Don’t let your sales compensation dashboard tell you half the story. Take a look at the five key productivity metrics and five key people metrics you need to consider when determining whether your sales employees are performing as expected, driving your organization’s strategy and motivated to take
In this Conversations in Sales series podcast, hear Emily Manley at IBM and Barry Trailer, chief research officer at CSO Insights, a division of MHI Global, discuss sales performance management (SPM) and incentive compensation management (ICM). From this insightful discussion learn more about the
At the core of many big data architectures is Apache Hadoop and Apache Spark. Organizations adopting these technologies for their big data journey are nevertheless at different levels of maturity. Hear what Prasad Pandit had to say in an interview with Andrea Braida about how IBM is evolving its
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.
Before diving into planning for sales compensation, get a fix on the company’s business goals and strategy. See why having a framework in place is critical when designing a sales strategy and compensation program.
Many forward-thinking organizations want to investigate how big data analytics helps them outthink and outperform the competition. However, many also are challenged with finding the right talent to run the operations, keep the data secure and figure out how to leverage the myriad tools at their
Banking industry leaders are rethinking their incentive compensation strategies in terms of risk and compliance. Here are some important questions—and some best practices—that can guide banking managers and executives as they develop incentive compensation plans that drive both compliance and
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.
Do you manage variable-based pay at your organization? Find out how you can avoid payment errors and streamline plan administration while giving your organization the insights that your sales team needs.
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.