This is the most unique presentation relating to the topic of Big Data I’ve ever seen. One example used by this presenter is “how would you visualize all those twitter posts relating to someone tweeting about where they just landed in order to get an idea of where people are traveling to?” Words can’t do…
I recently had the opportunity to chat with Loren Bast, Director of Business Intelligence at online humor network Cheezburger. Cheezburger invested in a new BI tool because it was unable to keep up with the amount of data it was producing across its popular humor websites such as I Can Has Cheezburger and FAIL Blog.
I asked Bast how he would have managed the project differently if he could start again. He said in an ideal world, he would have focused more on the following three things:
John O’Rourke, one of the most seasoned veterans of the EPM industry, offers his perspective in this candid interview with Susan Serven. John shares his views on the future of EPM, the merger of Hyperion and Oracle, the most common misconceptions of EPM, his advice for a company just starting to consider implementing a performance management system, why Balanced Scorecard may have fallen out of favor, and many other insights.
Big data can help businesses gain new insights at incredibly fast, real-time speeds. However, making an informed decision based on accurate information is only the first step. You have to implement that decision across your organization in order to produce the desired outcomes. But how do you do that?
I always find the acceptance speeches at Hollywood’s Academy Awards to be inspirational. The ones I enjoy most are Oscar recipients who thank the teams that contributed to their receiving the award. Success comes much more from teams than from an individual’s performance. My favorite acceptance speeches are from Oscar recipients in science and technology.…
Indeed, “a big data project can’t be treated like a conventional, large IT project, with its defined outcomes, required tasks, and detailed plans for carrying them out … Commissioned to address a problem or opportunity that someone has sensed, such a project frames questions to which data might provide answers, develops hypotheses, and then iteratively experiments to gain knowledge and understanding.”
Back in November, EPM Channel developed their Finance 360° Insight survey to determine where Finance was delivering game-changing value, where they were not, and what could be done about it.
We designed this survey to be a 360° Insight analysis of the finance functions from all levels within the organization. Marketing. Sales. Operations. HR.
“HR executives are well-equipped to competently manage the basics – recruiting, hiring, onboarding, payroll, benefits, training, etc. – and operating unit general managers are generally satisfied with the results. The typical missing link for HR executives, however, is often their ability to assist general managers with the more strategic issues, like:
Are we better off keeping our geographic sales structure after the acquisition, or do we now have sufficient critical mass and concentrations of expertise to take an industry-centric approach?
Can we predict how the increased average age of our skilled workers, their upcoming retirement and the massive replacements by inexperienced workers will affect the business?
The increased production and sales capacity is going to make R&D the bottleneck; what are the critical technical skills we’re going to need and what is the optimal mix of hires, layoffs and retraining to counteract that bottleneck?
In order to meet the increased seasonal demand from new customers, should we build inventory early, run additional shifts or outsource some of our production needs?
Me? Twenty years ago, I was a statistical purist, an unabashed, hypothesis-driven fanatic – perhaps as much as the first author. In fact, I probably would have been considered a top-down analytics “planner.” I did, however, come to expand my horizon to a broader data science discipline that combines statistical orthodoxy with large N data, exploratory visualization and machine learning techniques – balancing an aggressive search for predictive relationships with the cross-validating protection of the no-pattern null hypothesis. So I guess I’ve now evolved into more a bottom-up data-driven “searcher.” Statistical science, though still a central tool, is only a part of a larger analytics portfolio.
arcplan makes its living on the chaos of its customers, is how Dwight deVera, senior vice president, describes the firm’s business.
Financial services firms are a favorite target since they always seem to be acquiring new businesses, meaning they have systems that don’t talk to each other, even if they come from the same vendor. When Bank of America acquired Merrill Lynch, both were running SAP.
“But you can’t consolidate across them. Just because they run the same software doesn’t mean that any of their requirements match. They have thousands of discrete requirements, and some requirements contradict others.” They could try to harmonize the two systems, said deVera, but they would never get the job done.