Aftersales service
Build aftersales service operations to drive revenue growth, customer loyalty and lower cost to serve.
How AI is changing aftersales service
After a product is sold, the real test of a brand begins. Warranty claims, field service calls, spare parts availability and returns handling are where customer loyalty is won or lost. Most companies manage these operations in silos, with fragmented systems and reactive processes that drive up cost and frustrate customers. AI makes it possible to anticipate failures before they happen and turn after sales service into a revenue stream. Accenture helps companies reduce cost-to-serve, improve first-time fix rates and give customers a reason to stay.
DATA
80%
customers say the experience a company provides is as important as its products and services, making standout service central to growth.
36%
global average supply chain capability maturity, indicating most companies have significant headroom to improve aftersales service performance.
9 in 10
CEOs plan to increase AI investments this year, creating pressure on aftersales functions to adopt AI-powered service models faster.
How Accenture can help in aftersales services
Field service management
We help you schedule, dispatch and manage field engineers so more jobs are resolved first time and at lower cost.
Client pain points
Most field service operations run on reactive processes: a customer reports a fault, a job is logged, an engineer is dispatched. This approach is expensive and slow. Scheduling is manual, parts availability is uncertain and first-time fix rates are low because engineers arrive without the right information or components. Service backlogs build, customer complaints rise and the cost-to-serve stays high.
Why partner with Accenture
AI-powered scheduling and dispatch
Accenture builds intelligent scheduling solutions that match jobs to engineers based on skills, location, parts availability and real-time traffic. Fewer wasted journeys, higher first-time fix rates and lower cost-to-serve.
Salesforce Field Service and platform depth
With deep expertise in Salesforce Field Service Lightning, ServiceMax and IFS, Accenture integrates field service platforms with back-office ERP and parts systems so engineers have the full picture before they arrive on site.
Predictive maintenance to reduce reactive calls
Accenture deploys IoT-enabled predictive maintenance models that identify asset failure risk before a fault occurs. Clients shift from reactive to proactive service, reducing emergency call-outs and extending asset life.
Industry-specific field service configuration
Field service requirements differ significantly across utilities, industrials, high tech and life sciences. Accenture brings sector-specific configuration and compliance knowledge so field service solutions reflect the realities of each industry.
Your path to better field service management
Step 1: Diagnose - Assess current field service performance and identify the biggest cost drivers
Start with a structured diagnostic of your current field service operation: first-time fix rates, mean time to repair, scheduling efficiency and parts availability. Accenture's Enterprise Navigator tool maps pain points across the service workflow and identifies where AI-powered scheduling and predictive maintenance create the fastest improvement in cost and customer satisfaction.
Step 2: Build - Design and build the right scheduling and dispatch model
Accenture works with your team to select and configure the right field service platform, integrate it with your ERP and parts systems and build the AI scheduling logic that matches jobs to engineers. The implementation plan is designed to protect service continuity throughout the transition.
Step 3: Optimize - Go live, measure outcomes and shift from reactive to predictive service
Once live, Accenture monitors first-time fix rates, scheduling efficiency and cost-to-serve against agreed targets. Predictive maintenance models are tuned using real operational data, progressively reducing reactive call volumes and improving the experience for both engineers and customers.
What our field service management services include
- AI-powered job scheduling and engineer dispatch based on skills, parts and location
Match every job to the right engineer with the right parts before they leave the depot, using AI scheduling logic that cuts travel time, reduces repeat visits and improves first-time fix rates. - Salesforce Field Service Lightning, ServiceMax and IFS implementation and integration
Configure and implement the right field service platform for your operation, integrated with your ERP, parts systems and customer management tools so data flows without manual handoffs. - Predictive maintenance modelling using IoT sensor data and asset history
Use sensor data and asset performance history to predict failures before they happen, shifting your service model from reactive call-out to planned intervention and reducing emergency repair costs. - Mobile field service apps giving engineers job information, manuals and parts data on site
Put everything an engineer needs on their device before they arrive: job details, asset history, technical manuals and parts availability, so they can resolve issues on the first visit. - Real-time service backlog management and exception handling
Give dispatchers and service managers a live view of the job queue, with exception alerts that surface delays, parts shortages and at-risk SLAs before they become customer complaints. - Field service performance reporting covering first-time fix rate, MTTR and cost-to-serve
Track the metrics that matter across your field operation and connect service performance data to financial outcomes so leadership can see where investment is improving both customer satisfaction and margin.
