (ELT) functionality for procurement, sales, and order to cash SAP accelerators. These offered incredible near real time replication technology. However, as their SAP was already heavily customised, he knew he would need support to customise the accelerators.
Next, where to house the data? Instead of using Data Bricks, he opted for Snowflake. The elastic cloud compute capabilities of Snowflake and pay as you go service, aligned with his strategy and would enable the company to get the functionality it needed in the early stages, while being able to scale once connected vehicles became a reality and terabytes of IoT data would need to be stored. The fully managed SaaS nature of Snowflake also meant they wouldn’t need a host of database administrators to run it.
With the right technology selected, Sailash needed a partner to make it a reality. Catalyst - as both a Qlik and Snowflake partner, and with SAP consultants with knowledge of the back and front end of SAP on their team, Catalyst proved the perfect partner for the project.
Catalyst worked closely with the departmental directors to determine the essential performance indicators required for running the business smoothly. Through reverse engineering the business processes, Catalyst smoothly transitioned from visualising data to fulfilling data mart and data warehouse requirements, ultimately returning to the original source data in SAP.
Despite having a small IT team and strict deadlines, Catalyst efficiently ensured that data and valuable insights were promptly delivered to the business users while meeting the complex needs of INEOS Automotive. Doing this empowered experts across all divisions of the business to make commercial decisions quickly and effectively.
By focusing on business outcomes, Catalyst enabled INEOS Automotive to:
Within six months, Catalyst delivered a fully integrated cloud data warehouse solution for procurement. It also enabled INEOS Automotive to analyse procurement and sales information prior to the launch of the Grenadier across Europe. And it created a repeatable solution implementation approach that could be used across other INEOS business lines that utilise SAP as a data source.
As the company grew, Sailash did not want his department to become a bottleneck for analytics. He wanted to give data analytics capabilities to end users to build their own reports. Using accelerators built by Catalyst and linking to Qlik for procurement, finance, sale and after sales, the teams can now self-serve, building their own reports.
The next priority area is on building a marketing data warehouse with a huge push on marketing and after sales capability. Extracting data from SAP Cloud for Customer will be sped up with a Qlik native connector. However, as there is no out of the box analytics accelerator from Qlik, Catalyst will help INEOS Automotive built a bespoke solution.
Today the company has the Grenadier, the Quartermaster and Fusilier vehicles sold across three continents and the scale of data is growing. The team is looking ahead to the future as the connected vehicle with an app and IoT data become a reality. In addition, they want to provide AI-driven apps, provisioning through Qlik or Snowflake using Copilot and Large Language Models.
As Sailash said when asked what his biggest success factors were, it came down to three things: Choosing the right technology solution, at the right price with the right partnership.
“INEOS Automotive has been collaborating closely with Catalyst since 2021. Throughout this period, they have successfully executed various data analytics projects, handling everything from data engineering to data modelling, and meeting the analytical needs of different departments on a case-by-case basis. The collaboration between INEOS Automotive and Catalyst is fantastic. Catalyst have an excellent grasp of the solution architecture and have consistently delivered impressive results. Their exceptional performance has led me to recommend Catalyst to other business lines within the INEOS Group,”
Sailash Patel, Head of Data and Analytics at INEOS Automotive
If you are currently modernising your SAP systems and need assistance with your SAP data strategy so that you are future-ready, contact Catalyst.