Changing Tastes and Expectations



Changing consumer tastes and commodity volatility are impacting your profits. Fluctuating demand, supply bottlenecks, material shelf life, production lead time, and paper-thin margins complicate your business’ ability to ensure inventory coverage without gross overproduction. Matching demand with supply requires real-time data visibility and analysis, requiring robust S&OP processes and supply chain capabilities.

However, traditional S&OP approaches and practices often involve highly manual and siloed processes, complex workbooks, and outdated legacy systems. These challenges limit your ability to analyze processes and decisions, efficiently repeat successes, and improve performance over time. With growing market uncertainty and supply volatility, will your business be able to endure these changes with its current capability?

 
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Retail Level Detail

Leverage data to a greater depth of detail to produce SKU-level forecasts

AI-POWERED ACCURACY

Forecasting is the foundation of the S&OP process, but it is too often misaligned to consumer demand. Traditional approaches and legacy systems lack the ability to leverage all your information sources effectively. Rubikloud’s AI Engine ingests and analyzes data from each of your disconnected sources, compensating for information gaps, to extrapolate and produce SKU-level forecasts that accurately align to actual consumption.

RETURN ON INVESTMENT

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SKU-LEVEL FORECAST ACCURACY IMPROVEMENT

Clients typically see a 33% improvement in SKU-level forecasting

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Improve Planning Efficiency

Drive planning process efficiency with AI-powered decision automation

HARNESS DECISION AUTOMATION

Forecasting and demand planning are core steps within the S&OP process, but they require highly manual and complex steps that make it difficult to efficiently complete. Rubikloud’s AI Engine accurately forecasts demand in real-time and feeds outputs directly back into your legacy systems. This helps to transform manual tasks, seamlessly execute plans, and allows planners and teams to focus on more strategic, higher-value opportunities.

RETURN ON INVESTMENT

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EMPLOYEE DAYS SAVED IN A YEAR

Client saved a 1200 full-time employee days in a year, based on a 50% reduction in planning and execution time

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Reduce Excess Inventory

Capitalize on daily and hourly forecasts to minimize overproduction

REDUCE OVERPRODUCTION

Inaccurate forecasts, material shelf life, and manufacturing lead times are all factors that impact your production. Producing safety stock is one method to mitigate the risk of stockouts, but increases your carrying costs. Rubikloud’s machine learning models continuously analyze shipment, market, retailer POS, ERP and external data to generate highly accurate consumption-based forecasts in real-time. These improved demand forecasts enable teams to reduce excess inventory, impacting your margins and bottom line.

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MARGIN IMPACT

A +7% category-level forecast accuracy improvement resulted in a $39M margin opportunity

Why Choose Rubikloud?

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UNIFIED DATA

Our expandable solutions ingest data from all your raw sources and quickly converts it into a clean, usable data model. This removes the onus from internal resources and allows for seamless integration back into your legacy systems.

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REAL PRODUCT. REAL RESULTS.

Our proven solutions are deployment ready, no need for costly custom builds or lengthy sessions that never lead to anything tangible. This approach delivers the fastest time to value on the market while optimizing total cost of ownership.

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WORLD LEADING CPG-SPECIFIC ML

Using our best-in-class, industry specific Machine Learning expertise, we tackle the most complex and nuanced business challenges uniquely impacting retailers.

Stop Speculating. Start Predicting.

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