Choosing Wisely: Expert-Led Comparisons of Leading WFM Software for Contact Centers – Forecasting (1 of 10)
Navigating WFM Software Choices with Expert Guidance
Intro
It all starts with foundation and in every customer facing organisation, this foundation is called forecasting. We all know the operational and financial challenges that arise with the forecasts being off and luckily there are tools to support with getting them as accurate as possible.
Let’s explore some of the strengths and weaknesses in the forecasting capability of Calabrio, Verint, NICE IEX, Alvaria, Genesys and injixo.
Verint
Verint is one of the most well-known WFM tools on the market with a rich history under the belt. It offers a comprehensive set of features that handle all aspects of WFM, including advanced forecasting capabilities, ensuring seamless and efficient business operations.
The newest version has improved user-friendliness and features a more intuitive design, enhancing the overall user experience
Strengths
AI-Powered Insights: Verint leverages sophisticated AI algorithms to deliver highly accurate demand predictions. These predictions are further refined by the platform’s ability to analyse the impact of various events using advanced forecasting bots.
Comprehensive Cross-Channel Forecasting: Verint excels in managing forecasts across a diverse range of channels. It uses a variety of methodologies to prepare for immediate and deferred channels as well as other work types, including project-based time requirements. It also allows the user to fetch backlogs in the calculations thus taking into account additional non-phone workload activities.
Dynamic Real-Time Adjustments: The platform offers the capability to adjust forecasts in real time based on actual performance and changing conditions, providing enhanced flexibility and responsiveness.
Weaknesses
Standalone Capacity Forecasting: The platform’s long-range forecasting and staff modelling are conducted in a separate client, which is basic, inflexible, and not well-integrated with the main platform, limiting its overall utility.
Complex Configuration Requirements: Setting up and fine-tuning the forecasting models in Verint can be complex, often necessitating specialised knowledge or training.
Calabrio
Calabrio is a leading provider of Workforce Engagement, Workforce Management and Analytics solutions, dedicated to helping contact centers improve their operations and customer service.
Calabrio WFM forecasting is a powerful tool that helps organisations accurately predict workload and optimize staffing. By leveraging advanced analytics and machine learning, it enables contact centers to maintain high service levels, improve customer satisfaction, and achieve cost efficiency.
Strengths
Multiple ways to generate a forecasts volume: There are several ways to generate a forecast in Calabrio WFM from user driven, AI Assisted and fully automated. Depending on your organisation you may find one better than the other. Calabrio does use a variety of forecasting methods and is assisted by machine learning and AI.
Allows for user inputs into forecast creation, so there are no surprises - Calabrio forecasting provides you with the ability to build your own forecast using data you decide whether that be last year, the last 2 years or even the last 6 months, you can decide all the inputs that go into your forecast.
Intuitive user process for creating forecast means Calabrio suits all levels, from novice to experienced planners. It’s automated forecasting tool allows you to create accurate forecast is a few simple steps.
Weaknesses
Lacks some of the forecasting methodologies used by other solutions and offers no way to account for external drivers.
Some of the automated forecast can give strange results if you have limited data. The automated forecast uses a pre-defined data set, so if this is limited or volatile the results may not be as accurate as required.
Long Asynchronous channels can be a problem. - It does struggle with channels that have long SLA’s, longer than 30 days.
NICE WFM
NICE Workforce Management (WFM) is renowned for its robust and proven track record in forecasting capabilities, utilised by numerous clients globally. The original weighted moving average employs a comprehensive methodology that examines an 13-week history to identify interval trends, seasonal monthly patterns, and specific week-within-month trends. In addition to the original methodology, there are further forecasting methods using regression, exponential, and smoothing approaches. This multi-faceted approach usually ensures high accuracy in forecasting. Additionally, NICE WFM offers flexibility, allowing users to take control over special days or adjust forecasts at various levels, including weekly (via a long-term planner), daily totals, and at specific intervals, thereby catering to dynamic operational needs.
Strengths
Comprehensive Methodology: Utilises an 13-week history for analyzing interval trends, seasonal monthly trends, and week-within-month trends, ensuring accurate and nuanced forecasts.
Flexibility and Control: Allows users to manually adjust forecasts for special days and make changes at the weekly, daily, and interval levels, providing adaptability to unique business requirements.
Multi-skilled Efficiency: Forecasts multi-skilled efficiency through blending, optimising the utilisation of a workforce with diverse skill sets.
Weaknesses
Complexity: The comprehensive nature of the system can be complex, potentially requiring significant training and expertise to utilise effectively.
Special Days Adjustment: Manual adjustments for special days, while flexible, can be time-consuming and prone to human error.
Initial Setup: The initial setup and customization of the system to fit specific business needs can be resource-intensive.
No CX/Platform-Wide Forecasting: Lacks the capability to forecast using different forecast drivers not defined in contact queue structure, which limits the ability to lead forecasting through customer journeys or overall customer base/user trends comprehensively.
Alvaria/Aspect
The Alvaria Workforce/Aspect eWFM solution offers a true enterprise-level forecasting tool, leveraging decades of experience and combining proprietary forecasting methods with the Holt-Winters method to ensure robust predictions. The solution excels in its flexibility..
Designed for enterprise level contact centres, it includes simple to use tools such as Allocate to split your estate level forecasts across multiple sites or outsource partners with options to dictate the split or using expected staffing levels to optimise the share.
Strengths
Allocate, Assume, Override: A varied toolkit that makes managing multiple sites, partners or clients easy, efficient and insightful. Making it an ideal solution for those who have outsource partners or BPOs themselves.
Flexibility and Control: Leveraging the scenarios or the override option, you really do have control over the forecasting. With Auto Run capabilities you spend less time on admin and more time on value add activities.
