Consumer Goods

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

Learn more about Marketing Analytics and Demand Forecasting.

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.

Case Studies

The savings from consumer goods solutions can be substantial for all parties involved.  Our clients—whether newly-formed analytics teams or established pros—find that we help them create solutions to optimize every step of the supply chain. Examples of our consumer goods solutions include:

Developing a Strategic Roadmap and Analytics Center of Excellence

An established leader in the household products sector hired Elder Research to assess its current analytics needs, develop a strategic roadmap, and build an analytics center of excellence. This organization had a strong culture but lacked an analytics process and governance to deliver value across business functions. After a half-day, on-site strategy session with the organization’s executives, Elder Research created a multi-year roadmap focused on the speed of data and analytics delivery and agility in the marketplace.

Results: In the first year alone, Elder Research worked with the company analytics teams to prioritize, approve, and complete more than 30 projects. The initial 15 projects are estimated to yield a savings of $2.2 million and 5,000 person-hours per year when implemented.

Predicting Customer Lifetime Value

A leading Consumer Product Goods (CPG) client wanted to identify customers most likely to make purchases in the future by predicting their lifetime value (LV) and use this lifetime value to inform their digital spending decisions for paid search advertising. Elder Research data scientists developed a model to predict if and when a particular customer will purchase products based on prior purchasing behavior, and estimate the monetary value associated with their next purchases.

Results: Elder Research built predictive models that recognized consumers who were up to 10 times more likely to purchase products, allowing for targeted marketing campaigns. Model results were presented with a custom-built visualization and scenario planning tool, allowing for easy interpretation of the results for non-technical staff.

Optimizing Trade Promotion Budget Allocation

A leading CPG company hired Elder Research to optimize budget allocation to promote over 5,000 brands and account combinations to reach target growth objectives. Using Rsymphony, Elder Research developed a linear model to optimize their nearly one billion dollar budget allocation based on targeted growth rates for 5000 decision variables and 500 constraints in seconds.

Results: The result saved the client over 2,000 employee hours annually. A process, which previously took five employees over half their time and months to complete, now takes one employee a half-day with employee review. Automation enabled the client to quickly adjust trade spend to support new insights from data-driven marketing campaigns.

Analyzing Paid Search Ad and Keyword Effectiveness

A leading retail company for consumer product goods (CPG) wanted to understand the effectiveness of their digital marketing efforts in order to better understand their customers and drive performance-based marketing to maximize their return on investment. They hired Elder Research to assess the effectiveness of various paid product ads and determine the value of Google paid search keywords.

Results: Post promotion analytics enabled the client to optimize market spend and trade promotion mix for company-wide success while improving value to consumers. Elder Research built a keyword pricing model to identify under-performing ad characteristics and overspending in 25% of our clients’ paid search budget. Additionally, the team developed a Power BI dashboard that allows brand teams to quickly visualize the most and least effective keywords.