INTEGRATION IMPERATIVE
Susan Lahey outlines that the time is now to ensure that analytics and data science are fully integrated into corporate and operational decision-making.
We’re hitting the nail on the head with the responses in this report. It really comes around to, ‘do I have the necessary data available for the study that I’m trying to do?’ And ‘is that good data?’ Data is always gonna be an issue in any type of analytics and data science approach. And the reality is we just have to be able to figure out alternatives. What are the best approaches both from a technical perspective and a sheer modeling perspective and what is going to make the most sense? Data quality is often an outcome from how programs have been executed. When you see data quality being an issue or lack of available data being an issue, it’s important to be able to sit down and really work to understand ways that we can pull the needed data together or piece that data
“It’s important to be able to sit down and really work to understand ways that we can pull the needed data together or piece that data together.” together. Often clients have information. It’s just all in separate areas due to in coming into the organization through different sources. With anything data and analytics based, you’re going in front of people and putting tons of numbers in front of them and trying to build a story along with those numbers. So the real critical piece is making data and analytics more accessible to anyone, regardless of whether or not they consider themselves data savvy. As data and analytics providers our role is to help build that story. We have to understand what are those key critical questions that our customers or clients have and how can we answer those using the numbers that we have. When people say that it’s not as integrated, I don’t think it’s for lack of desire to have it integrated. It’s more
Powered by FlippingBook