Case Study

Internal Analytics Data Lake for a Fortune 500 Global Manufacturer

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Challenge

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:

  • Product Profitability: An 8-week manual process without the ability to merge data across various regions and systems
  • High-Margin Product & Inventory Analysis: No capability existed, limiting the company’s ability to push out excess inventory timely to high sales regions to maximize profits.
  • Extended Terms Request: The client’s ‘net 30’ standard payment term required a tedious 10-step process for approving exceptions. Most of the required data was either missing or needed manual cross-checking from CRM systems.  

Antuit designed and built a data lake for stronger analytics and reporting using business intelligence and visualization tools. 

Solution

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:

  • Product Profitability: For every business unit and sub-unit, the client can now report numbers for margin, revenue and cost details with various product lines that are sold by multiple channels. The process reduced from 8 weeks to roughly 2 days of process check, and once data is in the cluster, it is on the dashboard within an hour.
  • High-Margin Product & Inventory Analysis: The client was able to define global cost and average selling prices across product lines and related materials, then blend data with inventory and order backlog data-sets to increase quarterly margins.
  • Extended Terms Request: Antuit provided advance analytics to enrich manual data entry into the sales application with natural language processing (NLP) so it could be compared with client information in the CRM systems. Now the data is harmonized using data sets from the sales rep application, ERP and CRM systems. The solution reduced the steps from 10 to only 3 steps: ingest, harmonize and publish.

 

Results

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. 

 

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