Skip to content

Blog Posts: Demand Management

Deep analysis is only half the job. Win trust with decision makers and inspire actions to deliver impact. Most analysts have been part of failed projects or have encountered the dreaded “I am not sure I understand it...” followed by…

Historically, concerns about over-zealous censorship have focused on repressive governments. In the United States, free speech has been a pillar of our society since its founding. For the most part, government attempts at censorship or speech restrictions receive swift and…
We’re excited to host the semi-annual Analytics Symposium in IIA’s hometown: Portland, Oregon on March 12-13 at the historic Sentinel Hotel. Come hear top analytics leaders share their experiences in executing successful programs within their organization, trends they see…
With the hype surrounding Artificial Intelligence (AI) today, almost everyone in the analytics and data science space has been asked about AI by their business partners. Unfortunately, during these conversations it often becomes apparent that the business person really doesn’t…
Portland, Ore. (Dec. 11, 2018) – International Institute for Analytics (IIA) leaders Bill Franks, Tom Davenport and Bob Morison revealed their list of 2019 analytics predictions and priorities for data-driven enterprises. Pressing topics include ethics, unique data, artificial intelligence, security,…
Everyone who has lived within the world of analytics has seen cases where different parts of a business have made use of slightly differing definitions of core business metrics. Sometimes these differences lead to only minor and non-material disagreement.…
Profit and Loss (P&L) statements permeate businesses due to the need to track how a business is performing at overall, business unit, and even project-by-project levels. This blog raises a question: why shouldn’t an analytics plan be expected as…
Machine learning is a great way to extract maximum predictive or categorization value from a large volume of structured data. The idea (at least for “supervised learning,” by far the most common type in business) is to train a model…
Certainly, it is important to have analytics available in the timeframe needed for making decisions. For many years, it was too difficult and expensive to execute analytics anywhere near real-time and so everything was done using infrequent batch processes.…