Yes, Larry, the Digital Analyst can generate decision recommendations based upon the automatic analysis of the data carried out by its underlying algorithms, rather than just providing insights or analytic reports. Hence, Larry is forward-focused on what the next best decision should be, rather than rearward focused on what happened in the past and why. As a simple example, it's possible to define two classes of entities within Larry: Customers and Products, where customers have preferences for certain products and these preferences must be extracted from the data. The utility matrix gives (for each customer-product pair) a value that represents what is known about the degree of preference of that customer for that product (the matrix is often sparse, as most entries are unknown). Larry, the Digital Analyst then examines the properties of products recommended to customers: For example, customer A likes products with characteristics X, so that Larry would recommend products with characteristic X, and analyse the similarity measures between customers and/or products (the products that are recommended to a customer are those preferred by similar customers, which is often referred to as collaborative filtering).