Nelly NLY AB improves Returns Management with mpmX

Nelly.com is a Swedish online retailer selling clothing, shoes, and accessories for young women. The company offers both branded and private-label products through its e-commerce platforms and serves customers in several European countries.

The lack of process transparency and the demand for enhancing traditional KPIs with processual context led Nelly to the decision of implementing and working with mpmX throughout the organization. In collaboration with the mpmX Partner Drake Analytics AB, the Customer-Order-to-Returned-Product process was visualized and mpmX was seamlessly integrated into the existing Qlik® Sense environment.

Initial Situation

‍The Returns Management is a crucial part in retail and e-commerce. On the one hand, returns are indicative for Nelly concerning customer experience. Returns can impact how likely a customer is to purchase again in the future and its longer-term lifetime value. On the other hand, returns are causing costs in terms of shipping, labour, and others.

This process of interfacing with customers who wish to return a product includes various process steps like collecting, organizing, and restocking inventory that has been returned or exchanged. Within the described Customer-Order-to-Returned-Product process, bottlenecks may occur and thus result in longer lead times than expected.

In order to deploy a Process Mining tool, the related data had to be retrieved from various types of data sources. Whereas the order data is delivered through Nelly’s ERP system, the “internal” process steps are stored within their Warehouse Management System. Within Nelly’s Data Warehouse, the “external” process steps and contextual data (product, customer, supplier, etc.) can be accessed.

Project Objectives‍

The main objective of Nelly’s Process Mining initiative was to be able to shorten the lead time within the Customer-Order-to-Returned-Product process. Furthermore, the following insights and goals were targeted:

• Analysis of as-is process (performance & compliance)
• Pinpointing what data is missing and taking action on starting collecting that data
• Measurement and visualization of important Key Performance Indicators & Process Performance Indicators
• Identification, evaluation and measurement of actions taken
• Identification of automation potentials
• Process comparison (as-is vs. to-be)
• Roll-out mpmX with further use cases and increase data-driven decisions

Why mpmX‍

Besides a productive partnership between Drake Analytics and Nelly, various factors were convincing to choose mpmX. For the most part, mpmX brings time savings in process analysis as well as more valid analysis results through quantitative analysis. In addition, it allows controlling the effects of developed measures through permanent real-time data. Another key factor was the seamless integration into the existing Qlik® Sense platform. Nelly determined that Business Intelligence & Process Mining belong together in the field of data analytics and should be run on one platform rather than on separate ones. With mpmX, the same data sources are used and the similar requirements for data governance and dashboarding can be covered.