Process Mining in Global Business Services (GBS)

Introduction

Global Business Services (GBS) organizations have evolved from transactional back-office centers to strategic partners, demonstrating greater ownership and delivering complex, higher-value services. The focus has shifted from cost impact to business impact, emphasizing improved service quality, customer experience, and resilience. The COVID-19 pandemic further highlighted GBS agility and resilience, leading to significant expansion. However, many GBS organizations face challenges in delivering intended value due to a lack of end-to-end process visibility. Process mining, which monitors processes, highlights inefficiencies, and addresses root causes, is emerging as a key enabler for GBS organizations to deliver enhanced value. This research examines the evolving priorities of GBS, the role of process mining, its operationalization across functions, and includes an enterprise case study. It is intended for GBS and SSC leaders, process excellence leaders, and business transformation teams.

Evolving Priorities of GBS

The Shift from Internal Provider to Value-Add Partner

Traditionally, shared services organizations focused on labor arbitrage and cost savings. With increasing maturity, they evolved to deliver a mix of transactional and high-skill services across functions like finance and HR, and industry-specific operations. Mature GBS organizations now act as extensions of the global enterprise, playing a role in strategic initiatives and impacting end-customers directly. The mindset has shifted from cost-based to business impact- or value-based, aiming to improve customer experience and drive revenue growth.

The GBS Evolution Journey

Everest Group identifies five phases in the GBS evolution journey:

• Arbitrageur: Focus on cost savings, transactional back-office functions, low value beyond arbitrage.
• Service Provider: High-quality delivery of transactional functions, focus on expanding services to deliver complex services.
• Optimizer: Focus on operational efficiency, mix of transactional and high-skill delivery, support in transformation, niche/digital skills.
• Transformer: Focus on advanced digital and innovation capabilities, people, process, tech ownership (Global Process Owners - GPOs), seat at the table in sourcing decisions, global talent hub.
• Integrator: Focus on end-customer experience, revenue growth, and innovation, borderless operating model, global leadership hub, focus on the future of work.

The impact progresses through Cost Savings, Operational Improvement, Customer Experience Enhancement, and Revenue Growth.

Innovation and Digital at the Core

Technology adoption is central to GBS growth. Offshore locations leverage talent availability for technology-led initiatives, scaling automation and digital capabilities to support enterprise digital transformation. GBS centers integrate automation with analytics and IoT. More than 50% of GBS setups expanded digital capabilities in 2020-21, and three in five new centers offer automation. Enterprises expect GBS to take end-to-end ownership of process transformation, not just automate stand-alone use cases. GBS firms are becoming nerve centers for innovation and business partners for digital investments.

Challenges in Delivering Greater Value

Despite advancements, GBS organizations face challenges in scaling up and delivering value, including:

• Access to niche talent in a competitive market.
• Pivoting to new employee value propositions and building a distinguished GBS brand.
• Competing budgets and pressure for cost savings.
• Scaling capabilities across regions and functions.
• Inability to achieve baseline efficiencies.
• Managing non-standardized processes across regions and functions.
• Difficulty in predicting ROI and building business cases for digital investments.

The Role of Process Mining in GBS

Defining Process Mining and How it Fits into the GBS Model

Challenges related to standardization and scaling often stem from limited process visibility and operational transparency. Manual approaches to process discovery and mapping provide incomplete pictures. Process mining offers a fact-based approach to discover processes, enhance transparency, and provide a data-driven view. It leverages event log data from enterprise systems (ERP, CRM, SCM) to discover and analyze processes, generate maps, and extract insights. It visualizes processes in-depth, detects anomalies, and allows for near real-time monitoring and optimization against KPIs.

Process Mining Architecture

The process mining architecture involves several components:

• Data Sources: Enterprise systems (ERP, CRM, SCM) and Legacy systems generate event logs.
• Process Mining Engine: This core component includes Event log data pre-processing, Process map creation, and Insights generation. It utilizes underlying technology components such as data mining, sequence mining, activity clustering, association rules mining, Business Intelligence (BI) capabilities, analytics engines, and predictive/prescriptive capabilities.
• Key Applications: These are categorized into Insights (Discovery & visualization, Process standardization, Conformance checking, Process monitoring, Process simulation, Process improvement) and Actions (System actions, Automation trigger, Next-best actions, Alerts/Notifications).
• Feedback Loop: A continuous improvement loop connects insights and actions back to the process.

