5 ways IBM Cognos Analytics is transforming business

With business generating more data than ever before, organizations are rapidly investing in business intelligence (BI) capabilities to help them generate insights from that data to drive better business decisions and identify new opportunities.

In January, market research firm Research and Markets forecast the global business intelligence and analytics software market would hit $55.48 billion by 2026, representing a CAGR of 10.4 percent from the $22.79 billion the market accounted for in 2017.

IBM Cognos Analytics is a self-service analytic platform that integrates cognitive computing technology, including artificial intelligence (AI) and machine learning, originally developed for Watson Analytics. For example, the platform uses cognitive technologies to help automate data preparation. The system learns users’ data and can generate recommendations for data joins and visualizations. It’s intended as an all-in-one platform, so provides analytics functions ranging from creating dashboards and data integration to reporting, exploration, and data modeling.

Here are five examples of organizations using Cognos Analytics to transform their operations.

Maximizing charitable donations with text analytics

Like most institutions of higher education, Michigan State University (MSU) seeks to raise charitable donations from alumni and other stakeholders but doesn’t want to bombard potential donors with fundraising requests that could sour them on giving. To solve this problem, MSU’s University Advancement Team is leveraging text analytics to mine alumni and stakeholder records to make its fundraising requests more effective.

MSU is using IBM Cognos Analytics to mine data from biographical data, records of committee and board meetings, reports from volunteering initiatives, student and staff records, and donation histories. It’s also pulling data from blogs, forums, and social media content and has purchased additional data sets from providers such as LexisNexis.

MSU’s team of eight data scientists have used the information to build sentiment analyses and predictive models that analyze 177 different variables to determine how likely an individual is to donate.

Optimizing retail operations with purchase analytics

In addition to its luxury hotels, golf courses, and spa, the Pebble Beach resort in Monterey, Calif., features a full-service retail operation with 15 stores. The resort had minimal visibility into the inventory levels of its retail operation and increasingly faced stockouts, which led to unhappy guests. To gain better visibility into its retail operation and optimize purchasing, the resort turned to IBM Cognos Analytics to manage the inflow and outflow of nearly 30,000 products across its stores.

Pebble Beach centralized the previously siloed data from its disparate retail systems and transitioned from on-premises servers to the cloud, providing it with better access to retail data. The resort has cut the cost of sales by nearly 2 percent and accelerated reporting from several hours to minutes.

Leveraging data to maximize fan engagement

Every year, the All England Lawn Tennis Club (AELTC) brings thousands of spectators to the grounds and millions of viewers from around the world to the Wimbledon Championships. Like other major sporting events it is constantly challenged with finding new ways to engage fans and retain viewers. Media outlets that partner with AELTC to bring Wimbledon to the world are always on the hunt to cover the matches in a more compelling way to grow their audiences.

To better serve its fans and media outlets, AELTC uses IBM Cognos Analytics to analyze its historical data (dating back to 1877) and real-time data from the umpire chair and referee’s office. During the 2018 champions, an infrastructure architect worked with Cognos Analytics full-time, leveraging a combination of 120 pre-built reports and spontaneous queries, to discover statistics and respond to questions from the AELTC and media in minutes rather than hours.

In 2019, IBM hopes to provide members of the media the ability to self-serve queries and reports.

Deploying data science to keep salmon populations healthy

Norway is the world’s largest producer of Atlantic salmon, and exports 95 percent of that production. Sea lice are among the biggest threats to Norway’s wild salmon population and its salmon farming industry. The parasite naturally occurs in marine waters but has reached unnaturally high concentrations in many of Norway’s fjords and coastal waters due to intensive production of salmon and rainbow trout.

The Seafood Innovation Cluster, an industry-funded member organization, has made the health of Norway’s salmon a top priority. It says that sea lice management costs the industry at least $600 million a year. Farmers that can’t prove they have lice populations under control are not allowed to expand their operations. The Seafood Innovation Cluster needed to provide rival farmers with a way to collaborate and share information while protecting their commercially sensitive data.

With IBM’s help, the organization developed an automated system for collecting, anonymizing, and aggregating data from salmon farms across the country — 945,000 data points daily from more than 2,000 salmon enclosures. With Cognos Analytics each farmer has a dashboard that provides them with an estimate of the likelihood of an outbreak at each of their sites over the next two weeks. The model has so far proved 70 percent accurate over a two-week horizon, and the team expects the results to continue to improve as more data becomes available. The two-week horizon gives farmers time to take countermeasures before the population explodes.

Predicting audience viewing preferences

Over the past decade, television has evolved into a multi-channel, multi-stream business with fragmented audiences, and that has put increasing pressure on networks to make smarter choices about how they market to viewers.

AMC is using Cognos Analytics to draw actionable insights from hundreds of billions of rows of data ranging from Nielsen and comScore ratings to iTunes and Amazon sales data, data from third-party platforms like Netflix and Hulu, and its own video-on-demand service.

The real-time data has given AMC’s business intelligence department the ability to create statistical models that help the network decide how intensively it should promote each of its shows. Intelligent segmentation and lookalike modeling help it target viewers so effectively that it says video-on-demand transactions significantly exceeded forecasts. The network says the new capability also demonstrates potential for advertising partners to fine-tune campaigns and appeal to audiences across both linear and digital channels.