Customer Service, Returned Goods & Warranty – Medical Devices: Standardization & Automation Reduce Costs, Cycle Times

Client situation

For years, the product-return volumes for this company’s medical devices grew predictably and proportionately with sales by region.

Managing returns and related compliance was relatively simple for each region and product line. But over the course of several years, the unpredictability of these returns soared—and was still growing.

The total returned goods volumes were in line with industry norms, but it became almost impossible to complete processing while meeting the regulatory cycle times and documentation requirements. Each of its three global returns processing centers handled their assignment somewhat differently. Despite the company’s numerous “standard operating procedures” (SOPs), there were variations among products, regions, locations, even across employees in the same location.

These inconsistencies thwarted the company’s desire to centrally triage returned goods processing across locations, balance all available processing capacity, and keep cycle times within regulatory limits.

Attempting to solve the problem, the company invested heavily in a cloud-based Returns Management Application or RMA. As initially installed, the technology was cumbersome to use. Employees disliked keying in the extensive data and status updates required. They felt that these added tasks simply slowed them down. And the situation only deteriorated further:

• Cycle times eventually exceeded the industry average by nearly double, and sometimes more.
• Compliance violations (read: “financial liability exposure”) skyrocketed.
• Customer experience declined.
• Returned goods processing costs increased sharply.

None of this was helping to position the company to achieve its aggressive growth strategy targets. The company wasn’t unwilling to change; nor did they lack the budget to make changes, as their hefty RMA investment made clear. They were simply gridlocked and frustrated with prior, disappointing efforts. They had three major goals:

• Pinpoint the problems
• Smooth out the variance
• Make better use of their three state-of-the-art returned goods processing centers

The Lab’s database of standardization & improvement templates convinced management it was possible.

Client Description, Project Scope, Objectives

This global top-ten medical-device subsidiary maintains 20 facilities for operations and manufacturing. It sells & services products in over 100 countries. Product return operations included 450 employees in three global locations throughout the returns life-cycle:

• Sales/Customer support
• Production
• Engineering
• Returns group

The principal objective was to develop a broad, inarguable consensus on the existing returns processing operations including returns routing decisions. The documentation developed would include comparative process maps and reliable data on:

• Actual “touch time”
• Total cycle times
• Administrative quality
• And more

Overview: Phase I, Analysis and Design

The Returned Goods & Warranty (RGW) transformation initiative began with an eight-week, Phase I analysis. It documented the end-to-end (E2E) business processes from annual returns planning to individual product authorization and shipping, including the hand-off to the appropriate parties within the business, including Repairs, Replacements, and Compliance/Legal.

The Lab’s standardized process-map and discovery templates enabled documentation of more than 85 percent of work activities (approximately two minutes each, or less), while only requiring one hour per week of any subject matter expert’s (SME’s) time.

The Lab’s Business Standardization Platform and data science models mined, compiled, and generated insights for the maps from internal client applications:

• Event logs
• Work product volumes
• Cost-center data
• And more

The Lab’s external data provided benchmark comparisons, best-practice comparisons, and automation use-case comparisons.

Coordinating and reconciling the internal data and external benchmarks across three regions resulted in E2E maps that could easily be directly reviewed, refined, and validated by all 450 employees—even with the company’s far-flung locations across the globe.

The Lab’s analysis revealed that the returns process needed to be divided into three buckets—low, medium, and high—depending on the complexity of the device being returned. The low end dealt with simpler (yet higher-volume) products such as catheter tubes, whereas the high end was dedicated to more complicated, lower-volume (yet higher-compliance/liability/risk-exposure) products such as heart pacemakers.

This segmentation—aligned with individual employee skill levels—solved the disparity and delay of having “over-qualified” technicians handling simple, higher-volume product returns that could be processed by less experienced employees. 

The findings also revealed the need to standardize processes and activities across the different locations, to realize the goal of transferability and enable a central point of triage and capacity-management for all returns.

Overview: Phase II, Implementation

This Phase I effort delivered a self-funding business case and work plan that launched an eight-month, Phase II transformation project. Improved performance was achieved with robotic process automation (RPA), workflow automation (minimal), and more effective and extensive use of the previously installed RMA platform.

The eight-month, self-funding Phase II implementation effort delivered immediate results:

• Increased productivity
• Compressed cycle times
• Improve customer service
• Meaningful cost reduction

Improvement goals were established by area and or by E2E business process, and the organizations involved could perform the work with any mix of resources they chose:

• Internal resources
• The Lab’s resources
• Others

Returned Goods Improvement Examples: Phase II, Implementation

The Lab implemented more than 250 standardization, analytics, and automation improvements to improve efficiency and increase service levels. Examples:

IMPROVEMENT EXAMPLE #1 Service-level segmentation

The Lab helped to create three tiers—and standardized E2E business processes—for product returns, based on product complexity (high, medium, or low). The most valuable near-term benefits:

• Centralized triage capability established ongoing refinement with AI
• Average capacity utilization doubled across sites
• Over 70 percent of simple returns processed by less experienced employees.

Some simple tasks—such as prep and newly created “pre-processing” tasks—can now be handed off to sales reps, or even offered as a self-service customer option.

IMPROVEMENT EXAMPLE #2 Automated administration of the RMA platform

The company’s problem here was a common one: Their initial configuration of their sophisticated RMA platform failed to take advantage of many powerful features—which actually would support multi-tier segmentation and global scale. The Lab helped the client’s IT team to attune the RMA more closely to the newly-standardized business processes—reducing administrative tasks by about half. Next, RPA bots assumed approximately 80 percent of the remaining “swivel-chair activities” (data input and status updates) which had previously burdened the returned-goods-processing employees.

IMPROVEMENT EXAMPLE #3 Standardized inconsistent performance data

The lack of standard customer service methods reduced the comparability and integrity of both performance data-capture and service level reporting (for regulatory needs). Each location interpreted definitions differently, used inconsistent data formats, and performed work sequences differently. This affected a range of issues from warranty coverage through visibility of work-order status. The Lab implemented standardized data taxonomies and templates that dovetailed with operating procedures and data-quality-tracking key performance indicators (KPIs).

Post-Implementation Support, Sustainability & Automation

The Lab provided hassle-free, post-implementation hourly sustainability support for this client to maintain automations, process standardization, and operational data analytics models implemented during the Phase II engagement.

If the client’s team was not up-skilled enough to perform any needed automation updates, they leaned on The Lab for Tier 3-level support. If analytics dashboards required additional views or data connected, The Lab’s team was a simple phone call away.

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