Proven, measurable results
15%
increase in compliance levels to the Thames Water Customer Promise.
33%
increase to 96% compliance on key customer touch points.
70%
reduction in customer complaints at Thames Water following the field service overhaul.
Reverse logistics and returns management
We help you process returns faster, recover more value from returned goods and reduce the cost of running a returns operation.
Client pain points
Returns volumes are rising across every sector, but most returns operations were built for a world where returns were the exception, not the norm. Processing is manual, grading is inconsistent and refurbishment decisions are made without reliable data on asset value or repair cost. The result is high cost-to-return, slow credit turnaround for customers and large volumes of returned inventory that sits unprocessed, depreciating in value.
Why partner with Accenture
Returns processing at scale with consistent grading
Accenture designs and operates returns processing workflows that handle high volumes with consistent condition grading, automated routing to repair, refurbish or recycle and clear audit trails for warranty and compliance purposes.
AI-driven returns prediction and pre-authorization
Accenture builds returns prediction models that give supply chain teams visibility into expected return volumes before goods arrive. Pre-authorization workflows reduce processing time and let refurbishment planning start earlier, protecting asset value.
Circular economy and recommerce capability
Accenture helps clients build recommerce programs that recover maximum value from returned goods through refurbishment, repackaging and resale. This reduces landfill, meets circular economy commitments and creates a secondary revenue stream.
Ecosystem integration across carriers and platforms
Accenture integrates returns management systems with carrier networks, e-commerce platforms and ERP to give customers a simple returns experience and operations teams real-time visibility into return status, location and disposition.
Your path to better reverse logistics and returns management
Step 1: Map - Map your current returns flow and identify where value is being lost
Accenture starts with a diagnostic of your end-to-end returns process: return authorization rates, processing time, grading accuracy, refurbishment yield and cost-per-return. This baseline identifies where the biggest value leakage occurs and where AI-powered prediction and automation create the fastest improvement.
Step 2: Design - Design the target operating model and returns technology stack
Accenture works with your team to design a returns operating model that fits your volume, product mix and sustainability commitments. The technology selection covers returns management systems, grading tools and integration with your existing e-commerce and ERP platforms.
Step 3: Implement - Implement, measure recovery rates and build toward circularity
Once live, Accenture tracks return processing time, refurbishment yield and cost-per-return against agreed targets. Continuous improvement cycles use grading and disposition data to increase recovery rates and deliver operational efficiencies over time, building the business case for a full recommerce program.
What our reverse logistics and returns management services include
- Returns authorization and pre-processing workflows with customer self-service options
Give customers a fast, self-serve returns experience while building the pre-processing workflows that capture condition data early and reduce handling cost before items reach the returns center. - AI-powered returns volume prediction and inventory pre-positioning
Use returns forecast models to anticipate volume by product category and pre-position inventory and labor so your returns operation absorbs peaks without delay or cost overrun. - Condition grading and automated disposition routing across repair, refurbish and recycle
Apply consistent grading logic at intake and route each item automatically to the highest-value disposition path, whether repair, refurbishment, resale or recycling, to maximize recovery on every return. - Recommerce and secondary market program design and operations
Design and operate the recommerce infrastructure that turns refurbished returns into a revenue channel, including pricing strategy, channel selection and the fulfillment operations that make secondary market sales viable at scale. - Carrier and 3PL integration for real-time return status visibility
Connect your carriers and third-party logistics partners into a single returns tracking view so your team and your customers can see exactly where every return is and when it will be processed. - Sustainability reporting on returns, refurbishment rates and landfill diversion
Build the data capture and reporting capability that tracks refurbishment yield, material recovery and landfill diversion against sustainability targets, giving your ESG reporting accurate, auditable returns data.
Proven, measurable results
80%
customers say the experience a company provides is as important as its products and services, making standout service central to growth.
