From Aisle to AI How CPGs Can Conquer Demand Variability
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From Aisle to AI: How CPGs Can Conquer Demand Variability
From Aisle to AI How CPGs Can Conquer Demand Variability
Tom Gregorchik, 1 minute read
Extreme demand volatility and unprecedented supply chain disruptions make it tough for many manufacturers to get the demand-supply balance right. Consumer packaged goods (CPG) companies face especially difficult forecasting and demand planning challenges. Every day, CPG planners must contend with the complexities of omni-channel sales and promotions, product seasonality, shelf life and perishability, and new product launches.
In addition, the rise of omni-channel has created significant, and not always predictable, changes in shopper behaviors. It’s opened the door to heightened competition from lower-priced private-label offerings, as well as causing consumers to choose different product sizes.
Amid this complexity and uncertainty, consumer products manufacturers still need the right product to be at the right place, at the right time, across all channels and retail customers. This is essential to drive revenue, protect profit margins, and build strong retailer and consumer relationships.
But how do they get there?
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It all comes down to accurate demand planning to arrive at the correct product mix — along with accurate demand sensing to ensure inventory is positioned in the right location to fulfill on-time and in-full requirements, even in the face of extreme market volatility. This high level of precision is driven by access to internal and external data, automated planning processes fueled by artificial intelligence (AI) and machine learning (ML), in-depth analysis tools and sophisticated algorithms.
Instead of relying on manual analysis, outdated tools, static planning cycles and consumer-grade spreadsheets — which introduce errors, inefficiencies and risks — successful CPG companies are using internal and external data sources to create a factual basis for increased forecast accuracy.
Just as CPG companies constantly refresh their product lines and brand strategies to stay current in the retail aisle, they also need to keep pace with digital planning innovation. As more companies realize the value of AI and ML, data science, predictive analytics and advanced forecasting algorithms, CPG leaders can’t afford to get behind the curve. To maximize their demand planning results, they need to embrace AI- and ML-enabled solutions that offers these three essential capabilities:
Real-time decision-making, enabled by simulation. CPG companies need an intelligent solution that ingests hundreds of demand-driving variables — including granular local sales data, but also macroeconomic indicators like housing starts and interest rates. The ideal solution also considers planned promotions, open orders, recent deliveries, customer inventory levels, retailer point-of-sale (POS) numbers and other data. The right solution not only makes recommendations based on its analysis but also — here’s the critical part — enables planners to simulate the outcomes of their decisions before they implement them. As they prepare to pull an execution lever, planners have already predicted the most probable outcomes, relying on statistical algorithms and predictive modeling capabilities.
Transparency into demand cause-and-effect. Explainable AI enables demand planning teams to proactively shape demand by understanding the likely real-world impacts of promotions, new product launches, economic trends, local events and weather on their forecasts. Instead of making assumptions or guesses based on human cognition, CPG planning teams can leverage digital decision engines to conduct rigorous mathematical analysis — and consider hundreds of potential demand-influencing factors in mere minutes. Planners can accurately predict cause-and-effect upfront and execute on the demand plan with full confidence.
Near-term demand sensing with longer-term forecasting, all in one solution. The days of static forecasting, conducted on a monthly or quarterly basis, are over. Today’s market volatility demands a more dynamic, real-time approach. As market trends emerge or consumer behaviors shift, CPG companies must sense these changes in near real time, then adjust forecasts and plans dynamically. CPG companies need a near real-time solution that guides them as they dynamically rebalance and reposition inventory, shift allocation, adjust regional or store-cluster replenishment, and otherwise fine-tune execution plans based on real-time, unbiased demand data. But they can’t just focus on short-term factors that improve near-term forecasting results. They also need appropriate algorithms for a longer planning horizon, where unknown factors might emerge. This mix-and-match forecasting approach is essential to achieve both short- and long-term views of demand.
Stop browsing and choose Blue Yonder Cognitive Demand Planning
It’s hard to imagine a single digital solution that delivers all these capabilities, answering the specific challenges faced by CPG planning teams. But Blue Yonder Cognitive Demand Planning is purpose-built to help consumer products companies create accurate, dynamic forecasts — no matter how quickly, or how often, demand changes.
Powered by AI, ML, data science and proprietary forecasting algorithms, Cognitive Demand Planning minimizes the lag time between planning and execution. In generating dynamic forecasts, this powerful solution runs hundreds of what-if simulations quickly, to ensure supply is being accurately and profitably matched with near real-time, objective demand data. Via intelligent scenario planning, CPG companies can increase forecast accuracy by up to 15%. This more accurate, more confident forecast can be shared up and down the supply chain to ensure a coordinated response, minimize excess inventory at all nodes and improve customer service.
As it increases CPG companies’ understanding of demand drivers, Blue Yonder Cognitive Demand Planning:
Reduces lost sales by up to 3%
Improves planner productivity by up to 75%
Transparently shows the cause of forecast increases and decreases
Identifies new causal factors over time
Allows planners to add their own demand drivers to its analysis
Leverages multiple statistical and ML models to forecast over different time horizons, regions, retailers, store clusters and product categories
Ingests causal data from multiple sources, including the data marketplace managed by Snowflake, a strategic Blue Yonder partner
Your one-stop shop for greater planning speed and accuracy
If you’re a demand planner in the consumer products industry, why are you still shopping? Leading CPG companies have already placed Blue Yonder Cognitive Demand Planning in their carts. They’re using it every day to successfully navigate today’s overwhelmingly complex, fast-paced world of demand forecasting. For example, a global beverages leader recently used Cognitive Demand Planning to improve forecast accuracy by 6% — while reducing bias by 11%.
Find out how Cognitive Demand Planning can produce significant improvements in your planning speed, accuracy, productivity and frequency.
Real-time insights, for real powerful results.
Cut through the noise and get straight to the data. Our AI-powered solution simplifies real-time demand planning for consumer goods, improving forecasts and planner efficiency.
