PureCloud WFM and Decisions users now have access to a new class of WFM forecasters.  For years, most WFM vendors have had rather simple forecasting techniques in their WFM platforms. As a result, many companies have built their own home-grown forecasting spreadsheets. 

In PureCloud and the latest version of Decisions, is a new approach to forecasting, one that takes the power of cloud computing and AI to bring the best of the best forecasting technologies to WFM.

Here's how it works.  There are 4 major steps to the forecaster.

1. Historical call center data is consolidated and sent to the forecasting service in the cloud. If you are a PureCloud WFM user, your data is already in the cloud.  If you are a Decisions customer, your data will be sent to our servers.
2. The data will be processed to create a clean data set for forecasting purposes. Missing data will hit a variety of algorithms to fill in your history, and outliers will hit three separate outlier detection algorithms to determine if the data points are truly anomalous.
3. The data stream will be analyzed to note whether there is seasonality and its periodicity, whether there are trends up or down.
4. (This is the coolest step): Based upon the data analysis in step 3, the system will use the appropriate forecasting methods, of the 27 state-of-the-art methods (and gorwing) in our cloud library.  We will spin up CPU's and crank through over 700,000 forecasts and compare them to find the one with the least amount of error.  A best-of-the-best forecast.

Here's the rub.  This whole process, because we are using the power of cloud computing, typically takes a minute or so to run.  We've tested thousands of data streams, and these forecasts are very solid.

PureCloud WFM customers have had access to this approach for about a month-I am curious if you've noticed a change in your forecast accuracy??

PureCloud WFM and Decisions users now have access to a new class of WFM forecasters.  For years, most WFM vendors have had rather simple forecasting techniques in their WFM platforms. As a result, many companies have built their own home-grown forecasting spreadsheets. 

In PureCloud and the latest version of Decisions, is a new approach to forecasting, one that takes the power of cloud computing and AI to bring the best of the best forecasting technologies to WFM.

Here's how it works.  There are 4 major steps to the forecaster.

1. Historical call center data is consolidated and sent to the forecasting service in the cloud. If you are a PureCloud WFM user, your data is already in the cloud.  If you are a Decisions customer, your data will be sent to our servers.
2. The data will be processed to create a clean data set for forecasting purposes. Missing data will hit a variety of algorithms to fill in your history, and outliers will hit three separate outlier detection algorithms to determine if the data points are truly anomalous.
3. The data stream will be analyzed to note whether there is seasonality and its periodicity, whether there are trends up or down.
4. (This is the coolest step): Based upon the data analysis in step 3, the system will use the appropriate forecasting methods, of the 27 state-of-the-art methods (and gorwing) in our cloud library.  We will spin up CPU's and crank through over 700,000 forecasts and compare them to find the one with the least amount of error.  A best-of-the-best forecast.

Here's the rub.  This whole process, because we are using the power of cloud computing, typically takes a minute or so to run.  We've tested thousands of data streams, and these forecasts are very solid.

PureCloud WFM customers have had access to this approach for about a month-I am curious if you've noticed a change in your forecast accuracy??

PureCloud WFM and Decisions users now have access to a new class of WFM forecasters.  For years, most WFM vendors have had rather simple forecasting techniques in their WFM platforms. As a result, many companies have built their own home-grown forecasting spreadsheets. 

In PureCloud and the latest version of Decisions, is a new approach to forecasting, one that takes the power of cloud computing and AI to bring the best of the best forecasting technologies to WFM.

Here's how it works.  There are 4 major steps to the forecaster.

1. Historical call center data is consolidated and sent to the forecasting service in the cloud. If you are a PureCloud WFM user, your data is already in the cloud.  If you are a Decisions customer, your data will be sent to our servers.
2. The data will be processed to create a clean data set for forecasting purposes. Missing data will hit a variety of algorithms to fill in your history, and outliers will hit three separate outlier detection algorithms to determine if the data points are truly anomalous.
3. The data stream will be analyzed to note whether there is seasonality and its periodicity, whether there are trends up or down.
4. (This is the coolest step): Based upon the data analysis in step 3, the system will use the appropriate forecasting methods, of the 27 state-of-the-art methods (and gorwing) in our cloud library.  We will spin up CPU's and crank through over 700,000 forecasts and compare them to find the one with the least amount of error.  A best-of-the-best forecast.

Here's the rub.  This whole process, because we are using the power of cloud computing, typically takes a minute or so to run.  We've tested thousands of data streams, and these forecasts are very solid.

PureCloud WFM customers have had access to this approach for about a month-I am curious if you've noticed a change in your forecast accuracy??

PureCloud WFM and Decisions users now have access to a new class of WFM forecasters.  For years, most WFM vendors have had rather simple forecasting techniques in their WFM platforms. As a result, many companies have built their own home-grown forecasting spreadsheets. 

