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The world’s largest companies tend to have an enormous amount of items that they purchase globally in multiple languages and systems. There is often a significant hidden saving to be unlocked through prudent and targeted standardization efforts on this Big Data, but it’s not without significant effort. In the past it didn’t make much sense to do it since, without algorithmic automation it ends up being an impractical task to do quickly and well. With Refresh software automation it remains a formidable task but stubborn savings that were previously impractical are now firmly within reach.
This particular customer is a household-name Fortune 50 Chemical multinational with many materials – around 4 million SKU’s in their ERP systems spread around 200 sites in 35 countries worldwide. After demonstrating potential for tangible savings on a successful test set of 10 000 Raw, Semi Finished and Finished SKU’s, the global HQ in the USA signed up for a full global enterprise license of both Refresh Desktop and Refresh Server.Case Study - Auto UNSPSC at Global Top 3 Chemical Co. Read more
The world’s largest coated fine paper company was facing a Big Data challenge – how to optimally manage an increasing number of materials, services and suppliers across multiple countries and languages. Two major strategies had been decided by the corporate procurement department: 1) to leverage Procurement by Spend Visibility / Spend Transparency across mills, and 2) to lower working capital by eliminating duplicates and permit sharing of critical items.
In terms of in-house Spend Analysis there already existed an internal SAP material group code but this was not consistently applied across the 340 000 material masters. Additionally procurement selected UNSPSC as the benchmark external material group for spend reporting as well as two other important coding systems: eccma’s eOTD for commercially neutral material descriptions, and INTRASTAT/HTS for consistent commodity / VAT reporting.Case Study - Auto SAP Material Masters - Global Paper Co. Read more
In 2011 one of the world’s leading universities was facing a Big Data challenge – how to increase spend penetration in the right commodities with continued demonstrable savings. The university had already covered significant ground – with an excellent record in increasing the % spend penetrated over the last five years almost one hundred fold.
Even with this substantial success management had targeted even more future spend visibility and spend analysis for the majority of the university’s Purchase items, services and suppliers in the Oracle Financials system. In terms of in-house software tools, the organization had been running Oracle Financials successfully for many years as well as some best-of-breed reporting tools. However, the current tools were not the main problem – the underlying raw data was the real issue. It was extremely tough to get users to provide trustworthy spend classification across an extremely diverse group of commodity groups from stationery to building services to complex medical equipment.Case Study - Auto UNSPSC Codes in Oracle PO line items Read more
In 2010 this leading company’s Nickel business unit had completed a global SAP implementation and was looking to make significant procurement cost savings during a tough time for global commodity prices and volumes. Headquartered in Canada, with an annual managed production of more than 100,000 tonnes of nickel in seven countries they had many lines of raw data passing through their ERP systems and took the opportunity to drive better procurement through some standardization of their own data.
Each site had an extremely diverse range of items of supply being bought daily from many suppliers through multiple purchasers in each country. They were running best of breed procurement tools however, the current tools were not the main problem – the underlying raw data was the real issue.Case Study - Auto UNSPSC and ISO8000 in MRO items Read more
In 2012 one of the world’s leading producers of sugar was facing a Big Data challenge – how to manage and optimize spend on an increasing amount of materials from a large supplier base. Additionally their sugar plant is the largest most technologically advanced, fully integrated cane sugar manufacturing facility in the world which means excellent production figures, but quite a diverse range of items of supply being bought daily through many purchasers.
In terms of in-house software tools, the organization had been running SAP for many years as well as some best-of-breed reporting tools. However, the current tools were not the main problem – the underlying raw data was the real issue. The main problem remained: how best to automatically tag all materials and purchase line items to UNSPSC and how to get standard Noun:Modifier material descriptions – reducing duplicates & off-contract spend?Case Study - Auto UNSPSC Codes for SAP PO line items Read more
In 2011 one of the world’s largest energy companies was facing a Big Data challenge – how to optimally manage increasing numbers of project data, assets, spares, services and suppliers across multiple projects & phases. Three major decisions had been agreed by the corporate supply chain & engineering departments: 1) to mandate to suppliers the full practical technical & purchasing data to be supplied early at RFP/RFI stage; 2) to build internal data knowledge in the Oil & Gas engineering data standards and purchasing specifications in-house as a foundation for their growing E&P assets; and 3) to make sure that these standards could be future proofed. Basically this meant that they needed standards in detail down to each attribute at Front End Engineering Design (FEED) stage, long before being handed over in practical terms to SAP & Maximo for operational maintenance and procurement people at commissioning. The company had tried to solve the problem previously using a master data management system and outsourced data company but without much traction.Case Study - Auto ISO classes for SAP and Maximo items Read more
With acquired operations in seven countries and on three continents, it had become a Big Data challenge to standardize a significant amount of materials and services at this large wood products multinational company. Items were being bought daily through many operational buyers in five different languages, some in countries where the head office language is not well-known. In terms of existing software tools, the organization had been running SAP for many years extremely well. However, the underlying material and service line item data was the real issue with 200 000 materials in the ERP system in a mix of 5 languages with possible duplicates, obsoletes and incorrectly classified items.
The question was: how best to automatically clean and standardize these 200 000 materials correctly and simultaneously in all five languages in seven countries. And after that: how to keep them standardized globally in each and every country simultaneously at first point of entry?Case Study - Auto UNSPSC and SAP item text translations Read more
In 2009 the company was facing a challenge – how to optimally manage some 600 000 MRO materials and services across multiple ERP systems and 75 locations. An in-house strategic P2P (procure to pay) initiative aimed to identify and categorize most materials and services procurement lines using the United Nations Standard Products and Services Code (UNSPSC). UNSPSC was to be mapped to each of the 600 000 Materials and Services and then updated in Passport, Maximo and SAP to facilitate:
• consistent, accurate and uniform tracking of company spend
• easy company-wide visibility of all items, MRO in particular;
• the further development of strategies, benchmarks & analytics for strategic sourcing.Case Study - Auto UNSPSC the fast and easy way Read more
Big data within the purchasing and maintenance systems of any large organization tends to hold substantial savings in the form of duplicated items. These savings are tough to unlock without an automated software tool to algorithmically identify duplicates and drive automatic standardization.
This particular customer is perfect example of this: a well-run household-name Fortune 500 consumer good company with well loved brands, found in almost every home in the United States. As the company has grown over the years, many duplicated items of supply have crept in - a great opportunity for a software driven de-duplication project.
The procurement, engineering and finance teams had struggled in the past to get to grips with the half-a-million different items being purchased, stocked or sold. Without software automation the project would simply not have started.Case Study - Auto-find Duplicates in SAP for USA CPG Co Read more
With more than 30 years of excellence in high quality aluminium production, the company expects the same high quality standards from its master data. Being the world’s largest single site aluminium smelter with a captive power station means having close to 100 000 material masters in one SAP plant. The major facilities spread over 500 hectares (six square kilometers) include a one million metric tonne per- annum primary aluminium smelter, a 2350 megawatt power station, a 30 million gallon per day water desalination plant and a significant shipping port. In 2006 the company had implemented SAP and was dealing with the practical challenges of how to leverage the system to achieve its expected benefits. A previous effort of outsourcing the material data cleansing to a well-known off-shore data cleansing company had not achieved the level of quality desired and so the main problem remained: How best to increase the data quality of the existing materials, especially with consistent commercial and technical short and long descriptions & characteristics?Case Study - Auto MRO SAP Material Master Descriptions Read more