Leo Sadovy currently manages the Analytics Thought Leadership Program at SAS, enabling SAS’ thought leaders in being a catalyst for conversation and in sharing a vision and opinions that matter via excellence in storytelling that address our clients’ business issues. Previously at SAS Leo handled marketing for Analytic Business Solutions such as performance management, manufacturing and supply chain. Before joining SAS, he spent seven years as Vice-President of Finance for a North American division of Fujitsu, managing a team focused on commercial operations, alliance partnerships, and strategic planning. Prior to Fujitsu, Leo was with Digital Equipment Corporation for eight years in financial management and sales. He started his management career in laser optics fabrication for Spectra-Physics and later moved into a finance position at the General Dynamics F-16 fighter plant in Fort Worth, Texas. He has a Masters in Analytics, an MBA in Finance, a Bachelor’s in Marketing, and is a SAS Certified Data Scientist and Certified AI and Machine Learning Professional. He and his wife Ellen live in North Carolina with their engineering graduate children, and among his unique life experiences he can count a singing performance at Carnegie Hall.
COVID-19 has upset nearly every prediction and business plan for 2020 across the planet. Making predictions for 2021 may seem like a fool’s errand at this point, but many trends and consequences are already obvious and emerging from the global pandemic. The last global pandemic of this magnitude, the Spanish
For Climate Month I thought I’d research something on the positive side of the equation. My last two climate posts were a bit gloomy, as they focused on greenhouse gasses and ocean acidification. Instead we’re going to tackle a product adoption issue related to the climate: When might the United
Where in your business process can analytics and AI play a contributing role in enhancing your decision making capability? At the information interpretation stage. As a framework for understanding where analytic and AI opportunities may arise, the simple diagram below illustrates the relationships between data, information and knowledge, and how
It is a generally accepted maxim in business that you can’t cost-cut your way to success. Growth requires attention to the top line, which in turn is largely driven by innovation. Applying analytics to improving innovation suffers from the same lack of direction as does Analytics for strategy, but with
“Ocean acidification is sometimes referred to as global warming's equally evil twin.” ~ Elizabeth Kolbert This is the second post in my two-part series about climate change. You can read part 1 of this series here. When engaging in data exploration for insights, it’s good practice to start with a
“The future is already here — it's just not very evenly distributed.” ~ William Gibson, author The same can be said for climate change – global warming is here, in a big way, but its effects are still an arm's length away for many of us. How is climate change
If you're looking for advice on developing an analytics strategy, there's no shortage of resources, including this from SAS: Building your data and analytics strategy. If, on the other hand, you're looking for advice on how to apply analytics to strategic planning, your search has likely to come up wanting.
“They were the best of asteroids, they were the worst of asteroids.” ~ Charles Dickens Armstrong There are good asteroids, and there are bad asteroids. Good asteroids stay in their own neighborhoods and wait for us to come visit them. Bad asteroids, however, don’t wait for an invitation – they
By now you’ve seen the headlines and the hype proclaiming data as the new oil. The well-meaning intent of these proclamations is to cast data in the role of primary economic driver for the 21st century, just as oil was for the 20th century. As analogies go, it’s not too
There is one equation every retail store, call center, traffic, airport or hospital manager should know by heart. No, it’s not E = mc². The one I had in mind is this: W = 1 / (μ – λ) It may not look like much, but it can mean the
