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Case Studies
British Sugar
Sweet success at British Sugar by embracing advanced technology
The winning mix of data and AI to optimize operations and preserve technical expertise
British Sugar is the sole processor of the United Kingdom’s sugar beet crop and has been an essential contributor to the country’s food industry for over 112 years. Supplying over 50% of the UK’s sugar, the company has a long-standing history of producing high-quality sugar sold to customers and consumers around the world.
With innovation in its DNA, British Sugar is continuously looking to build upon and adapt its operations to maintain its competitiveness on the global sugar market. To take the business to the next level, it became pivotal to use the latest digitization capabilities, alongside overcoming a few key challenges around the capture of embedded organizational and technical knowledge.
To start, the company wanted to change how decisions were made by becoming more reliant on thorough analyses and data-driven choices—a process many organizations are undergoing. And, although the company had already integrated automation and 4G technology in its operations, some processes were still manual. For example, locating valuable knowledge and matching information that is required to make decisions was manually time-consuming, which lead to errors and missed opportunities.
Historically, decision-making at the company relied predominantly on the expertise, intuition and experiential knowledge of practiced employees who had been with the business for decades. This technical knowledge was often passed down through training schemes, shared experiences and stories. And, while this approach has been effective for more than a century, contemporary technology and the approaching retirement of many employees presented an opportunity for change. To stay ahead, British Sugar needed to embrace new frameworks that codify and scale experience across all data, leveraging its ability to adapt and thrive in a rapidly changing market.
Moreover, the company also faced departmental isolation, where different teams worked independently, resulting in repeated work and slowed processes. In terms of mechanical malfunctions, while they were few and far between, the company recognized the potential for unplanned downtime to impact production. To mitigate this risk, British Sugar considered implementing predictive maintenance strategies. At last, another aspect the company wanted to address was the escalation of costs that were intensified by erratic climate effects, impacting crop outputs and transportation effectiveness.
British Sugar recognized that technology held the key to unlock its full potential. So, the company partnered with IBM to create a data-driven organization powered by Artificial Intelligence (AI) and build on existing automation and 4G infrastructure. Working closely with IBM Research® and the IBM Consulting® AI and Analytics practice, they deployed a business transformation framework to address its challenges.
The first step was to develop a digital twin of the early stages of its supply chain lifecycle, powered by Microsoft Azure OpenAI service and hosted on the Microsoft Azure Cloud Platform. While British Sugar intended to apply this process to the entire business network, it currently focused on the “make” part of the supply chain. Through this smart factory digital twin, the company was able to simulate real-world scenarios and optimize production without disrupting operations. By leveraging advanced data modelling and analytics, British Sugar significantly improved its extraction and energy processes, material management and quality control. The company also optimized water management, production scheduling and scenario planning.
Simultaneously, British Sugar went on to create a minimum viable product (MVP) for predictive maintenance and prevention of equipment failures by using IoT sensors, machine learning algorithms and data analytics. As a result of this proof of concept, the company reduced failures and downtime from rotating equipment.
As a next step, British Sugar plans to incorporate the MVP into a full-scale digital twin control tower across all factories. The goal is to establish a centralized control tower that is powered by AI by 2025 and monitor predictive maintenance, crop volumes, supply chain plans and operational performance.
By integrating its models directly into data control systems, British Sugar managed to combine operational data with AI. This approach strengthened organizational design and empowered fewer experts across the board by augmenting knowledge search and quickly summarizing thousands of data points for rapid interpretation of complex documentation.
Pioneering digital twin technology for sweet success
Having built one of the first digital twins in sugar manufacturing, British Sugar is at the forefront of technological innovation in the industry. The company has seen a 20% reduction in the duration spent manually understanding data and information, due to the use of advanced technology and automation of tasks. This transformation improved important decision-making in time-sensitive environments. Now, its employees are free to focus on high-value tasks, including root cause analysis, proactive management and more. Additionally, the digital transformation has also enabled better visibility into supplier inventories, reducing stockouts and enhancing overall supply chain reliability—a significant advantage over manual stock checks.
The connected systems that were built also eliminated silos and boosted production efficiencies, which allowed real-time adjustments and a reduction in manual interventions. Autonomous capabilities have been a gamechanger, cutting unplanned downtimes and reducing the average time to resolve production issues by 20%. The company also saw advances in supply chain reliability. Thanks to predictive analytics, real-time data sharing with suppliers improved logistics planning and reduced costs around raw materials used in purification processes by 10%. These innovations will help keep factories fully supplied with sugar beet, even during disruptive weather.
The advancements it made will also lead to less waste and rework, improving product quality consistency and its sustainability quotient. Decision-making time came down by 25% with real-time data insights, and operational setbacks decreased by 50% using the supply chain digital twin in financial and process "what-if" analyses.
With the introduction of extensive modelling, British Sugar has assimilated the knowledge from senior staff and mitigated the risk of technical knowledge loss. After integrating a subset of its models directly into data control systems, fully autonomous adjustments to additions in the sugar purification process achieved effective results, increasing throughput and reducing raw material costs. Now, with the technology to transform how the company disseminates its information and data, British Sugar expects to almost halve the time it takes new employees to become expert sugar makers. This allows for a smoother transition of knowledge and reduces the burden on its experienced decision-makers, preserving critical technical knowledge and ensuring a more sustainable future for the organization.
British Sugar is poised for sustained performance improvements and long-term competitiveness by establishing a framework for continuous improvement and using machine learning and AI capabilities to adapt to changing conditions. The company has big plans to continue pushing the needle on what is possible, driving innovation and excellence in the sugar industry.
Founded in 1912, British Sugar (link resides outside of ibm.com) is a subsidiary of Associated British Foods plc (ABF), and the sole processor of UK’s sugar beet crop. The company works in partnership with over 2,300 growers to process around eight million tonnes of sugar beet, producing up to 1.2 million tonnes of sugar each year. With its integrated approach to manufacturing, British Sugar transforms its raw materials and byproducts into various products, including animal feed, lime for soil conditioning, and soil for landscaping. The company creates more than 27 different sugar and co-products and produces less than 200 grams of waste for every tonne of sugar beet processed.
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