In the words of former GE CEO, Jack Welch, "If you don't have a competitive advantage, don't compete." This CLE covers how technology has changed the practice of law and how we can (and should) use analytics to our transactional and litigation advantage. Examine how analytics have changed our application of model rules of professional responsibility. Understand how analytics and artificial intelligence are applied in both professional and legal world. Examine how to use and apply analytics in a legal case.

Not only does Starbucks go through mounds of coffee beans to satiate its raving fans, but they also have mounds of data that they leverage in many ways to improve the customer experience and their business. With 90 million transactions a week in 25,000 stores worldwide the coffee giant is in many ways on the cutting edge of using big data and artificial intelligence to help direct marketing, sales and business decisions. When Starbucks launched its rewards program and mobile app, they dramatically increased the data they collected and could use to get to know their customers and extract info about purchasing habits. The mobile app has more than 17 million and the reward program has 13 million active users. These users alone create an overwhelming amount of data about what, where and when they buy coffee and complementary products that can be overlaid on other data including weather, holidays and special promotions.

Data is everywhere in business, and teams that are adopting data-driven cultures are making huge strides. Tools and strategies for data-based decision making can be applied in so many different ways: for maximizing operational efficiencies, as a team engagement tool or to help build more effective customer acquisition campaigns. In my coaching practice, I've started to see some truly successful implementations of both business intelligence (BI) and artificial intelligence (AI) as execs learn to lead confident, data-driven teams.

Data is everywhere in business, and teams that are adopting data-driven cultures are making huge strides. Tools and strategies for data-based decision making can be applied in so many different ways: for maximizing operational efficiencies, as a team engagement tool or to help build more effective customer acquisition campaigns. In my coaching practice, I've started to see some truly successful implementations of both business intelligence (BI) and artificial intelligence (AI) as execs learn to lead confident, data-driven teams. There's no question that integrating artificial intelligence and business analytics can have a major impact on your team's performance, but there are some key challenges to making it happen. While data can make your organization more efficient, it can also impact your brand identity, the roles on your team and the customer experience.