Scanmarket Expands Analytics Capabilities With the Acquisition of Artificial Intelligence Company Mia Data
Scanmarket acquires analytics company; Scanmarket brings artificial intelligence and analytics into its Source-to-Contract platform; Scanmarket introduces new Spend Analytics module
Scanmarket is pleased to announce the acquisition of MIA Data, an analytics technology company specializing in artificial intelligence and machine learning applied to digitalization of business procurement processes.
As Scanmarket continues to evolve with additional analytics capabilities, MIA Data will play an integral role in implementing its scalable analytics capabilities across the Scanmarket platform.
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“The evolution towards artificial intelligence and machine learning within the procurement industry marks a next step in the journey to digitalize procurement, creating a best-in-class solution for resolving the pain of tedious data gathering and insights,” says Betina Nygaard, CEO of Scanmarket.
Introducing analytics into procurement and applying it across the entire software platform, enables customers to gain increased transparency and instant visibility across many different data sets and dispersed data sources, resulting in easy identification of risks and potential areas for efficiency improvements.
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Initially, the new AI capabilities have been applied to Scanmarket’s Spend Analytics software. The technology will be fully integrated into the existing Scanmarket platform for a seamless workflow process between modules and tasks ensuring a fully transparent spend management approach. The analytics will allow greater visibility into the entire spend under management to better understand and communicate optimization opportunities.
Visibility into spend is critical in strategic sourcing and analysis of spend patterns have come a long way since the days of manually pulling data from spreadsheets. Scanmarket’s new Spend Analytics module can gather spend data from various company systems into a single repository. It is then cleansed, normalized, enriched and classified to provide a factual picture of both direct and indirect spend across categories, vendors, geographical spread, languages, business units and more.
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