British Bakels, improves forecast accuracy through sofco Planning

British Bakels, a manufacturer and distributor of tailor-made ingredients, improves forecast accuracy through sofco Planning.

British Bakels manufacture and distribute a wide range of high-quality bakery ingredients to the commercial bakery market, some of which are tailor-made for industrial and instore bakeries, while others are specifically developed for the craft and foodservice sectors.

Located in Bicester, Oxfordshire, British Bakels commenced production in 1990, and now employ over 3,000 people worldwide and have over 2,000 products.

The Challenge

British Bakels needed a powerful forecasting tool that combined automated forecasting capabilities with a user-friendly, collaborative interface. The goal was to enable demand planners and account managers to develop and review forecasts quickly and efficiently from any location. The solution had to be a cloud-based platform accessible across multiple devices to ensure seamless remote access for users. It also had to be designed to clearly differentiate roles between demand planners and account managers, facilitating streamlined workflows and enhancing forecast accuracy.

The system had to enable Demand Planners to develop, produce, and manage the forecasting process by providing tools for analysing historical SKU sales data, reviewing calculated statistical forecasts, and evaluating alternative statistical forecasts to identify the most accurate forecast. Additionally, the system needed to allow Account Managers to review forecasts for their assigned customers, incorporate customer-specific knowledge, and make final adjustments to forecasts, including adjustments for commercial factors and planned promotions.

The system needed to support managing demand across multiple time horizons by enabling forecasts to be viewed in both short-term and long-term windows, providing full visibility of SKU demand. It had to allow users to make forecast adjustments within the appropriate forecast window to effectively manage and adapt to internal and external conditions. Additionally, the system needed to provide flexibility to accommodate changing conditions, enabling users to evaluate different scenarios and assess the impact of adjustments to support more informed and improved decision-making.

Why sofco?

British Bakels chose sofco as their strategic partner due to sofco’s extensive experience in the Food Manufacturing industry, which instilled confidence in their team. They appreciated the knowledgeable and dedicated team’s ability to clearly define the project scope and deliver practical, actionable solutions through sofco’s transparent and effective implementation approach.

Additionally, the user-friendly nature of the software played a significant role in their decision. During demonstrations, British Bakels was impressed by the intuitive design, seamless functionality, and overall look and feel of the solution. They were particularly inspired by the collaboration system, which they believed could be easily adopted by account managers in the field, enhancing communication and operational efficiency.

The Solution

To ensure a rapid deployment, the standard sofco Demand Planning Template was utilised for both functionality and user interface design. This template was presented during the Gap Analysis workshop sessions, where British Bakels’ specific requirements regarding data structures and user collaboration were identified for the specific configuration of the model.  Data structure and gap analysis defined:

Data Structures

The product, market, location, and time dimensions, along with their hierarchies and attributes, were aligned with British Bakels’ requirements. This setup enables top-down and bottom-up forecast adjustments within the data slicers. Additionally, it provides the ability to filter data by different Account Managers, as well as other attributes within the Product, Market, and Location hierarchies.

Forecast Accuracy

The system automatically calculates absolute error, percentage error and percentage bias measured at the SKU lead time. The Slant Chart dashboard displays forecast stability and illustrates how the forecast evolves between each version of the forecast cycle.

With the use of the configured data slicers, forecast accuracy can be seen to display accuracy across each site or view accuracy for each Account Manager.

Forecast Collaboration

The use of the Forecast Collaboration/Commercial Review Dashboards was imperative to the success of the project and involved both Commercial and Account Managers within the business. Primarily British Bakels develop and make forecast adjustments at the SKU | Customer | Site level.

Across the Collaboration Dashboards and Commercial Review Dashboard, users utilise the top-down/bottom-up functionality where these adjustments can be made at an aggregated level and disaggregated to the SKU | Customer level, and vice versa.

The below Dashboards were configured in line with British Bakels requirements:

• Forecast Collaboration by Customer: This feature enables users to view forecasts for each customer, including their associated SKU combinations. Presented on the dashboard, users can compare forecasted quantities against previous years (Y-1 and Y-2), as well as review forecast values and margins. Additionally, users can make adjustments based on their customer insights and market intelligence, fostering a collaborative and informed forecasting process.
• Forecast Collaboration by SKU: An alternative option for users is to view the forecast by SKU, where the forecast can be viewed by each SKU and its associated Customer combinations. Displayed in the Dashboard, users can review the forecasted quantities in comparison to Y-1 and Y-2 and are also able to plan/develop promotional activity.
• Commercial Review: The use of the Commercial Review provides a view of the published forecast from the historical four-week horizon. In addition to the Forecast Collaboration by Customer/SKU Dashboards, users can make promotional adjustments in this Dashboard and both percentage/absolute forecast adjustments.

Product Linking

The Data Linking functionality allows for an improved process to forecast new SKUs with no sales history. Within the application, users can link sales history from a SKU and attach this sales history to a new SKU. This functionality can be used when a SKU is replaced by a new version/iteration.

This function has provided an additional benefit to the forecasting process as users can copy the complete sales history from a SKU or select a specific time range of sales history to be copied to the destination SKU.

Personnel Engagement and Training

The success or failure of a project like this often hinges on user acceptance of the new system. Experience shows that this can be particularly challenging when Account Managers are asked to interact with a planning system.

To address this, the project team first engaged closely with the day-to-day users of the application. Their goal was to understand what data and information users needed from the system, as well as their key requirements for how the system could enhance the development and quality of forecast outputs. These requirements were then communicated to sofco, who configured the system accordingly during the implementation process.

Account Managers play a crucial role in maintaining both the development and quality of their forecasts, and they are held accountable for the final, published forecasts.

Since its implementation, the system has had a positive impact on British Bakels. The improved visibility of data and a more user-friendly interface have made interactions smoother. Both Planners and Account Managers have successfully adapted to the new system and are increasingly comfortable using it, laying the foundation for ongoing improvements and greater confidence in the forecasting process.