Data Value Hub AbCon

AbCon – a growing Irish Manufacturer – needed to increase sales revenue while decreasing administrative charges and stock retention costs.

Meet Abcon

Established in 2005, following an MBO of the abrasive business from a UK company, the business commenced with 8 employees and has now grown to employ 165 people operating from three sites in Cavan and exporting to over 50 countries globally.

The Company operates as two distinct manufacturing units;

  • Abrasives; serving the industrial engineering (fabrication & refinishing), automotive, wood working, aerospace and medical manufacturing industries in Ireland, UK, Europe and US.
  • Industrial Rubber Hose (including plant lining) which serves the global market in mining, materials handling and recycling, oil and gas, food and beverage.

Industry: Manufacturing

Location: Cootehill, Co.Cavan

Company Size: 165+

Key Project Deliverables:

  • Predictive analysis of supply and demand: Increase sales revenue while decreasing administrative charges and stock retention costs.

“Our business was scaling fast despite COVID and Brexit and we needed to understand how AI could help us grow quicker and recoup wastage. The incubator helped us very quickly zero in on stock prediction and better digitisation and I’m pleased to say we have two projects now in progress following the incubator with a solid ROI case which will allow us to grow at less cost than before.”

Ronan Smith, Manager

The Problem

Lost Sales and Inventory Shortages:

  • A significant portion of sales are lost due to ‘out of stock’ statuses, due to inaccurate demand prediction and a raft of supply chain challenges.
  • Seasonality: Demand fluctuations stem from seasonal construction patterns.
  • Challenges from Brexit and COVID-19: Disruptions in supply chains due to Brexit and COVID-19 hinder predictive algorithm training.
  • Supply Chain disruptions: AbCon’s supplied materials faced extended lead times due to distant suppliers.

The Challenge

  • Increase sales revenue while decreasing administrative charges and stock retention costs.
  • Utilise predictive analytics to optimise ordering of long lead time products by considering demand variance and correlations.
  • Ideally, integrate to a single comprehensive view of the business covering sales, supplier orders, and lead times for order fulfilment.

And that’s where we came in.

“I found the program to be excellent and a real differentiated offering for SMEs like us in the region. It challenged us to think differently about how our data is used and how to further extract value from it. The program was hands-on and practical with a real focus on delivery of the project outcome which was impressive given the number and variation of the projects on the incubator. ”

Adrian Jebb, IT Support Technician, Abcon

The Solution

The AI Incubator programme gave Abcon  instant access to the support & resources they needed to leverage the power of AI for their business & execute their data strategy in-house with ease and confidence. 

During the AI Incubator, AbCon and DVH worked to identify a set of AI methods which were potentially applicable to their problems.  The teams also conducted a rigorous examination of the quality and history of orders & stock data available (which included the events of Brexit, COVID, and the Suez Canal supply chain disruption).  Then the teams build their Proof of Concept predictive models which could be incorporated into dashes for stock / order prediction reporting.


Supply Chain Optimisation:

  • Enhanced Predictive Analytics for Ordering: Ordering of long lead time products using predictive analytics, accounting for demand variances and inter-product correlations.

Unified Enterprise View and Expansion:

  • Single view of AbCon’s sales, supplier orders, and lead times.

Efficiency, Revenue, and Cost Improvements:

  • Reduced understocking and overstocking, resulting in increased sales revenue through lower admin charges, improved sales, and reduced stock retention. Achieved via predictive analytics and streamlined data.
  • Enabled efficient stock valuations and repricing during supplier price hikes through the unified enterprise stock view.
  • Automated sales order processing – another project investigated during the AI Incubator – pointed to additional savings in sales admin staff time and reduced order errors, which is important as volumes are growing.

Follow On Projects

Abcon  is working on two follow on projects which will allow them to deploy and measure predictive ordering in practice and increase the digitisation and automation of sales order processing.

The Benefits – ROI/Impact

While it’s still early into the implementation stages of the follow on projects, we predict the following key results for the Abcon team:

Abcon hope to reduce lost sales by up to 50%.

An improved ordering process, efficient stock retention, and improved CRM.

The project is expected to produce 2x-5x ROI.

The programme has upskilled key IT and Managerial Staff

A portion of Sales Support Staff time can now be transferred to higher value work supporting continued growth.

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