In PureCloud and the latest version of Decisions, is a new approach to forecasting, one that takes the power of cloud computing and AI to bring the best of the best forecasting technologies to WFM.

Here's how it works.  There are 4 major steps to the forecaster.

1. Historical call center data is consolidated and sent to the forecasting service in the cloud. If you are a PureCloud WFM user, your data is already in the cloud.  If you are a Decisions customer, your data will be sent to our servers.
2. The data will be processed to create a clean data set for forecasting purposes. Missing data will hit a variety of algorithms to fill in your history, and outliers will hit three separate outlier detection algorithms to determine if the data points are truly anomalous.
3. The data stream will be analyzed to note whether there is seasonality and its periodicity, whether there are trends up or down.
4. (This is the coolest step): Based upon the data analysis in step 3, the system will use the appropriate forecasting methods, of the 27 state-of-the-art methods (and gorwing) in our cloud library.  We will spin up CPU's and crank through over 700,000 forecasts and compare them to find the one with the least amount of error.  A best-of-the-best forecast.

Here's the rub.  This whole process, because we are using the power of cloud computing, typically takes a minute or so to run.  We've tested thousands of data streams, and these forecasts are very solid.

PureCloud WFM customers have had access to this approach for about a month-I am curious if you've noticed a change in your forecast accuracy??

PureCloud WFM and Decisions users now have access to a new class of WFM forecasters.  For years, most WFM vendors have had rather simple forecasting techniques in their WFM platforms. As a result, many companies have built their own home-grown forecasting spreadsheets. 

In PureCloud and the latest version of Decisions, is a new approach to forecasting, one that takes the power of cloud computing and AI to bring the best of the best forecasting technologies to WFM.

Here's how it works.  There are 4 major steps to the forecaster.

1. Historical call center data is consolidated and sent to the forecasting service in the cloud. If you are a PureCloud WFM user, your data is already in the cloud.  If you are a Decisions customer, your data will be sent to our servers.
2. The data will be processed to create a clean data set for forecasting purposes. Missing data will hit a variety of algorithms to fill in your history, and outliers will hit three separate outlier detection algorithms to determine if the data points are truly anomalous.
3. The data stream will be analyzed to note whether there is seasonality and its periodicity, whether there are trends up or down.
4. (This is the coolest step): Based upon the data analysis in step 3, the system will use the appropriate forecasting methods, of the 27 state-of-the-art methods (and gorwing) in our cloud library.  We will spin up CPU's and crank through over 700,000 forecasts and compare them to find the one with the least amount of error.  A best-of-the-best forecast.

Here's the rub.  This whole process, because we are using the power of cloud computing, typically takes a minute or so to run.  We've tested thousands of data streams, and these forecasts are very solid.

PureCloud WFM customers have had access to this approach for about a month-I am curious if you've noticed a change in your forecast accuracy??

PureCloud WFM and Decisions users now have access to a new class of WFM forecasters.  For years, most WFM vendors have had rather simple forecasting techniques in their WFM platforms. As a result, many companies have built their own home-grown forecasting spreadsheets. 

In PureCloud and the latest version of Decisions, is a new approach to forecasting, one that takes the power of cloud computing and AI to bring the best of the best forecasting technologies to WFM.

Here's how it works.  There are 4 major steps to the forecaster.

1. Historical call center data is consolidated and sent to the forecasting service in the cloud. If you are a PureCloud WFM user, your data is already in the cloud.  If you are a Decisions customer, your data will be sent to our servers.
2. The data will be processed to create a clean data set for forecasting purposes. Missing data will hit a variety of algorithms to fill in your history, and outliers will hit three separate outlier detection algorithms to determine if the data points are truly anomalous.
3. The data stream will be analyzed to note whether there is seasonality and its periodicity, whether there are trends up or down.
4. (This is the coolest step): Based upon the data analysis in step 3, the system will use the appropriate forecasting methods, of the 27 state-of-the-art methods (and gorwing) in our cloud library.  We will spin up CPU's and crank through over 700,000 forecasts and compare them to find the one with the least amount of error.  A best-of-the-best forecast.

Here's the rub.  This whole process, because we are using the power of cloud computing, typically takes a minute or so to run.  We've tested thousands of data streams, and these forecasts are very solid.

PureCloud WFM customers have had access to this approach for about a month-I am curious if you've noticed a change in your forecast accuracy??

PureCloud WFM and Decisions users now have access to a new class of WFM forecasters.  For years, most WFM vendors have had rather simple forecasting techniques in their WFM platforms. As a result, many companies have built their own home-grown forecasting spreadsheets. 

In PureCloud and the latest version of Decisions, is a new approach to forecasting, one that takes the power of cloud computing and AI to bring the best of the best forecasting technologies to WFM.

Here's how it works.  There are 4 major steps to the forecaster.

