Why FICO Was Named a Leader in Predictive Analytics

Great news, FICO was named as a leader in the March 2017 report, The Forrester Wave™: Predictive Analytics and Machine Learning Solutions, Q1 2017. This is an honor, and it underscores for us the value and positive business impact our analytic solutions continue to deliver.

Forrester Graphic Predictive Analytics Machine Learning Wave 300x240 Why FICO Was Named a Leader in Predictive Analytics

These types of technology evaluations are really useful for organizations needing guidance as they enter into new strategic ventures. With plenty of attention on the promise of advanced analytics and machine learning, this report from Forrester is very timely. The report highlights:

  • The Predictive Analytics and Machine Learning (PAML) Solutions market is “hot,” with Forrester forecasting “a 15% compound annual growth rate (CAGR) for the PAML market through 2021.”
  • The true essence and core value of predictive analytics, stating “enterprises that can make probabilistic predictions about customers, business processes, and operations will have an edge over enterprises that can’t.”
  • Machine learning is fundamental to artificial intelligence.

When you talk to data scientists and business leaders and hear their real-world stories, one begins to comprehend the possibilities that come with advanced analytics or data science. So, to compliment this Forrester Wave report, I thought I would share a few FICO case studies that demonstrate the value and competitive advantage predictive analytics can provide.

Airline Predicts and Solves Problems Before Crews Are Grounded and Customers Are Unhappy

Managing an airline that serves 100 million customers annually – with more than 3,900 daily departures during peak travel season to more than 100 destinations globally – is no small undertaking. And when regular operations become irregular, the task of keeping customers happy, flights on time and crews supported is daunting.

This is why airlines, like Southwest, have extensive contingency plans for irregular operations. Southwest has The Baker, a recovery optimization engine that turned the best practices of its irregular operations (IROPS) team into complex algorithms that solve potential challenges like maintenance problems or volatile weather, while minimizing the impact to passengers and crews.

Southwest can not only react to problems within minutes, but it can also get ahead of potential disruptions hours in advance and evaluate multiple scenarios. The Baker has helped Southwest improve on-time performance and customer satisfaction, while lowering flight diversions, tarmac delays and crew changes.

This is predictive analytics in action, and it has made a significant impact at Southwest, helping the airline gain advantage in a highly aggressive and competitive market.

Meaningful, Personalized Connections with Customers at the Grocery Store

Virtually any customer engagement can be improved with the power to predict. In the case of a major grocery retailer FICO works with, using analytics to deeply understand customers helped the retailer provide a highly personalized experience that encouraged loyalty and increased profitability.

The grocery retailer wanted to predict the propensity of a customer to purchase particular products and then prescribe the best offer. This required a multidimensional understanding of each of its 9 million loyalty program members, as well as taking into consideration business objectives and constraints.

With FICO’s advanced predictive analytics, the grocer was able to take its 380 billion possible offer combinations and deliver 20 tailored, relevant offers to each member every week.

Predictive Analytics Revolutionize the Energy Industry

Another great FICO customer example is SolarCity, a leading solar energy provider working to create an ideal way to store solar energy and then use it when demand is high. Electric demand can vary widely, based on things like changes in the weather, inconsistent supply or seasonal consumer patterns. With advanced predictive analytics, SolarCity is able to track and forecast complex scenarios for selling aggregated energy.

It’s fascinating that the same technology that is helping Southwest minimize flight delays and a grocery retailer deliver highly personalized offers to customers is also helping optimize a solar energy grid. Hopefully these real-world examples add a little perspective as you read the March 2017 Forrester Wave™ for Predictive Analytics and Machine Learning Solutions.

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