Effectively harnessing big data today determines your competitiveness for tomorrow. But with the increasing flood of data that is captured today, how do you determine which data is actually useful? INVERTO sheds light on the basics of successfully implementing a big data strategy in procurement using practical applications.
Many companies have not yet developed a consistent analytics strategy or defined application areas and goals for big data, even though this is a prerequisite for successfully employing new forecasting methods and platforms. According to a study by the Gartner Institute in Stamford, Connecticut, 70% to 80% of current business intelligence projects do not manage to achieve their defined expectations.
So how can companies develop effective big data strategies?
Procurement is an ideal area for big data applications because it uses a fact-oriented approach. Procurement has access to significant data, primarily from the supply chain and also the environment that suppliers operate in. It is also easy to prove added value in procurement, because cost savings and performance improvements are tangible results that have a direct positive impact on business performance. Many procurement departments already make use of digital solutions to support important processes, such as forecasting demand, securing and evaluating tenders, and designing dynamic cost models and price overviews. The main challenge lies in selecting and “translating” the application areas in big data analytics into your specific procurement and supply chain.
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