1. Historical call center data is consolidated and sent to the forecasting service in the cloud. If you are a PureCloud WFM user, your data is already in the cloud.  If you are a Decisions customer, your data will be sent to our servers.
2. The data will be processed to create a clean data set for forecasting purposes. Missing data will hit a variety of algorithms to fill in your history, and outliers will hit three separate outlier detection algorithms to determine if the data points are truly anomalous.
3. The data stream will be analyzed to note whether there is seasonality and its periodicity, whether there are trends up or down.
4. (This is the coolest step): Based upon the data analysis in step 3, the system will use the appropriate forecasting methods, of the 27 state-of-the-art methods (and gorwing) in our cloud library.  We will spin up CPU's and crank through over 700,000 forecasts and compare them to find the one with the least amount of error.  A best-of-the-best forecast.

Here's the rub.  This whole process, because we are using the power of cloud computing, typically takes a minute or so to run.  We've tested thousands of data streams, and these forecasts are very solid.

PureCloud WFM customers have had access to this approach for about a month-I am curious if you've noticed a change in your forecast accuracy??

8.5.214 General release

• New Forecast Module Interface-WFM Web for Supervisors includes a new forecasting interface, enabling access to existing forecasting functionality and features, but with many user-friendly enhancements, wizards, and tools.

  Note that Web for Supervisors (Classic) Forecast interface is still supported and available.

• New Forecast Module Help-Workforce Management Supervisor Help is a context-sensitive Help that describes the new forecasting interface, including topics describing Forecast Scenario and Master Forecast views and procedures describing forecasting tasks.

  Note that the Workforce Management Supervisors (Classic) Help is still available.

• Forecast Overlays Enhancement-In WFM Web's new Forecast module, supervisors can now adjust the overlay's Spread over distribution to 15 or 30 minutes (in addition to 60).
• New Splash Screen-WFM Web has a new Log In splash screen, displaying the latest Genesys branding and logos.
• New Configuration Options-The following configuration options and [auth] section are introduced in this release:
  • WFM Server Application-[Server] tzdb
  • WFM Web Application-[Functionality] NewSupervisor and [Functionality] ClassicAgent
  • WFM Web, Server, Builder, and Data Aggregator Applications-[auth] provider

  For a complete list of WFM configuration options, see the Workforce Management Options Reference.

• Renewed Java Certificate-WFM Web has a renewed certificate for signing Java code. The certificate provided in previous WFM versions expires on June 11, 2019.
• TLS 1.2 and FIPS 140-2 Security Compliance-TLS 1.2 is supported to provide secure network connections between WFM applications, Genesys Management Framework, and third-party software. WFM supports configurations that use only FIPS 140-2-compliant algorithms in secure network connections. For more information about securing connections, see the Workforce Management Adminstrator's Guide.
• WFM Web UI Launcher-This application can be selected and downloaded using the RUN_JAVA_STANDALONE setting in About > Settings in the UI. After the launcher is deployed, WFM uses it as the default application to open .wfm files in the same session.
• OpenJDK Support-WFM Web and Daemon now support OpenJDK. The new WFM UI Launcher enables clients to run on OpenJDK 11, thereby removing the dependency on Oracle Java versions for which public updates are no longer available.
• Supported Database-WFM now supports Oracle 12c R2.
• Supported Browsers-WFM Web's new Forecast interface supports:
  • Google Chrome 73 or later
  • Mozilla FireFox 60.5 or later

PureCloud WFM and Decisions users now have access to a new class of WFM forecasters.  For years, most WFM vendors have had rather simple forecasting techniques in their WFM platforms. As a result, many companies have built their own home-grown forecasting spreadsheets. 

In PureCloud and the latest version of Decisions, is a new approach to forecasting, one that takes the power of cloud computing and AI to bring the best of the best forecasting technologies to WFM.

Here's how it works.  There are 4 major steps to the forecaster.

1. Historical call center data is consolidated and sent to the forecasting service in the cloud. If you are a PureCloud WFM user, your data is already in the cloud.  If you are a Decisions customer, your data will be sent to our servers.
2. The data will be processed to create a clean data set for forecasting purposes. Missing data will hit a variety of algorithms to fill in your history, and outliers will hit three separate outlier detection algorithms to determine if the data points are truly anomalous.
3. The data stream will be analyzed to note whether there is seasonality and its periodicity, whether there are trends up or down.
4. (This is the coolest step): Based upon the data analysis in step 3, the system will use the appropriate forecasting methods, of the 27 state-of-the-art methods (and gorwing) in our cloud library.  We will spin up CPU's and crank through over 700,000 forecasts and compare them to find the one with the least amount of error.  A best-of-the-best forecast.

Here's the rub.  This whole process, because we are using the power of cloud computing, typically takes a minute or so to run.  We've tested thousands of data streams, and these forecasts are very solid.

PureCloud WFM customers have had access to this approach for about a month-I am curious if you've noticed a change in your forecast accuracy??