Customer experience management can be compared to finding a needle in a haystack. Yet, it’s actually much more challenging—akin to tracking handfuls of needles in a mountain of needles. See how organizations can effectively measure, track and manage subscriber performance in real time.
Learn how IBM SPSS Statistics can enhance the value that statistical analysis adds to a business, and find out how you can tap into the power of high-performance statistical modeling in your own organization.
Essentially, Monte Carlo simulations predict an outcome not from the actual values of input data (which aren’t known) but from the likely (aka “simulated”) values of that data (based on their probability distributions). These simulations can prove invaluable for assessing risks in many real-world
Although spreadsheets offer a stable, attractive option when working with numbers, they can fall far short when they are applied to enterprise-scale statistical analytics. Weigh the limitations of spreadsheets against the benefits of a sophisticated, enterprise-grade statistical analysis tool for
Open source tools continue to foster non-stop innovation throughout the Insight Economy. So it’s no surprise that open-source languages—most notably, R--have moved to the center of enterprise statistical analytics and data management.
Do you find yourself increasingly having to make decisions amid uncertain conditions? The advanced capabilities offered by IBM SPSS Statistics aim to make Monte Carlo simulation a part of your risk analysis by bringing these two worlds together in a single software solution.
Spreadsheets are excellent tools as far as they go—but how far can they truly go? If you’re pushing your spreadsheet-based solutions beyond their viable limits, then they might be doing more harm than good. Discover what considerations you shouldn’t ignore when using spreadsheets for statistical
Data analytics is no longer an either/or choice. With the integration of IBM SPSS Statistics and R, you can bring together the statistical analysis and data management capabilities that have helped so many data scientists gain insight after insight from their data.
Understanding data and data relationships is particularly vital in the energy and utilities industry. Discover how industry data models serve as blueprints for defining structures that provide a broad, in-depth view of business, and how they helped one energy and utilities organization extract data
Advanced analytics, reporting and aggregation software for social media is everywhere these days. As a social media manager, my job is to keep testing out these tools all the time. In all of this testing, seeing a disruptive product that makes you stop and think is rare. And yet I’m pleased to say
For European insurers, the Solvency II Pillar 3 reporting deadline looms. These best practices guidelines can help insurance firms in the selection of a fast-track software solution to ensure compliance with Solvency II Pillar 3 reporting requirements.
From retrospective to predictive to prescriptive analytics, healthcare organizations are embarking on analytics journeys to enhance medical outcomes and create cost efficiencies. Where are you on your healthcare analytics journey?
Discover how automation can help you overcome your incentive compensation plan challenges in an analyst report from Aite. Then, explore how managers can apply Sales Performance Management solutions to help eliminate surprises and make sound, strategic choices for their variable incentive programs.
Organizations may frequently fall into the trap of trying to get an advanced sales performance management (SPM) solution in operation as soon as possible. However, initiating an implementation stage too soon, too hastily or at the expense of best practices can cause companies to overlook critical
A North American manufacturer of retail steel and steel building products implements a comprehensive analysis and reporting system, gaining insights into supply chain and customer demand trends and cutting financial reporting times when it engages with IBM.