We hear a lot of hype that says organizations should be “Data–first”, or “AI-first, or “Data–driven”, or “Technology–driven”. A better prescription for business success is for our organization to be analytics–driven and thus analytics-first, while being data-informed and technology-empowered. Analytics are the products, the outcomes, and the ROI of our Big Data, Data Science, AI, and Machine Learning investments!
AI strategies and data strategies should therefore focus on outcomes first. Such a focus explicitly induces the corporate messaging, strategy, and culture to be better aligned with what matters the most: business outcomes!
The analytics-first strategy can be referred to as Analytics By Design, which is derived from similar principles in education: Understanding By Design. Analytics are the outcomes of data activities (data science, machine learning, AI) within the organization. So we should keep our eye on the prize — maintaining our focus on the business outcomes (the analytics), which are data-fueled, technology-enabled, and metrics-verified. That’s the essence of Analytics by Design.
The longer complete version of this article “How Analytics by Design Tackles The Yin and Yang of Metrics and Data” is available at the Western Digital DataMakesPossible.com blog site. In that article, you can read about:
- The two complementary roles of data — “the yin and the yang” — in which data are collected at the front end (from business activities, customer interactions, marketing reports, and more), while data are also collected at the back end as metrics to verify performance and compliance with stated goals and objectives.
- The four principles of Analytics By Design.
- The five take-away messages for organizations that have lots of data and that want to win with Analytics By Design.
For data scientists, the message is “Come for the data. Stay for the science!”
Read the full story here: “How Analytics by Design Tackles The Yin and Yang of Metrics and Data“