RPA Factory Talent Fulfilment at a Fortune 500 IT Services Provider — 35% Talent Cost Reduction, 84% Onboarding Time Crunch
MindMap RPA Factory delivering Junior-and-Senior RPA Developers, RPA Business Analysts and RPA Solutions Architects under a flex-on-demand model with 7-day lead-time.
The challenge
The client — a global Fortune 500 IT-services provider with digital-products, digital IT-services and cloud-based data-engineering-and-automation services across more than 166 locations and a staff strength of more than 250,000 people globally — was amongst the global market-leader in digital-transformation services and was experiencing a major spurt in demand for enabling automation using RPA for its customers. Owing to the inherent complexity in the nature of such services and the short shelf-life of projects (mean duration of 3 months), the customer had a need to rapidly augment the existing staff-strength with temporary-staff across roles such as Junior RPA Developer, Senior RPA Developer, RPA Business Analyst and some other niche roles like RPA ML Architect and OCR/ICR Specialist.
The typical process of hiring internally as a resource-fulfilment mechanism for these positions had structural challenges. Long and time-consuming lifecycle from the point of raising a new resource-request to the onboarding of a new full-time employee; high overall total-cost of resources as they need to be retained-or-benched post-project-closures; missed-revenue-opportunities due to the delayed response-cycle; typical high attrition-rate for RPA-resources due to high industry-demand resulted in an unreliable internal talent-pool.
Quantifying the problem statement made the scope clear: 200+ new positions raised as new requests every month; high average onboarding-time of employees of approximately 45 days; approximately 34% attrition-rate in RPA-resources leading to an unreliable internal talent-pool; up to 33% extra cost spent on resources for longer retention-periods as full-time employees and salaries paid in training-period; approximately 20% of requests not closed on time due to high volume of manual work; out of the above estimated approximately 25% of new-requests lost due to untimely-closure leading to loss of revenue.
The approach
MindMap implemented the MindMap RPA Factory as an alternative hiring model for the temporary staff-augmentation in a talent-on-demand model. The flex-on-demand talent-hiring uses the MindMap pool of RPA-resources with the structured per-position engagement process.
Phase one was the per-position request workflow. New requests are sent out by the hiring-team to MindMap's RPA Factory SPOC as and when new demand arises. In a sample period of one month, 42 such independent requests were made.
Phase two was the per-position profile-presentation workflow. For every position to be hired for, MindMap presents the customer with 3 alternative resource-profiles with a turn-around-time of 24 hours for profiles to be shared. All profiles shared meet the pre-required criteria for available tool-certifications, overall years-of-experience, immediate-availability to join, and other position-specific requirements.
Phase three was the per-position interview-and-selection workflow. Interviews are conducted with the business SPOCs at the client's end and in some cases also with the client's end-customer to get approvals-and-buy-ins. Alternative profiles are shared based on any feedback on the previously-shared profiles; alternatively, selected-profiles are onboarded immediately.
Phase four was the per-resource onboarding-and-engagement workflow. Onboarded profiles are signed into a contract aligned to a pre-agreed resource-skill-unit-level rate-card, and monthly invoices are raised by MindMap for the resources. The lead-time across the end-to-end engagement is less than 7 days from the initial request to the resource-onboarding.
The pre-built building blocks
Rather than commission a ground-up build, the engagement leaned on MindMap's pre-built accelerator library — production-tested components that compress what would otherwise be a six-to-nine-month build into weeks.
Workflow Automator
RPA-resource pool covering Junior-and-Senior Developers across UiPath, AA, BP
Workflow Planner
Per-position request-and-engagement workflow management
Process Assessment Engine
Per-resource skill-validation and per-position profile-matching
Customer 360
Per-resource engagement-history and customer-fit context
The architecture
The MindMap RPA Factory operates as a structured talent-fulfilment engine with the MindMap-managed pool of RPA-resources across the required roles (Junior RPA Developer, Senior RPA Developer, RPA Business Analyst, RPA Solutions Architect, and the niche-roles including RPA ML Architect and OCR/ICR Specialist).
