Grocery delivery app saw 10x faster time to market
Use Case
Demand forecasting
Industry: E-Commerce
Company Size: Operates in 26 cities with thousands of products and over 2K employees
Solution: Forecast demand at SKU level across cities
Platform Use Case: Demand forecasting
Data Stack: BigQuery
10x
faster time-to-market
12,000
partner stores’ data included in models
80-90%
accuracyIn predictive analytics, accuracy is a measure of a predictive model’s performance. It’s usually expressed as a percentage, calculated by dividing the number of correct… for forecasting top revenue categories
Challenge
Over 12,000 suppliers and 26 cities of data
This grocery delivery app company needed to build and maintain a demand forecast model that could accurately predict sales volume at the SKU level. In addition to needing a granular forecast for each product, the company also needed to anticipate demand for each item across more than 26 cities with over 12,000 suppliers. This complex modeling challenge made it impossible to build and deploy a scalable solution in-house.
The forecasting challenge had resulted in overstock of certain products at some stores, and understock of other products elsewhere — leading to massive inventory costs and a poor customer experience.
Solution
From raw sales and SKU data to accurate predictions
Given the scope and complexity of this client’s supply chain, the desired predictive analyticsPredictive analytics uses data, statistics, and machine learning techniques to build mathematical models that can generate predictions about things likely to happen in the future…. project seemed insurmountable. Yet Pecan accomplished the task in just a few days, beating the existing models created over several months in both accuracy and actionability.
The predictions of this model were 80-90% accurate, partially due to Pecan’s data enrichmentData enrichment involves integrating external data from trusted third-party sources into analytics in ways that complement a company’s internal data. For example, demographic, weather, or… with regional weather, traffic, and economic data.
Results
Unprecedented demand forecasting—and no more stockouts
With the Pecan platform, the customer deployed their models 10x faster without compromising model accuracy and usability. Since the business team could rely on Pecan to solve their long-awaited demand forecasting needs, the internal data science team could focus on custom business questions and use cases.
Pecan’s models consistently performed accurately, even with dozens of forecasts that spanned varying time horizons, configurations, business aspects, frequency, and other factors over several weeks.
Within the highest-value product categories, Pecan accurately forecast 50% of the SKUs with under 20% predictionA prediction is the ultimate goal of a predictive model. In Pecan, a prediction is often tied to a specific customer. After learning from data… error. Additionally, by leveraging Pecan’s proprietary data enrichmentThe process of adding additional information or context to existing data in order to improve its value and usefulness. This can include adding new data… assets, the customer revealed unexpected business insights about the strongest predictors of demand for their top-priority SKUs.
Ultimately, the company saw overstock instances reduced by several orders of magnitude through using Pecan’s AI-powered predictive analytics to forecast demand. Pecan’s forecasts advanced the company’s efficacy and supply capability. Most importantly, the accurate, granular forecasts improved their customers’ experience by minimizing stockouts to historical low levels.
Contents
It’s time to refine your outreach with customer foresight
Latest Resources
10 Data Breakthroughs That Solve Business Problems
Are you curious about your enterprise and how you can improve your business? Meet our latest Data Science breakthroughs.
Predictive Analytics: Getting Actual Value from Machine Learning
In this webinar, we shared the essential components of predictive analyticsAnalytics is a business practice that uses descriptive and visualization techniques to gain insight into data; those insights can then be used to guide business... to get value in the shortest time possible.
Stop User Churn in 3 Steps with Predictions
In a constant battle for user time, developers need to keep their users engaged and happy while monitoring reduced engagement and churn rates.