The manufacturer only had access to high-level, manually-generated summarizations of product sales information, with little or no ability to drill deep into the sales numbers to understand which products, product families or geographic regions were performing as expected or not. These are few of the specific challenges:
The new data lake ingests granular data to produce reporting and analytics that provide the manufacturer unprecedented visibility into their own internal sales and manufacturing data. These solutions address the manufacturer’s initial problems:
For this solution, Antuit first provided advanced analytics to enrich data manually entered into the sales application with natural language processing (NLP) and then compared it with client information in the CRM systems. After that step, data sets were harmonized from the sales rep application, ERP and CRM systems to understand the existing relationship and potential future relationships with the client requesting the extended payment terms. The solution includes logging and analyzing the track record of salespeople requesting “exception” terms. This approach resulted the first time that data across 3 to 4 enterprise systems could merge to derive crucial analytics.
The manufacturer now enjoys a scalable Hadoop framework data platform designed to evaluate future business decisions objectively through advanced analytics and reporting. This provides a powerful and flexible foundation where all data can be ingested and stored in its original format, allowing for data lineage and rapid iteration as the client’s data and business requirements mature over time.
The product profitability and high-margin product are inventory analysis use cases for the data lake and are projected to save the manufacturer between $7 million and $12 million USD in the first year. The extended payment terms use case is projected to increase gross revenue by roughly $500 million.