AmRest becomes a data-driven business with SoftwareOne and Azure

Building up the power brands

Since 1993, AmRest has steadily built its leading position as an multi- brand restaurant chain operator. It brings people's favourite brands, such as KFC, Pizza Hut, Burger King and Starbucks, to customers around the world, from Central and Eastern Europe to Spain, France and China. 

The company started with a single restaurant in Wroclaw, Poland. Today, AmRest operates more than 2,100 restaurants in 21 countries and employs more than 45,000 people. With the growing complexity of the business, the company decided to invest in new technology solutions that would help it make the most of the data coming from its ever-expanding network.

The growing potential

AmRest generates hundreds of gigabytes (GBs) of structured data every day. As the company has grown both organically and through acquisitions, its rapid growth has created a broad portfolio of data processing platforms that have required significant integration efforts. Information is collected from multiple systems in different areas, making it very difficult to reconcile.

The company comprehensively monitors each business area, empowering employees by holding them accountable for areas of their performance and leveraging their data assets in the process. Getting the right information to the right people at the right time is critical to making data-driven decisions.

With the successful growth of the company's online channels, the need to capture and effectively process unstructured data has become more relevant across virtually all departments, from marketing to operations. Understanding customers' eating habits and overall brand perception allows the company to take a more personalised and individual approach to each order and marketing campaigns, delivering a unique, customer-centric experience.

Taking the first steps towards a new data strategy

Understanding the potential of its data and the limitations of its current systems, the company decided to strategically reinvent its reporting and create a single, consistent data platform where everyone could access the information they needed. 

The aim was to simplify its operations by bringing together data from all areas into a single platform, enabling easy access and analysis of data across the business. 

The company considered three main scenarios to achieve this goal: 

• Extend the existing on-premises data platform and grow its own infrastructure 
• Move the existing data platform to a public cloud IaaS model (lift & shift) for better scalability and availability
• Develop a new cloud-based data platform from scratch 

In response to AmRest's request, SoftwareOne, in close collaboration with Microsoft, proposed a modern data warehouse architecture using Azure Data Services. Following a successful proof of concept, in which the company evaluated solutions from leading BI vendors, the company decided to enter into a strategic relationship with Microsoft and selected SoftwareOne as its implementation partner.

As with any new technology, the Azure cloud raised some concerns. The issues of managing the cloud, its privacy or compliance often raise questions. However, a presentation on the clear benefits of building an infrastructure using Azure Data Services allayed AmRest's concerns. The presentation demonstrated:  

• PaaS services that require less administration and management from infrastructure staff 
• No maintenance required (version upgrades, patches, etc.) 
• Scalability, HA and DR capabilities available out of the box 
• Simple and fast deployment and configuration 
• Low cost of entry 
• Pay-as-you-go pricing 
• Some services may be suspended when not in use (Azure SQL DW, Azure Analysis Services) 

Identifying the project goals

AmRest wanted an infrastructure that could adapt and scale with its rapid business growth, increasing data volumes and growing user base. The company wanted to create a single source of truth that could be accessed quickly and easily by literally every employee.

Flexibility

The first goal of the project was to provide sales, marketing and operations with a high performance data model that would allow users to slice and dice any sales-related data at the touch of a button, while maintaining clarity and convenience. All day-to-day reporting, from analysing key performance indicators such as sales revenues, number of transactions, average transaction value, to ranking best-selling products or meals, must be quick and easy.

Performance

Performance was paramount for AmRest. The solution had to support the rapid creation of rankings: employees, restaurants, regions, districts based on sales, in multiple dimensions such as time, geography, sales revenues and ordering channels, etc. As the data relates to different countries, the rankings also had to support daily fluctuations in exchange rates, which had to be brought to a common denominator.

Reporting

The company had a working BI solution prior to SoftwareOne's involvement. Each user had access to an online portal to generate ad hoc reports on demand. The core reports were generated by the system as static reports and sent to subscribers each morning. As each user received multiple reports, this quickly added up to several thousand files. The generation phase was preceded by data collection, reconciliation and conversion.

As a result, the system was running at capacity and required maintenance and support. In addition, static reports provided end users with limited business insight. Requests for specific information had to be handled by dedicated teams. The new system needed to provide simpler and more efficient reporting functionality.

Adoption

The solution developed needed to measure adoption across the organisation. Data was to be collected from services such as Azure Log Analytics and Power BI and fed into a dedicated report showing how each service was being used and the increase in the overall user base.

Getting usage statistics on the new solution is useful for determining ROI, but also for identifying areas where more training or support may be needed.

The previous system supported millions of transactions per day. The new solution must be able to handle at least several times that number over the next three years. During that time, it would also need to perform efficiently for thousands of users and scale to several thousand more. AmRest expected the solution to support thousands of concurrent user sessions at any time, with consistent performance.

The data warehouse currently holds several TBs of data and is expected to grow at a rate of around 40% per year. Some of the data comes from non-integrated point-of-sale (PoS) systems, which the solution also needs to support. The new infrastructure is evolving in line with new business requirements, but the agile approach allows changes to be introduced on an ongoing basis.

Ultimately, the new data warehouse is expected to add nearly one hundred GB of raw data per day, which will be made available to business users in 30-minute packages loaded from PoS systems.