Value Chain Analytics
Our team of experts utilizes a data-driven approach to value chain analysis, using advanced analytical tools and techniques to identify and map out the various stages of the value chain. We examine everything from suppliers to end-users, identifying where value is created and lost at each stage. By gaining a deeper understanding of the value chain, businesses can identify opportunities for optimization and growth. Our insights can help you make informed decisions about where to invest resources, whether it's in R&D, marketing, or operations.
Our value chain database is designed to be flexible and scalable, meaning that we can tailor our approach to meet the specific needs of your business. Whether you're a small startup or a large multinational corporation, we have the tools and expertise to help you gain a deeper understanding of your industry's value chain.
At Delphi Data Labs, we're committed to delivering exceptional value to our clients. Our value chain database is just one example of how we're helping businesses stay ahead of the competition and achieve their business goals.
Unlike the industry standard, which relies mainly on interviews, our process is built on big data analytics. Our approach ensures highest academic research standards, and limits the negative impact of cognitive bias, which happens to occur in expert interviews. The human brain is simply not designed to correctly record and depict the nature of complex international multi-billion dollar markets.
That’s why statistical analysis of adequate data is the core of our research methodology. Nevertheless, we strongly rely on human expertise, which marks the starting & final process step in our work:
At first we map and understand the relationships in an industrial value chain to set the frame for our research. In the second step, we fill our value chain model with data from various sources to determine the market potential. In the next step of the process, our data is challenged by human expertise. We then integrate the feedback and adjust our data in a second human feedback & approval process.