• Black Facebook Icon
  • Black Twitter Icon
  • Black LinkedIn Icon

© 2019 Vemo, Inc. All Rights Reserved - Privacy Statement

Please reload

Recent Posts

BPI Announces Vemo CEO Peter Louch Best Practice Award Winner!

December 7, 2016

1/1
Please reload

Featured Posts

Predictive Analytics - See the future of your organization

September 30, 2016

 

From elections to sporting events to the stock market, you can find countless opinions on what the future will bring. But without supporting data, any opinion is nothing more than an educated guess. How do you go from a guess to a prediction? By using data to inform decisions about the future. Predictive analytics allows you to discover, analyze and act on data. It’s about learning from the past to uncover trends and predict likely outcomes, but that’s not all. Predictive analytics gives you a framework to analyze data over time, leading to more refined outcomes and countless opportunities for improvement. With an uncertain talent outlook on the horizon, using data to create a coherent view of the future has never been more important. Predictive analytics combines techniques from statistics, data mining and machine learning to find meaning from large amounts of data.  Integrating historical HRMS, talent, learning, financials and benchmarking data is powerful fuel to get a predictive analytics engine running. However, many companies are still challenged to collect, manage and analyze this information to position their organization for success.

 The key stages for an analytical life cycle include:

  • Analytical data preparation – Source, clean and prepare the data for optimal results.

  • Visualization and exploration – Explore all data to identify relevant variables, trends and relationships.

  • Statistical analysis – Use everything from simple descriptive statistics to complex Bayesian analysis to quantify uncertainty, make inferences and drive decisions.

  • Predictive modeling – Build the predictive model using statistical, data mining or text mining algorithms, including the critical capability of transforming and selecting key variables.

  • Model deployment – Apply the new champion model, once validated and approved, to new data.

  • Model management and monitoring – Examine model performance to make sure it is up-to-date and delivering valid results.

Once a fully functional workforce analytics program is in place HR can empower their business leaders, operational executives, and front-line managers with role-based information that’s easy to understand and act on. Software guided discovery makes it simple to find outliers, patterns, trends, and relationships. When problem areas are identified, users can easily drill down into data to uncover root causes and take appropriate action.

Vemo offers enterprise Cloud-Based Workforce Planning and Analytics technology. Request a Vemo Demo to further assess our capabilities! 

Email: info@vemoworkforce.com Follow us on Twitter: @VemoSocial

Share on Facebook
Share on Twitter
Please reload

Follow Us
Please reload

Search By Tags