The challenge to getting the most out of data analytics initiatives, however, is in establishing the most productive approach. Many companies start with “What are we going to do with all this data?” rather than with “What opportunities do we want to seize?” or “How can we develop industry-disrupting customer insights?” They put the cart before the horse by not starting with the strategic outcomes.
Establishing an outcomes-based objective creates a framework for identifying which data are important and what questions to ask in your analytics. The decisions that need to be made faster, better and/or cheaper drive the analytics to be run, which drives the data to be captured.
When you ask better questions of your data, you’ll get better answers — the kind that can drive large-scale change in your business. Here are other insights gleaned from the research.
You don’t just think about data differently — you work with it differently
Once you know what you want to use your data for, there are several operations you’ll need to undertake in order to use it in new and more effective ways: data-integrity measures to improve data reliability, data standardization to make analysis more inclusive and practical, and normalization to operationalize data across silos so that everyone works from the same data.
But to work with data differently, you also need different tools. And there is a wide range of newer tools gaining traction, such as visualization tools that make data more accessible and easier to understand the business implications. EY has taken a data-driven approach in developing our Supply Chain Smart Maps solution, enabling clients to gain end-to-end visibility across the supply chain. Thus, Smart Maps becomes a catalyst for generating innovative digital solutions for a company’s supply chain transformation journey.
No matter how valuable you think your data are, they’re probably more valuable than that
It’s easy to fall into the trap of thinking that today’s data are just like yesterday’s, just more of it. Instead, you need to appreciate the extraordinary value to be extracted from connected data, both structured and unstructured. They produce new sources of information. They lead to asking better questions, which can open new arenas and levels of competitive advantage. They enable proactive, innovative solution development.