Its easy for large companies to spend large budget dollars on multi million dollar data initiatives, thereby taking risks that could yield significant rewards. Small to medium size companies dont always have the luxury of a large budget to build their analytics group or solution, and in many cases dont have the time, or patience, to wait for a solution to yield results. Large companies, while having the luxury of a budget, suffer from inertia, sometimes preventing progress.
All posts by Alexander Pelaez, Ph.D
SNA: Understanding the Social
Increasingly, companies are harvesting their data to understand relationships between customers. Customer’s word of mouth promotion or denunciation of a product or company can be a vital piece of knowledge for organizations. Companies that can identify key influencers within a network are capable of utilizing those influencers to promote the product and affect the communication of information in the shortest path possible, in stark contrast to simply broadcasting information over traditional media. Continue reading SNA: Understanding the Social
Analytics: Ph.D. Not required!
Analytical talent has become the hottest acquisition for companies, and many organizations are scouring for the best talent to bring on board. A question commonly asked is, “Should we hire Ph.D in Statistics or some related field”. The simple answer is, a Ph.D ISN’T required. What is needed for an analyst is a good math background, with some expertise or interest in experimental design.
3 Big Reasons Why A/B Tests Fail
A/B tests are more popular in today’s environment and can provide a great value to an organization. A/B tests are conducted when one is trying to understand the effect of a change to a system or environment. This type of testing has been done for many decades, but is known in academia and research organizations as experimental designs. Therefore, good A/B tests should follow sound methodological research practices, while remaining cognizant of practical limitations, such as sample size and construction and lack of a controlled environment, such as a laboratory. There are three reasons why many of these AB tests fail to yield expected results. Continue reading 3 Big Reasons Why A/B Tests Fail
The Analytics Organization – Part 1
Having been a part of large organizations, I have seen first hand the effect of both good and bad structures in Information Technology and Analytics. In analytics organizations, there are many different skill sets and the number of people calling themselves data analysts and data scientists it becomes increasingly difficult to determine how the analytics organization should be constructed. Continue reading The Analytics Organization – Part 1