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MSP 4.0: FROM CONTINGENT WORKFORCE MANAGEMENT TO CONTINGENT TALENT EMPOWERMENT 13 www.everestgrp.com | EGR - 2021 - 25 - V - 4434 MSPs can bring in the right people expertise (category managers with strategic sourcing expertise) and the right digital capabilities (especially the right analytics tools) to effectively deliver S2C and strategic processes. The combination of the right analytics and strategic sourcing expertise helps to identify the best sourcing strategies and balance the three project aspects – cost, quality, and timeliness – while ensuring that the organization has access to the skills they need as Exhibit 10 shows. EXHIBIT 10 Benefits of analytics and strategic sourcing expertise in services procurement Source: Everest Group (2021) Type of challenges Description Potential solutions with data Price comparison l This is the most critical challenge associated with sourcing l It is important to look under the hood beyond the overall cost or price of the project to understand what constitutes that cost Data can be leveraged for comparison and benchmarking of the overall project price/cost as well as to understand what constitutes that "price" (suppliers' rate card analytics) l It is important to track the number of people assigned and the time they spend on the assignments l Enterprises need to understand the experience and quality of assigned people to understand how pricing is impacted by it l Location of the people (onsite or at an offsite or low - cost offshore location) also has a big impact on the price Going beyond "category" management While managing services procurement, it is important to go granular into subcategories beyond just categories As an example, IT is one of the biggest categories in services procurement, but consists of various sub - categories with further subdivisions within them, with widely varying supplier strengths across each (e.g., application services and cloud & infrastructure services with further subcategories within them) Scope of services l There can be challenges in defining service specifications l Intangibility associated with certain services can also be a challenge for enterprises l Creation of a repository of SOW documents for standard services can help in quicker creation of new SOWs l Previous SOW documents can be parameterized to allow for quick building of new SOWs l Artificial Intelligence (AI) / Machine Learning (ML) can be leveraged to identify deviations from standard terms and the consequent impact on pricing Other specifications Need for specifications on output/SLAs/KPIs instead of technical measurements This requires detailed data around various services categories, some of which include the following: l Benchmark time taken for similar projects l Typical ways to measure outcomes (list of commonly used SLAs/KPIs) l Identification of SLA/KPI benchmarks that determine "good quality" Quality comparison l Involves assessing the vendor/supplier as well as its people l Curation of performance data on suppliers and their people from previous engagements can help with quality comparison – data cutting across companies and labor types (permanent / temporary / Independent Contractors (ICs)) will be more helpful l Evaluation of what constitutes "skilled people" – in terms of years of experience, nature of experience, and type of service certifications will help assess quality

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