Industry: Retail

Demand Forecasting assessment and recommendations for Speedo; Improved data completeness and accuracy across multiple systems; Enhanced demand planning and forecasting accuracy; Reduced manual data processing and validation efforts

Benefits & Results

  • Enhanced accuracy and completeness of product data leading to improved demand forecasting and planning.
  • Long-Term Impact: Streamlined data management processes, reduced manual effort, and better alignment of data across systems. More efficient operations, improved sales and profitability, and a more robust demand planning function for Speedo North America.

Increased efficiency and data accuracy contributing to overall business performance.

Background

Pentland Group is a multi-brand organization investing in retail and wholesale businesses within the sports outdoor and sports fashion sectors. Their brand Speedo North America (SNA) required a data cleanse initiative to improve demand planning and forecasting.

Challenges

Pentland Brands faced several challenges with their current data management: absence of clean and appropriate data, restricted view of data issues, inadequate knowledge of data estate, and challenges in generating timely accurate and efficient demand planning and forecasting reports.

Solution

NowVertical conducted a comprehensive assessment and provided a data cleanse solution for Pentland Brands. This included identifying key challenges, mapping leakages in the product journey, and recommending a future state with clean data for Blue Yonder implementation.

Implementation

  • Data Collection and Analysis: Gathered data from Centric (PLM), SAP (ERP), and Blue Yonder (Demand Planning & Forecasting). Conducted workshops, interviews, and documentation reviews with business and technical stakeholders. Performed data analysis to identify completeness and conflicting patterns.
  • Data Cleanse Initiatives: Developed a systematic approach to cleanse data. Created a product data health card and revalidated data anomalies. Generated and implemented business rules for data validation.
  • Recommendations and Roadmap: Proposed a future state with a streamlined data flow and automated checks. Provided a detailed roadmap for data cleanse and ongoing data management.
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