Order Spikes Analysis

Order Spikes Analysis is the process of identifying, analyzing and understanding sudden increases in order volume within a specific timeframe. These spikes can occur due to various factors, such as seasonal demand, promotional campaigns, supply chain disruptions or unexpected market trends.

Problem

Statement

Identifying anomalies in historical order data over a 52-week period, excluding the most recent week.

The goal is to detect significant deviations in order quantities for various CUSTOMER and ITEM combinations, allowing for better insights into purchasing behaviors and potential operational issues.

Solution

Proposed

01

Data Preparation

Filtering: The historical order data was filtered to exclude the most recent week, ensuring that only relevant data for analysis was considered. Also, prepared another data for the same time period last year.

02

Z Score Calculation

Baseline Establishment

For each CUSTOMER_ITEM combination, the average order quantity and standard deviation were calculated using the historical data.

Z Score Calculation:

The Z score was computed to measure the number of standard deviations and observation is from the mean.

03

Anomaly Detection

Threshold Comparision

The calculated Z scores were compared against a predefined threshold to flag orders as anomalies.

Comparison of Anomalies

The latest week's order quantities were compared to the historical same-time period averages to identify significant spikes in order quantities, providing seasonality context for anomalies.

04

Percentage Change

The percentage change in order quantity was calculated for each CUSTOMER_ITEM combination. This metric quantified the deviation from the average, providing a clear view of how much the latest orders differed from historical trends.

Business

Values

The implementation of an anomaly detection system for historical order data provides significant business value across several dimensions:

01

Enhanced Decision-Making

By identifying significant deviations in order quantities, the business can make informed decisions based on real-time insights. This enables proactive responses to change in customer behavior, market trends and inventory needs.

02

Improved Customer Satisfaction

Understanding purchasing behaviors through anomaly detection enables the business to tailor its offerings and marketing strategies. By addressing unexpected spikes or drops in orders, the company can better meet customer expectations and enhance satisfaction.

03

Cost Savings

By quickly identifying anomalies that could indicate overstock or stockouts, the business can reduce excess inventory costs and minimize lost sales opportunities. This financial efficiency directly impacts the bottom line.

04

Long-Term Strategic Insights

Over time, the data gathered from anomaly detection can reveal patterns and trends that inform long-term business strategies.

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