Due to thin profit margins and high variability in consumer spending, the consumer goods industry needs to optimize all steps in the supply chain. Advanced analytics and data science leverages data to discover critical business insights in order to create a critical competitive edge.
Consumer Goods – like food, clothing, vehicles, appliances, and personal care items – though different, share many similarities in manufacturing, storage, transportation, marketing, and sales. Profit margins can be razor thin so companies must optimize every step in the supply chain.
Elder Research has expert teams that provide consulting support to design and implement data strategies and analytics approaches. Our consumer goods solutions make relevant and actionable insights readily accessible to VPs, directors, managers, and other decision-makers, creating a competitive differentiator in the industry.
Our consumer goods analytics solutions include:
- Improved Demand Forecasts
- Optimized spend in Trade, Marketing, and Promotions
- Insights into the Complete Customer Journey
- Reduced Manufacturing Waste
- Reduced Fines for Late and Incomplete Case Orders
Examples of consumer product work include:
Trade Spend Optimization
We have applied optimization algorithms to the allocation of nearly a billion dollars of trade budget while meeting overall brand growth and trade objectives in over 5000 brand-customer combinations. While determining an optimal solution, the algorithm also prioritizes investment based on segment for brand-customer size of business and shelf placement and can incorporate other business input into the solution.
Manufacturing Waste Reduction
Manufacturing results in large losses due to waste — scrap material above the minimum required to manufacture each product. Scrap presents an opportunity to reduce manufacturing cost. When components are manufactured in multiple locations identifying the plant with the least scrap for each component provides an opportunity to identify reasons for excess material usage at plants needing to meet industry standards.
Optimizing Cost Sourcing
Sourcing optimization analyzes the sourcing process to assess which changes best reduce costs, prevent lost sales, and/or reduce customer fines from late or incomplete orders. We assess order details, inventory, forecasted demand, storage costs, sourcing cost, order batching opportunities, transportation history, customer fines, and any specific organizational constraints to design algorithms that optimally minimize the cost of transporting the goods to the customer.
Predictive Plant Maintenance
Plant asset performance metrics, such as mean-time-to-failure and mean-time-to-repair are essential for any organization with equipment-reliant operations. By tracking these critical KPIs, companies can maximize uptime and keep disruptions to a minimum. Further, by understanding these metrics, planned maintenance can be optimized to reduce cost and non-value-added repairs.
Plant Changeover Optimization
Intelligent allocation of jobs among limited manufacturing resources is a critical exercise for businesses seeking to minimize costs and maximize efficiency. Using cutting-edge operations research tools and algorithms, we can help boost your productivity by optimizing production schedules, reducing downtime, and increasing availability.