Unreasonable sales forecasts, badly overstocked inventory, misguided investments . . . bad analyses happen all the time, leading to bad decisions and costing businesses millions of dollars. Derek Ruths shares the five most common issues that lead to bad data-informed thinking. You’ll learn what they look like, how they arise, how they lead to bad decisions, and how to catch them before they hurt your organization.
Derek Ruths is cofounder and chief architect of CAI, a charity focused on bringing the power of data science to social good initiatives. Derek is also an associate professor of computer science at McGill University, the head of R&D at Data Sciences, and the director of the McGill Centre for Social and Cultural Data Science. In these capacities, he works closely with major tech companies, advises governments on technical innovation, teaches executive education programs, and partners with international humanitarian organizations. In his work and research, Derek has been a longtime advocate for the essential role of data science in fostering more equitable, more prosperous, and healthier organizations and societies.
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