Leveraging Process Mining to Enable Intelligent and Efficient Processes in GBS

GBS organizations are building expertise in process management and digital transformation, positioning themselves as process-improvement advisors. Process mining delivers significant value by providing a deeper understanding of underlying processes, supported by strong IT-operations collaboration. It helps identify bottlenecks, recommend improvements, and drive best practices through standardization. Process mining is critical for comparing, benchmarking, and standardizing processes at scale across regions, business units, and functions. It enables monitoring of end-to-end value chains, like Order-to-Cash (O2C), improving overall performance and collaboration.

Process mining applications include:

• Process discovery: Provides end-to-end visibility into as-is processes, including external workflows.
• Process standardization: Helps compare and standardize business processes across teams, departments, business units, and geographies.
• Process conformance: Performs compliance checks and benchmarking to identify deviations.
• Process monitoring: Enables continuous monitoring of process performance against KPIs and offers workforce insights.
• Process simulation: Facilitates what-if analysis and scenario testing to assess KPI impact.
• Process improvement: Identifies bottlenecks and opportunities for optimization or automation.
• Action triggers: Automatically initiates alerts, system actions, or automations for corrective measures.

Operationalizing Process Mining Across Common GBS Functions

Accounts Payable (AP)

GBS organizations excel in finance and procurement functions. AP is a key service impacting cash outflow, operating margins, and supplier relationships. Challenges include high processing costs, long cycle times, manual invoice processing, lack of visibility, and non-standardization. Process mining provides near real-time visibility into invoice processing by capturing data from source systems (e.g., ERP). It monitors AP processes and KPIs, identifies root causes of delays, missed discounts, and opportunities for free cash flow. Process mining can streamline and standardize processes, improve efficiencies, and deliver superior value within faster turnaround times.

Process Mining in AP: Insights, Actions, and Outcomes

• Insights: Monitor KPIs (e.g., invoices processed on time, without errors), identify causes of delays (allocation, duplicates, loss), detect duplicate invoices, highlight missed discounts.
• Actions: Trigger alerts for SLA breaches, initiate automation workflows (e.g., data extraction), recommend high-priority invoices for approval.
• Business Outcomes: On-time payment, higher SLA adherence, increased cash discounts, optimized working capital, and cost savings through automation.

Accounts Receivable (AR)

AR is crucial for cash flow management, focusing on collection prioritization, cash acceleration, and dispute management. Inefficient, manual processes and data fragmentation hinder decision-making, trapping working capital. Process mining provides a consolidated view of AR sub-processes across systems, benchmarks KPIs (DSO, DPD, DDO, ART) across various dimensions, and identifies root causes of problems. It predicts payment likelihood, prioritizes collections, and recommends optimal credit limits to mitigate risks.

Process Mining in AR: Insights, Actions, and Outcomes

• Insights: Consolidated view of AR sub-processes, KPI benchmarking, highlights deviations (late payment, faulty invoice), identifies root causes for delays (master data, manual creation), identifies issues for dispute claims.
• Actions: Recommend optimal credit limits, predict payment likelihood, trigger alerts for follow-ups.
• Business Outcomes: Reduced past-due receivables, lower late payment rates, and freed-up working capital.

Procurement

GBS organizations support procurement functions through spend analytics, requisition-to-PO processes, and master data management. Challenges include managing large supplier bases, data fragmentation, maverick buying, and poor spend visibility, leading to inefficient decision-making and higher spend. Process mining tracks procurement processes using log data, providing a consolidated view of spend activities and supplier performance. It identifies deviations (e.g., maverick buying, non-compliance), highlights manual steps causing delays, and identifies automation opportunities for efficiency and cost savings. It helps reduce catalog leakage and processing time.

Process Mining in Procurement: Insights, Actions, and Outcomes

• Insights: Monitor procurement KPIs (PO cycle time, supplier lead time), consolidated view of spend activities, detect late deliveries, identify manual rework and root causes, identify automation opportunities.
• Actions: Recommend catalog items for purchase orders, notify managers of maverick purchases, alert planning teams about systemic issues.
• Business Outcomes: Increased touchless purchase orders, lower processing time, and cost savings.

