We understand that different organizations face different challenges. That is why our AI based solutions are tailor-made to suit your specific needs.
Efficiency and Scalability: Customised solutions offer more efficiency and scalability, with an eye to the future of the organization.
Easy integration into desired environments:Custom applications offer the ease of integration within desired environments.
Flexibility:Typical drawbacks of commercial software solutions can be subverted and allows you the freedom to license or sell the software in the future.
Empowering Intelligence, Driving Insights
Unlocking the potential of AI to revolutionize your decision-making process
The client previously utilized the traditional BlueYonder (JDA) platform for demand forecasting, which solely relied on historical sales data and manual biases. To address this limitation, we implemented a two-phase approach for developing a Demand Forecasting Model, aiming to achieve the following objectives:
Phase 1:
Establish an integrated data warehouse by amalgamating data from various sources, facilitating Short-term Demand Forecasting models and Long-term Planning (3 months) and Reporting requirements.
Conduct data exploration, including external sources such as CRA, IRI, and Salesforce
Perform data cleansing and transformation.
Create standardized relational database tables on a cloud platform.
Automate the data loading process.
Phase 2:
Analyze market trends and identify lead indicators to forecast long-term sales growth or decline.
Develop a five-year forecast with a rolling 12-month projection.
This initiative significantly reduced the client's reliance on salespeople for monthly customer/SKU level forecasts and streamlined the annual forecast process for both sales teams and the FP&A team.
Business Need:
The client's current forecasting platform achieved 72% accuracy in 2019 and declined to 65% in 2020
Inaccurate demand forecasting resulted in elevated finished goods inventory expenses, tying up capital, and negatively impacting On Time In Full (OTIF) metrics with critical customers due to erroneous production schedules.
Increased transportation costs were incurred as products often required expedited shipping to meet client Service Level Agreements (SLAs) or to avoid fines resulting from non-compliance.
Benefits Delivered:
Substantial enhancement in forecast accuracy compared to the existing model.
Accessible across regions and platforms.
Provides actionable insights for demand managers, catering to short and long-term needs.
More cost-effective to maintain than the current model.
User-friendly and easily adaptable for demand managers to utilize.
Drastic reduction (90%) in salesperson's time required for monthly customer/sku level forecasting.
85% reduction in time needed to prepare the annual sales forecast for both salespersons and FP&A analysts.
AI-driven Food Formulation
The BCD AI team collaborated closely with food technologists and scientists to establish a standardized communication framework, including defining terms like "muffin" to ensure clarity between human experts and AI systems. This seemingly simple task for food scientists required careful consideration to enable AI comprehension. This effort extended to scrutinizing ingredient definitions, processes, and other variables within muffin recipes, fostering a mutual understanding for both humans and AI.Once this groundwork was laid, the experimentation phase commenced. The developed model successfully analyzed thousands of recipes digitally, culminating in the recommendation of 38 recipes for physical testing throughout the project's duration.
Business Need:
The client wanted to develop an improved clean-label, gluten-free muffin recipe with optimized product attributes to improve their current gold-standard clean-label, gluten-free muffinrecipe.
Benefits Delivered:
The model successfully suggested superior recipes, leading to noticeable enhancements within a short timeframe:
Notable improvement in the overall crumb structure.
Significant enhancements compared to the control recipe in terms of color, volume, initial firmness, shelf-life, and freeze-thaw stability.
AI-enabled recipe formulation resulted in an impressive 80% reduction in time compared to conventional formulation methods.
As a result of this project, a new benchmark gluten-free muffin recipe was established for the customer.
Global R&D and Innovation Platform
Records Tech Service customer interactions and transforms them into actionable content.
Facilitates the creation of automated process workflows across various Innovation functions.
Records comprehensive experimental designs and manual data inputs.
Integrates data from diverse sources including instruments, process sensors, SAP, Excel, and LIMS.
Stores and connects data within and across projects, Innovation functions, and geographical regions.
Offers analytical and visualization tools for enhanced insights.
Grants immediate access to historical data.
Enables real-time data sharing within the Innovation community.
Business Need:
Absence of a central data repository leads to restricted data access and insights.
Data dispersed across local systems, computers, individual files, and paper-based records.
Historical data inaccessible conveniently, resulting in redundant efforts.
Dependence on paper-based batch sheets for sample production, followed by manual transfer to Excel for analysis.
Manual compilation of data from various sources into a single document for analysis.
Lack of data connectivity among R&D functions, projects, and Idea Labs.
Manual data sharing through emails and collaboration platforms.
Benefits Delivered:
Productivity:Automated data processing liberates scientists' time for higher-value tasks.
