Michael D. Stevens is the Government Market Segment Manager for IBM’s Information Management division. He has over 25 years of experience in marketing, consulting and software development, much of it with a focus on government. He has worked broadly with IBM’s software business, in a variety of marketing, product management and solution development roles. Previously, Michael worked for software companies Informix and Autodesk, along with several consulting firms and the U.S. Federal Government.
Government Market Segment Manager, IBM
August 8, 2014
This blog discusses the value of Hadoop for government and how forward-thinking agencies are using it.
May 7, 2014
How can a painful experience at the Department of Motor Vehicles point the way to a more efficient, effective government? A key lies in the ability to anticipate rather than just respond. This blog illustrates how three government organizations from around the world are using IBM’s Big Data & Analytics to better serve their citizens.
October 17, 2013
Washington D.C. may close down occasionally, but never Las Vegas! We have another great set of presentations in the Government track of the Business Leadership Forum at IOD this year. A wide range of customers and solution partners will be showing how they are incorporating big data and analytics to achieve new levels of efficiency and effectiveness across a variety of government focus areas.
October 14, 2013
When weeks of analysis failed to uncover improper payments, the Big Data Analytics engine did it in 4 hours – and led to a $140 million payoff
May 9, 2013
It is my privilege to support government sector marketing for IBM. We live in a complex and sometimes dangerous world with growing threats to public safety, national security and the environment.
March 6, 2013
Cyberspace is today’s new battleground, and cyber security continues to be a top imperative for both enterprises and governments. This is where big data comes in. IBM® Security QRadar® uses big data capabilities to help keep pace with advanced threats and prevent attacks before they happen. It helps uncover hidden relationships within massive amounts of security data, using proven analytics to reduce billions of security events to a manageable set of prioritized incidents.