20% +
predicted cost savings over five years for a client using Accenture's integrated supply chain control tower and returns management capabilities.
Spare parts management
We help you make the right parts available at the right location so service teams can fix problems first time without carrying excess inventory.
Client pain points
Spare parts inventory is one of the most expensive and difficult areas of supply chain management. Holding too much stock ties up working capital. Holding too little means engineers cannot complete jobs first time and customers wait. Most companies manage parts planning reactively, relying on historical consumption data that does not reflect real demand patterns. When a new product launches or an installed base ages, the forecasts are wrong and service suffers.
Why partner with Accenture
AI-powered parts demand forecasting
Accenture builds demand forecasting models for spare parts that use installed base data, failure rates, service contract terms and external signals to predict parts consumption with significantly higher accuracy than historical averaging. Clients reduce both stockouts and excess inventory.
Parts network design and stocking strategy
Accenture designs multi-echelon parts networks that balance service level commitments against inventory cost. The right parts are held at the right locations: central warehouse, regional hub or engineer's van — based on failure probability and service response time targets.
Integration with field service and ERP platforms
Accenture integrates parts management systems with field service scheduling and ERP so engineers always know which parts are available and where. When a job is scheduled, parts reservations and van stock replenishment happen automatically.
Installed base analytics for proactive parts planning
Accenture builds installed base analytics that track the age, usage and failure history of every asset in the field. As assets age, parts demand patterns change. This intelligence allows service teams to shift from reactive parts ordering to proactive replenishment before failures occur.
Your path to better spare parts management
Step 1: Baseline - Baseline current parts availability, stockout rates and inventory cost
Accenture starts with a diagnostic of your parts operation: fill rates by part number, stockout frequency, excess inventory levels and total parts inventory cost. The diagnostic identifies which parts categories drive the most service failures and where demand forecasting improvements create the fastest value.
Step 2: Redesign - Redesign the parts network and forecasting model
Accenture works with your team to redesign the stocking strategy and build AI-powered demand forecasting for spare parts. The network design balances service level targets against inventory investment across every level of the parts distribution network.
Step 3: Optimize - Implement, track fill rates and drive continuous inventory optimization
Once live, Accenture monitors parts availability, first-time fix rates and inventory value against agreed targets. Forecasting models are updated continuously as real consumption data replaces historical assumptions, progressively reducing both stockouts and excess stock.
What our spare parts management services include
- AI-powered spare parts demand forecasting using installed base and failure rate data
Replace historical averages with forecasting models that use actual asset population data, usage patterns and failure rates to predict parts demand at the right location before a stockout occurs. - Multi-echelon parts network design covering central, regional and field stocking locations
Design a stocking strategy that balances service level targets against inventory investment across every tier of your parts network, from central warehouse to regional hub to engineer van stock. - Automatic parts reservation and van stock replenishment integrated with field service scheduling
Connect parts availability directly to job scheduling so the right parts are reserved and replenished automatically, reducing the manual coordination that leads to delayed jobs and repeat visits. - Installed base analytics tracking asset age, usage and failure history
Build a live view of your asset population that captures age, usage cycles and failure history by asset type, giving your parts planning team the data to anticipate demand rather than react to it. - Excess and obsolete parts identification and disposal program management
Systematically identify slow-moving and end-of-life parts before they become write-offs, and manage disposal or redistribution programs that recover value and free up working capital. - Parts availability reporting covering fill rate, stockout frequency and inventory cost
Track fill rates, stockout frequency and total inventory cost in one view so service and supply chain leadership can see where parts performance is affecting field service outcomes and where to prioritize investment.
Proven, measurable results
9x
improvement in inventory counting speed at Zuellig Pharma's warehouse using 5G-enabled drone inventory management, with 95% counting accuracy.
30%
improvement in pick productivity at Zuellig Pharma following warehouse automation and AI-driven inventory management.
Our leaders
Mark Oldani
Managing Director, Supply Chain and Engineering, After-sales Service, Americas
Markus Pfeifer
Managing Director, Supply Chain and Engineering, After-sales Service, EMEA
Christopher Poppy
Managing Director, Supply Chain and Engineering, After-sales Service, Americas