o9 Solutions, Inc. Case Studies Transforming Demand Planning in Beauty Retail with IoT

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	Transforming Demand Planning in Beauty Retail with IoT o9 Solutions, Inc.

Transforming Demand Planning in Beauty Retail with IoT

o9 Solutions, Inc.

Technology Category	Platform as a Service (PaaS) - Application Development Platforms Sensors - Level Sensors
Applicable Industries	E-Commerce Retail
Applicable Functions	Logistics & Transportation Sales & Marketing
Use Cases	Demand Planning & Forecasting Last Mile Delivery
Challenge	The beauty retailer, marketing 15 brands and 2000 SKUs across various distribution channels, faced a significant shift from physical retail channels to online due to the COVID-19 pandemic. This shift necessitated a future-proof planning tool to support their ambitious growth plans and to gain a deeper understanding of demand drivers. The company was heavily reliant on Excel, which led to latency and siloed processes. They lacked a comprehensive understanding of the main drivers of demand for their five channels. The company was also unable to plan at the desired level of granularity, leading to shortages and delivery delays. Demand planners were spending most of their time crunching Excel spreadsheets, unable to focus on higher-level strategic tasks. Manual interventions were frequently needed, especially for estimating the effect of New Product Introductions. Read More
About Customer	The customer is a leading beauty retailer that markets a total of 15 brands, covering 2000 SKUs, and uses a wide variety of distribution channels: mass market, hair and beauty salons, and selective distribution for various brands. The company experienced a significant shift in delivery from physical retail channels to online, mainly due to the COVID-19 pandemic. This shift required a future-proof planning tool to support their ambitious growth plans and help obtain a deeper understanding of the drivers of demand. The company was heavily reliant on Excel, which created latency and siloed processes. Read More
Solution	The company deployed o9's demand sensing features to understand the drivers behind the growing channel shift across e-commerce, modern trade, and general trade channels. This allowed them to determine the right level to forecast at and perform demand planning with high granularity for all 2000 SKUs. The company also used the o9 Enterprise Knowledge Graph to build demand models, enabling it to run key demand planning processes for all product lines in a single integrated platform. o9's open architecture was leveraged to ensure data integration with Matelabs.ai. This solution removed low-value manual work by enabling data-driven exception workflows and ML-based New Product Introduction forecasting. The company replaced Excel with o9, gaining flexibility of having a platform, rather than a product, which permits modeling flexibility. Read More Log in to view content
Contents

Technology Category

Platform as a Service (PaaS) - Application Development Platforms

Sensors - Level Sensors

Applicable Industries

E-Commerce

Retail

Applicable Functions

Logistics & Transportation

Sales & Marketing

Use Cases

Demand Planning & Forecasting

Last Mile Delivery

Challenge

The beauty retailer, marketing 15 brands and 2000 SKUs across various distribution channels, faced a significant shift from physical retail channels to online due to the COVID-19 pandemic. This shift necessitated a future-proof planning tool to support their ambitious growth plans and to gain a deeper understanding of demand drivers. The company was heavily reliant on Excel, which led to latency and siloed processes. They lacked a comprehensive understanding of the main drivers of demand for their five channels. The company was also unable to plan at the desired level of granularity, leading to shortages and delivery delays. Demand planners were spending most of their time crunching Excel spreadsheets, unable to focus on higher-level strategic tasks. Manual interventions were frequently needed, especially for estimating the effect of New Product Introductions.

About Customer

The customer is a leading beauty retailer that markets a total of 15 brands, covering 2000 SKUs, and uses a wide variety of distribution channels: mass market, hair and beauty salons, and selective distribution for various brands. The company experienced a significant shift in delivery from physical retail channels to online, mainly due to the COVID-19 pandemic. This shift required a future-proof planning tool to support their ambitious growth plans and help obtain a deeper understanding of the drivers of demand. The company was heavily reliant on Excel, which created latency and siloed processes.

Solution

The company deployed o9's demand sensing features to understand the drivers behind the growing channel shift across e-commerce, modern trade, and general trade channels. This allowed them to determine the right level to forecast at and perform demand planning with high granularity for all 2000 SKUs. The company also used the o9 Enterprise Knowledge Graph to build demand models, enabling it to run key demand planning processes for all product lines in a single integrated platform. o9's open architecture was leveraged to ensure data integration with Matelabs.ai. This solution removed low-value manual work by enabling data-driven exception workflows and ML-based New Product Introduction forecasting. The company replaced Excel with o9, gaining flexibility of having a platform, rather than a product, which permits modeling flexibility.

Impact #1	The implementation of o9's demand sensing features and Enterprise Knowledge Graph led to a transformative change in the company's demand planning process. The company was able to understand the drivers behind the growing channel shift across e-commerce, modern trade, and general trade channels. This allowed them to plan at a high level of granularity, reducing shortages and delivery delays. The solution also eliminated low-value manual work, enabling demand planners to focus on higher-level strategic tasks. The company was able to replace Excel with a more flexible and efficient platform, improving process orchestration and saving valuable time.

Impact #1

The implementation of o9's demand sensing features and Enterprise Knowledge Graph led to a transformative change in the company's demand planning process. The company was able to understand the drivers behind the growing channel shift across e-commerce, modern trade, and general trade channels. This allowed them to plan at a high level of granularity, reducing shortages and delivery delays. The solution also eliminated low-value manual work, enabling demand planners to focus on higher-level strategic tasks. The company was able to replace Excel with a more flexible and efficient platform, improving process orchestration and saving valuable time.

Benefit #1	Significant improvement in understanding the drivers of demand
Benefit #2	Increased forecast accuracy
Benefit #3	Improvement of process orchestration, resulting in winning back valuable time

Benefit #1

Significant improvement in understanding the drivers of demand

Benefit #2

Increased forecast accuracy

Benefit #3

Improvement of process orchestration, resulting in winning back valuable time

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Overview

Transforming Demand Planning in Beauty Retail with IoT

Operational Impact

Quantitative Benefit