One of the major hurdles companies face in transforming to a Digital Supply Chain is their inability to get data from customers and suppliers—or even from other departments in their own company. Nothing new, right?
What is new is the idea of “trading data” to overcome that hurdle and use as a catalyst for Digital Supply Chain transformation. Let me explain.
Companies are aggressively turning to artificial intelligence and machine learning (AI/ML) to gain a competitive advantage. But for that strategy to succeed, companies must develop algorithms that rely on AI/ML technology to run their business. And what is the life force behind algorithms? Data. Lots of data. That makes data trading, internally and with customers and suppliers, essential to unlocking the power of AI/ML.
The critical management question is how to do it? Read More
Tag Archives: Data Science
What is DataOps and Why It’s Critical to the Data Monetization Value Chain
In my previous blog “How DevOps Drives Analytics Operationalization and Monetization”, I discussed the critical and complementary role of DevOps to operationalize and monetize the analytics that came out of the Data Science development process. While the combination of Design Thinking and Data Science accelerate the creation of more effective, more predictive analytic modules (where analytic modules are packaged, reusable and extensible analytic modules), it’s the combination of Data Science and DevOps that drives analytic model operationalization and monetization. Read More
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