IRS Partner Request: Call Center Workforce Management Modernization and Transformation support

A woman-owned 8(a) small business IT and Business Process Outsourcing specialist is seeking a partner (large or small) who has direct past performance and/or relationships with the Internal Revenue Service and/or who have direct expertise and past performance supporting efforts to develop, test, and integrate an enterprise grade workforce management solution.  

This is in relation to an RFI posted by IRS earlier this week. Complete details as provided by the requestor are provided below.  

If you have specific capabilities and/or past performance supporting similar efforts at IRS, please contact us here or comment below for all to see. All responses will be passed on to this SDVOSB Prime requestor.  

“Going into Filing Seasons 2024 and 2025, the IRS has prioritized improving the call center’s ability to respond to demand as a major innovation focus area. A primary opportunity the IRS has identified is to successfully embed cutting-edge call center workforce management (WFM) tools, including enhanced forecasting, scheduling, and routing. Investing in these capabilities is intended to help the IRS better predict hiring and training needs, match CSR talent to demand, and significantly improve employee and taxpayer experience.  

This effort is taking place within the IRS’ broader transformation journey, where call center operations have surfaced as a top priority overall for the organization. Already, the IRS is investing heavily in establishing a new WFM operating model that shifts forecasting from a legacy excel-based system to using Alvaria, an industry standard WFM tool, within the accounts management call center environment. However, much work remains to expand utilization of Alvaria to all call centers within the IRS and to build on the historical data underpinning the Alvaria forecasts being stood up with more sophisticated data and methodologies.

Scope 

Program Goals: Our ultimate goal is to develop, test, and integrate a best-in-class workforce management solution for the IRS’ call center environment that efficiently and accurately matches supply to demand while ensuring agents who answer calls are equipped to respond to taxpayer needs. 

Areas of the program going well (no change): The IRS is in the process of transitioning its WFM tools from an excel-based model to Alvaria, an industry standard WFM tool, for its primary Accounts Management call center. This first step will enable us to have a baseline forecast based on historical data and begin to derive schedules tied to demand instead of supply. 

Areas of the program that need change: Our next focus is to build on the Alvaria tool with robust, data driven, and cutting edge WFM methodologies across all call center sites within the IRS, ensuring a major step change in both the accuracy and efficiency. We seek to achieve a best–in-class WFM solution in time for filing season 2025, with improvements rapidly deployed in the first half of FY 2024. 

Program Risks: Our four major risks are 1) change will not be affected quickly enough to see meaningful results within the next two filing seasons. 2) Processes will be insufficiently embedded, leading to limited uptake and eventual abandonment of new methodologies by the organization. 3) The designed system will be insufficiently holistic to unlock full value, failing to account for upstream or downstream impacts of changing WFM processes. 4) The methodologies put in place for WFM are insufficiently sophisticated to truly match supply and demand in the complex environment of the IRS call center. 

Due to the dynamic nature of transformations, modifications to increase the level of support are highly likely. The contractor should be prepared to increase support based on the needs of the Government. Any increase in scope will have to be determined fair and reasonable. 

Problem Statement 

The IRS currently does not have a methodology in place to provide accurate forecasting at a tactical, day to day level, or routing and scheduling systems that are underpinned by a clear understanding of supply and demand. Our goal is to rapidly develop, test, and integrate a best-in-class workforce management solution that brings these pieces together to consistently and accurately match supply to demand while ensuring agents who answer calls are equipped to answer. Our target is to reach a solution that both predicts and matches supply to demand with a 90% level of accuracy both daily and monthly, 90% of the time, in our forecasts before filing season 2024. 

There is an urgency to the work to stand up a fully operational and truly best-in-class system over the next two filing seasons. The IRS’ call centers have a high level of complexity, with over 18,000 call center representatives spread across the nation, answering calls on nearly 100 different applications each requiring different agent skill sets while also managing paper inventory. A successful solution will need to be bespoke and sophisticated enough to account for both high seasonality and frequent market roiling events (e.g., tax law changes) via cutting-edge approaches that can rapidly adjust forecasts in a constantly changing environment. 

Objective(s).  

We are seeking a strategic partner to support in developing, integrating, and embedding the following in advance of filing season 2025: 

• Advanced modeling and professional-grade forecasting methodologies that build beyond historical data to leverage leading-edge innovations in predictive analytics.  
• Best-in-class scheduling processes, building on improvements to forecasting to derive optimal schedules for call center environment, considering potential opportunities to improve both taxpayer and CSR experience. 
• Optimized routing structures to build a long-term queue structure that aligns taxpayer journeys to agent skillsets, informed by industry best-practices within a large-scale call center environment with nearly 100 applications and 18,000+ CSRs. 

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Looking for a consulting partner with past performance at the IRS? Click Here  You can filter the list by several key indicators, to include socio-economic status, NAICS, Contract vehicle, etc.   

Firms drawing the most attention at the IRS:   

Included below is a list of the large and small companies we have noted as drawing the most views by Government and industry leaders on the OrangeSlices AI consultant directory since the beginning of 2023 and that bring direct past performance and/or related relationships in support of the Internal Revenue Service.   

• OneZero Solutions      
• Makpar   
• Sky Solutions   
• 22nd Century Technologies    
• Brillient 
• ECS Federal         
• Anika **     
• Nüvitek       
• Booz Allen Hamilton         
• Chevo Consulting **       
• Maximus           
• Coforma **     
• Akira Technologies  
• EIDOS Technologies        
• Rapidiant        
• Applica     
• VIKINT 
• Leidos     
• Analytica      
• Technuf   
• Integrated Systems (ISI)      
• Citizant          
• SD Solutions        
• Ekagra         
• Vibrantech Solutions             
• eTelligent **         
• SoKat         
• INADEV **         
• Zeva          
• IMC         
• Truss   
• Accenture       
• Senture         
• Deloitte             
• Intact Technology         
• Precise Software Solutions         
• SAIC          
• Disruptive Solutions         
• GDIT  **         
• Cybermedia Technologies (CTEC)         
• CGI Federal **         
• ICF **       
• TechOp Solutions  
• Peraton          
• iTech AG **         
• TISTA         
• ITC / Dotit JV **         
• NTVI Solutions       
• Thinktek   

** An Elev8 GovCon Honoree, noted for a corporate culture that demonstrates its own excellence, making the company a beacon for talent, for partners, and for clients.      

We cannot and will not speculate here as to the reasons for the increased interest, but whether it is a company evaluating them as a potential partner; a federal acquisition leader doing their due diligence; or a consultant weighing their next job move, this group of companies has been receiving increased interest.  

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