Multi-skill Your Way : If you’re in a blended skills area or if you want to split your agents schedules using a rule engine, multi-skilling is a breeze.
Weaknesses
Visuals: The built-in visuals are somewhat limited, primarily offering text-based options. However, this is mitigated by the export feature, which allows you to view and analyse the data in any tool and format your business requires.
Multi-Channel Complexities: While the Multi-Channel options are robust, configuring them can be complex and time-consuming. Fortunately, version 23 introduces improvements, integrating some of the configuration processes into the Auto Run system for greater efficiency.
Visibility: Unlimited What-If scenarios are fantastic! However, the current solution lacks a quick and easy way to compare them directly. Fortunately, the export option comes to the rescue, enabling you to create comparison packs in any format—perfect for those dreaded business planning meetings.
Limited Forecasting Methods: Limited Forecasting Methods: The automated forecast method is restricted to volumes using the decomposition method. For propensity-based forecasting or cause-and-effect analysis across different lines of business, external modelling is required. These forecasts can then be integrated into the solution using the adjustments or override options.
Genesys
Genesys WFM (Workforce Management) offers forecasting capabilities to help contact centers accurately predict and plan for future contact volumes.
Genesys WFM utilises various Artificial Intelligence (AI) models and techniques to enhance the accuracy and effectiveness of its forecasting capabilities. The software does not let you select any specific AI method, as it selects the method based on the quality and volume of the data being analysed, combined with the objectives given for the forecast.
Strengths
The user of a Genesys Call Routing platform has a clear and obvious advantage in using Genesys WFM due to the close integration of data and configuration, which makes forecasting and data collecting for forecasting streamlined and low effort.
Genesys has a 20+ year history of WFM, providing a mature and well integrated, feature rich product.
When Genesys Call Routing is used for distribution, it can use WFM Targets, allowing contact centre operations to apply changes speedily and easily by reassigning tasks to agents.
Due to being part of the Genesys platform, reporting, realtime monitoring and employee management is part of the same UI and work stream, where data and configuration is maintained where it originates and used where it is needed.
Weaknesses
Genesys WFM has no capacity planning function (on the roadmap for late 2024)
When integrating with other call centre tech platforms, media streams et al, there is a substantial cost to create and maintain data flow, and a risk of outages and data corruption
Genesys WFM for Cloud is not as feature rich and user friendly as the premise version, where the most obvious lacking functions compared are staffing calculators, agent preference patterns, and meeting planners.
injixo
injixo offers a comprehensive Workforce Management (WFM) software solution designed to streamline forecasting and scheduling processes for specifically contact centres. Leveraging modern technologies, injixo aims to optimise workforce efficiency and enhance operational performance.
Understanding trends and patterns in your data is crucial for making clear, accurate predictions for the future. injixo provides automated forecasts that are continuously updated based on the latest historical data. This ensures organisations have the most reliable forecasts up to 365 days in advance for calls, chats, emails, social media, and more.
Strengths
Integration Capabilities: injixo supports standardised integrations that simplify data acquisition and processing, facilitating seamless operation across the platform.
Flexible Forecasting Methods: The software excels in forecasting trends and seasonal variations in temporal data, incorporating variables in the shape of self-defined events to enhance predictive accuracy.
User-Friendly: Known for its intuitive interface, injixo is accessible and straightforward, making it suitable for users with limited experience in forecasting.
Weaknesses
Limited AI Integration: While injixo provides reliable forecasting capabilities, it may lag behind competitors in advanced AI-driven forecasting methods, potentially affecting predictive accuracy in complex scenarios.
Scalability Challenges: Some users have reported scalability issues, especially in large-scale contact centres with multiple workflows and diverse operational needs.
Customisation Complexity: Advanced customization for experienced forecasters may be challenging, lacking transparency in visualising event impacts and applying detailed regression analysis.
Summary
In the competitive landscape of Workforce Management (WFM) software, leading providers such as Verint, Calabrio, NICE WFM, Aspect, Genesys, and injixo all offer good solutions with a variety of strengths and weaknesses. These platforms are great at leveraging contact data points, like queue-based metrics, to lead their forecasting efforts. However, there is a clear challenge and opportunity for all WFM software providers to evolve their methodologies.
Currently, these WFM solutions focus on traditional contact data points for forecasting rather than prioritising the customer journey or customer experience (CX) as the primary driver. This traditional approach might not align well with your business’s aims to enhance customer satisfaction and reduce operational costs through automation or AI-driven self-service gains.
The need for a paradigm shift in forecasting software is evident. Software providers must consider developing solutions that integrate customer-centric data to lead forecasts more effectively. Such an evolution could significantly improve the accuracy of predictions and better meet the needs of modern businesses.
For companies, especially those with a non-static customer base and high volatility, it is crucial to set realistic expectations regarding these software solutions. Users might find themselves needing to develop custom solutions or manual forecasts outside the provided tools to meet their specific needs. This necessity underscores the importance of adaptability and the potential benefits of a more innovative approach to WFM forecasting.
Conclusion
The current state of WFM software highlights a significant opportunity for innovation. While these solutions offer valuable tools and functionalities, they largely depend on contact data points, which may not fully align with the evolving needs of businesses focused on customer-centric forecasting. As the industry moves forward, there is a pressing need for WFM software providers to rethink their approach and develop solutions that better integrate customer journey data, thus providing more accurate and actionable forecasts. Until then, businesses with high volatility in changes should prepare to supplement these tools with external solutions, and manual forecasting, and recruit amazing forecasters to achieve the best results.
FYI - Calabrio can do 30 day SLAs