Case Study:

Worldwide Glass Manufacturer

About the Company

The worlds leading glass container manufacturer, has for well over half a century produced high quality, sustainable, brand-building glass packaging. It has created such glassware for many of the worlds best known food and beverage brands; Brands producing beer, wine, spirits, food, non-alcoholic beverages, cosmetics and pharmaceuticals for public sale and consumption. The company also produces a high value range of tableware and stemware for domestic usage.

Here is a description of the company from its corporate profile:

  • Worldwide headquarters: Perrysburg, Ohio, USA
  • $6.7 billion in net sales in 2016
  • 79 plants in 23 countries
  • Joint ventures in China, Italy, Malaysia, Mexico, the United States and Vietnam
  • 27,000-plus employees worldwide
  • More than 1,800 worldwide patents
  • 49,000-plus customers in 86 countries
  • 10,000-plus product offerings
  • 600-plus new product solutions launched each year
  • More post-consumer glass - 4.5 million tonnes - used than any other glass-container maker
  • Client Position
  • Solution
  • Result
Client Position

In late 2015 the company was looking to substantially increase its investment and development of Data Analytics. The company were seeking a corporate partner to guide and assist them in the very specialised area of Data Analytics after internally conducting a small pilot exercise. The company recognised its Data was disparate and isolated in various business systems across its Asia Pacific operation – ERP (SAP), Custom designed in-house manufacturing systems, Health and Safety Systems, A financial planning global system, Human Resources, Supply Chain Systems and many more were all being utilised – separately. The pressing need was to provide a regional view to support management with a dashboard application accessible through mobile and supporting desktop dashboards.

Data Science

In addition the company also was looking to select a solution to undertake “Proof of Concept” to then analyse the inspection machine data (sensor data) and to understand the variability in the performance of glass container inspection stations on production lines.

Countries In Scope
  • Australia
  • New Zealand
  • Malaysia
  • China
  • Vietnam
Solution

Infonyx worked with our technology and business teams in a onshore – offshore ‘Analytics As A Service’ model delivering a Regional View of the business across the Asia Pacific. The service included end to end delivery - extract, integrate, visualise data and ongoing support for:

  • Finance, Sales and Marketing (Monthly Financial Reporting, Daily Sales & Profit Analysis)
  • Supply Chain, Daily Production, Manufacturing Plant Production
  • Human Resources, Health and Safety

The project team leveraged AGILE (Iterative) delivery approach with incremental delivery of data and business capability. Access via the Infonyx Smart Data Cloud Platform enables mobility i.e. access ANYTIME, ANYWHERE. 200+ users across the region can access dashboards and generate insights. Initial solution delivered on premises then migrated to the Infonyx Cloud platform.

Key Insights and Benefits
  • A mobile view for regional, country leadership and management across all devices
  • Integrated view of the business across APAC
  • Access to information at a plant, equipment level (lowest detail) to management level KPI’s
  • Sales trend, forecast analysis, forecast accuracy, inventory levels, Inventory ageing, Understand customer delivery delays and causes
  • Monitor Daily production metrics, efficiency with ability to visualise manufacturing line defects at an equipment and equipment location level
  • Monitor business usage on the platform
  • Reduced Total Cost of Ownership leveraging migration to Infonyx cloud
Data Science (Proof of Concept)

Sensor Data (streaming) was ingested in the Infonyx pre-architected cloud into Hadoop and with a model developed and delivered using “R” to compare the performance of each of the glass container inspection stations to understand the variability of the inspection process with a goal to identify any outliers impacting the quality of inspections. We provide advisory consulting to help define the reference big data architecture for the company.