The RPA-resource-pool maintains the per-resource skill-and-certification profile (the UiPath, Automation Anywhere or Blue Prism tool-certifications, the per-resource project-and-domain experience, the per-resource availability-window). The pool composition is structurally maintained to support the per-position-request fulfilment within the 24-hour profile-presentation SLA.
The per-position request workflow uses a structured SPOC-based intake pattern with the appropriate per-request requirement-capture (the required skill-set, the required experience-level, the required availability-window, the required engagement-duration). The intake supports the per-request profile-matching workflow.
The per-position profile-matching workflow uses the structured per-position-and-per-resource match-scoring with the appropriate top-3-profile selection. The match-scoring considers the skill-fit, the experience-fit, the availability-fit and the customer-fit (the resource's prior-engagement-experience with comparable customers).
The per-resource engagement-management workflow handles the per-resource onboarding-to-the-client-environment, the per-resource performance-tracking, the per-resource customer-relationship-management and the per-resource off-boarding at the engagement-end. The engagement-management maintains the per-resource quality-and-feedback record for the future engagement-fulfilment work.
The financial-management layer handles the per-position rate-card-aligned billing with the appropriate per-resource monthly-invoicing.
The numbers behind the story
Financial benefits include approximately 35% reduction in total talent-ownership cost; revenue-leakage cases reduced by 50% for projects lost due to non-fulfilment of demand; and reduction in resources invested in for future-projects resulting in significant cash-flow benefits.
Operational benefits include between 25-38 days improvement (up to 84% improvement) in lead-times to onboarding; 85% first-time acceptance-ratio for all profiles shared; and >50 positions closed for a sample month with excellent feedback from business.
Strategic benefits include improved end-customer experience; highly-scalable solution for rapid-and-effective on-demand talent-fulfilment; frees up cash-flows in resources-investments; better business-agility to take up niche-skills-projects; and faster lead-times to project-implementations.
The programme's curriculum was co-developed and BPM-specific, spanning structured certified BPM and Digital BPM professional courses delivered across both online and classroom formats. The client's learning leadership framed the goal as keeping the workforce relevant against a shifting BPM landscape and the new people-skills it demands.
An unexpected outcome: the MindMap RPA Factory model has become a structural-template for the IT-services provider's other niche-skills talent-fulfilment requirements. The provider has been progressively extending the model to cover the adjacent technology-skill areas where the same structural-challenges (high-demand, short-project-shelf-life, structural-attrition) apply.
“MindMap's RPA Fulfilment Centre has been a big strategic win and a market-differentiator for us in being able to be truly agile with RPA-resources fulfilment. Thirty-five per cent total-talent-cost reduction, eighty-four per cent onboarding-time-crunch, and the flex-on-demand model that supports our customer-engagement agility.”— VP and Global Talent Development Leader· Fortune 500 IT Services Provider
Why MindMap was chosen
The IT-services provider had previously evaluated traditional staffing-agency partnerships for the temporary staff-augmentation. The traditional staffing-agency model had structural-limitations: the per-resource skill-validation was inconsistent, the per-resource quality was variable, and the per-resource engagement-management was structurally weak.
MindMap's structured RPA Factory approach — with the MindMap-managed pool of RPA-resources across the required roles, the structured per-position profile-matching workflow, and the per-resource engagement-management with the appropriate quality-and-feedback record — was the structural differentiator. The approach delivered the talent-fulfilment with the structural-quality-assurance that the traditional staffing-agency model had not been able to deliver.
Our embedded RPA-talent-management expertise on the delivery team (two former RPA-practice-leads from peer IT-services firms and a former RPA-talent-development specialist) was the third factor. The IT-services provider's talent-development leadership valued the team's understanding of the RPA-talent reality and the per-skill-set development-and-engagement patterns.
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