Order Management

Order management is vital for customer satisfaction and timely fulfillment. Challenges include ensuring on-time delivery, reducing processing time and costs, lack of operational visibility due to fragmented channels (email, calls, messages), manual processes, and handoffs that lead to errors. Process mining provides an integrated view of order management by consolidating data from transactional systems. It offers real-time KPI monitoring, insights into customer behavior, and helps prioritize orders. It prevents errors by detecting repetitive manual steps and helps resolve order errors. Process mining can predict and update delivery dates, alert relevant teams, and drive automated actions to prioritize orders and fulfillment.

Process Mining in Order Management: Insights, Actions, and Outcomes

• Insights: Unified view of order management across channels, real-time KPI reporting, customer behavior analytics, root cause analysis for delays, automation opportunities for sales order entry.
• Actions: Alerts for credit lines expiry, predicts and updates delivery dates, intelligently splits orders based on on-time delivery likelihood.
• Business Outcomes: Improved customer satisfaction, higher order fulfillment rate, and increased on-time delivery.

Case Study: Deutsche Telekom Services Europe (DTSE)

Context

Deutsche Telekom Services Europe (DTSE), part of Deutsche Telekom's SSC, provides finance, procurement, and HR services. Established in 2016, its objective was to drive cost savings, deliver superior quality services, and improve internal business processes through digitalization, aiming for seamless processes with reduced risks and compliance.

Challenges

As DTSE scaled, it faced challenges including limited process visibility, decisions based on subjective experiences, inability to identify process gaps and root causes, and unclear responsibilities between the SSC and the global enterprise.

Approach

DTSE partnered with Celonis in 2018, initiating process mining with the P2P function and establishing a Process Mining Center of Excellence (CoE) to interface between IT, data scientists, analysts, and executives for smooth implementation.

Outcomes and Learnings

The process mining solution connected systems like SAP and Salesforce, providing visibility, performance monitoring, and gap identification. Over four years, it expanded to 800+ users, improving KPIs like throughput time and automation rate. In P2P, it identified duplicate payments and automation opportunities. DTSE leveraged these solutions to streamline processes, enhance its value proposition, and expanded its use to HR and customer finance. Key learnings include involving process owners and SMEs, early IT onboarding, guiding process experts, and evangelizing the technology through success stories.

As Michael Gudel, Project Manager at DTSE, stated, “Process mining not only helped identify ways to improve the processes that DTSE managed, but also played a key role in providing value-add services, such as process analytics, to other entities of the global enterprise for analyzing and enhancing their internal processes.”

Conclusion

GBS organizations are evolving beyond cost arbitrage to become strategic value-add partners and transformation engines for their enterprises. Process mining provides a data-based approach to streamline and optimize processes across business functions, equipping traditional shared services organizations with advanced capabilities. It enables superior business outcomes such as on-time payments, higher SLA compliance, optimized working capital, and reduced late payments across prominent services like AP and AR. Process mining fosters a deeper understanding of processes, accelerates transformation, and serves as a crucial tool in the automation technology toolbox, delivering strategic benefits to the global enterprise.

About Everest Group

Everest Group is a research firm focused on strategic IT, business services, engineering services, and sourcing. Its research covers the technologies powering these functions, along with related talent trends and strategies. Clients include leading global companies, service and technology providers, and investors seeking to maximize operational and financial performance, transform experiences, and realize high-impact business outcomes. More details are available at www.everestgrp.com.

This study was funded, in part, by Celonis.

For more information about Everest Group, please contact: +1-214-451-3000 or info@everestgrp.com.

For inquiries about this topic, please contact the authors:

• Amardeep Modi, Vice President: amardeep.modi@everestgrp.com
• Bharath M, Vice President: bharath.m@everestgrp.com
• Harpreet Makan, Practice Director: harpreet.makan@everestgrp.com
• Samikshya Meher, Practice Director: samikshya.meher@everestgrp.com

This document is for informational purposes only. Everest Group is not a legal or investment adviser, and its contents should not be construed as such. It should not be used as a substitute for consultation with professional advisors.