Microsoft Manufacturing Germany

ALTANA

Supply Chain Optimization

The challenge: Fragmented knowledge spread across 35 ERP systems

Knowledge transfer is essential for the success of a company—not only when experienced employees are retiring and it’s necessary to preserve and pass on their many years of expertise. Chemical company ALTANA started early on to consolidate the knowledge of its purchasing department in a central location. To do this, the company is relying on a graph database, Microsoft Azure, and PRODYNA, a member of the Microsoft Partner Network. The EMPOWER platform solution not only minimizes time and effort, increases performance, and enables price predictions with a deviation of only 5 percent, it also brings more transparency to sustainability data in the supply chains.
Today, the EMPOWER platform is hosted entirely in Azure and is made up of three components: The first is the knowledge graph, which pulls together and combines internal metadata on material categories, raw materials, and suppliers from the 35 ERP systems. The second is the data factory based on

Reported impact

Business outcome

Knowledge transfer is essential for the success of a company—not only when experienced employees are retiring and it’s necessary to preserve and pass on their many years of expertise. Chemical company ALTANA started early on to consolidate the knowledge of its purchasing department in a central location. To do this, the company is relying on a graph database, Microsoft Azure, and PRODYNA, a member of the Microsoft Partner Network. The EMPOWER platform solution not only minimizes time and effort, increases performance, and enables price predictions with a deviation of only 5 percent, it also brings more transparency to sustainability data in the supply chains.

  • Productivity Improvement
  • Risk Reduction

Solution

Knowledge transfer is essential for the success of a company—not only when experienced employees are retiring and it’s necessary to preserve and pass on their many years of expertise. Chemical company ALTANA started early on to consolidate the knowledge of its purchasing department in a central location. To do this, the company is relying on a graph database, Microsoft Azure, and PRODYNA, a member of the Microsoft Partner Network. The EMPOWER platform solution not only minimizes time and effort, increases performance, and enables price predictions with a deviation of only 5 percent, it also brings more transparency to sustainability data in the supply chains.

Solution architecture

2 products mentioned
  • Azure
  • Azure AI Services

Evidence from the source

Knowledge transfer is essential for the success of a company—not only when experienced employees are retiring and it’s necessary to preserve and pass on their many years of expertise. Chemical company ALTANA started early on to consolidate the knowledge of its purchasing department in a central location. To do this, the company is relying on a graph database, Microsoft Azure, and PRODYNA, a member of the Microsoft Partner Network. The EMPOWER platform solution not only minimizes time and effort, increases performance, and enables price predictions with a deviation of only 5 percent, it also brings more transparency to sustainability data in the supply chains.
The challenge: Fragmented knowledge spread across 35 ERP systems
When the purchasing team at
go into meetings with their suppliers, it’s crucial that they have all relevant information such as supply volumes and other benchmark data at their fingertips. The same goes for purchasing management when company-wide data must be compiled to generate overviews of suppliers or price development. These overviews are the basis for optimizing both the business and its products—for instance, when the company is looking to exchange one raw material for another with a smaller carbon footprint.
Transparency Evidence & methodology 62/100 reference value · 83% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value62/100
  • Problem clarity12/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth0/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    2 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence83%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity4/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Microsoft

    ALTANA customer story

    First-party
    https://www.microsoft.com/en/customers/story/1661001566655499258-altana-prodyna-azure-en
    Source type
    Vendor-published customer story
    Published
    Aug 1, 2023
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Aug 1, 2023 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.