All company names, product names, tools, regions, and individuals have been deliberately generalised so the organisation and project lead cannot be identified, while the learning value and credibility remain intact.
Building a Scalable Asset Management System to Eliminate Waste and Improve Quality in a Professional Services Organisation
How a Lean Six Sigma Green Belt project reduced defects by over 90% and eliminated hundreds of hours of non-value-adding work
Introduction to Asset Management
Asset management is the backbone of operational excellence for organizations seeking to maximize the value and performance of their resources. A well-structured asset management process goes beyond simply tracking equipment or materials—it encompasses the entire lifecycle of assets, from acquisition and utilization to maintenance and eventual replacement. By adopting proven strategies and leveraging the right processes and technologies, organizations can drive process improvement, achieve continuous improvement, and enhance operational efficiency across their business.
Implementing a robust asset management system enables companies to reduce costs, eliminate waste, and ensure that every asset is contributing to organizational goals. This focus on efficiency and value creation not only supports better cash flow management and cost effectiveness, but also strengthens a company’s competitive advantage in the marketplace. When assets are managed proactively, organizations can deliver higher quality services, respond more quickly to customer needs, and maintain compliance with industry standards.
Ultimately, effective asset management is about more than just managing physical items—it’s about creating a culture of improvement, where every process is optimized for performance and every employee is empowered to contribute to business success. By prioritizing asset management, organizations can streamline operations, improve customer satisfaction, and unlock new opportunities for growth and innovation.
Overview
A global technology services organisation was experiencing growing inefficiencies in how delivery assets were created, stored, and reused across its Professional Services teams. As the organisation scaled, consultants increasingly relied on locally stored or self-created materials rather than shared, approved assets—leading to duplicated effort, quality risks, and inconsistent customer experiences. The organisation faced complex challenges in managing important processes and maintaining accurate inventory of assets, making it difficult to optimize asset utilization and ensure operational excellence.
To address this, a Lean Six Sigma Green Belt project was launched with a clear objective: move from fragmented, individual asset ownership to a controlled, shared asset system that enabled speed, quality, and consistency at scale.
The project focused on designing and piloting a lightweight but robust asset management process that would reduce preparation time, eliminate quality risks, and restore confidence in shared delivery materials.
The Business Challenge
Professional Services consultants regularly deliver complex customer workshops and engagements using a defined set of delivery assets such as slide decks, templates, and supporting materials.
However, the current state revealed several systemic issues:
- Assets were stored across multiple locations with no single source of truth
- A significant proportion of required assets were missing from the central repository
- Many assets were outdated, with some not reviewed for several years
- Consultants frequently rebuilt assets from scratch to avoid quality risks
- There was a non-trivial reputational risk caused by outdated or customer-specific data embedded in reused materials
As a result, consultants were spending a meaningful portion of project time on non-value-adding preparation work, rather than customer delivery. These inefficiencies can also lead to risks in service delivery, potential supply chain disruptions, and negatively impact product quality.
Define Phase: Clarifying the Problem and Objectives
The project team defined a clear problem statement:
Assets required for customer delivery were incomplete, outdated, and inconsistently managed, resulting in avoidable rework, wasted preparation time, and quality risk.
The primary objectives were to:
- Increase asset availability to cover the vast majority of delivery needs
- Ensure assets were current, peer-reviewed, and free of customer-specific data
- Reduce preparation time per engagement
- Establish a repeatable governance model for ongoing asset quality
Achieving these objectives required effective project management and careful implementation of new processes to ensure sustainable improvements and operational excellence.
Critical-to-Quality requirements focused on findability, freshness, correctness, and trust.
Voice of the Customer
Internal users (consultants and engagement managers) articulated consistent needs:
- Assets must be easy to find, ideally within minutes
- Templates must be in the latest approved design
- Assets must contain zero customer-specific data
- Contributors should receive recognition for maintaining shared assets
These requirements reinforced that the solution needed to balance rigour with usability—over-engineering would risk low adoption.
Meeting these requirements is essential for achieving high client satisfaction, as they directly impact service quality, operational excellence, and the overall customer experience.
Measure Phase: Establishing the Baseline
A comprehensive baseline was established across the existing asset library using data analysis and key performance indicators (KPIs) to assess the current state:
- Total assets reviewed: 57
- Assets meeting ageing requirements: fewer than 15%
- Average asset age: over two years
- Defects identified included outdated design, embedded customer data, and missing assets
From a Six Sigma perspective, the process was clearly incapable, highlighting the importance of performance measurement in tracking improvement:
- Defects Per Million Opportunities (DPMO): ~620,000
- Process capability (Cp): effectively zero
The data confirmed that the asset management process was not merely inefficient—it was fundamentally broken.
Analyse Phase: Identifying Root Causes
Quantitative analysis and qualitative workshops revealed three dominant root causes: the absence of a defined asset management process, unclear roles and responsibilities, and insufficient data-driven decision-making. In particular, the lack of standardized practices further contributed to inconsistent approaches and hindered the adoption of best industry standards.
Lack of a defined process
There was no standard mechanism to review, update, or retire assets. Ownership was unclear, and ageing went unchecked.
Low confidence in asset quality
Because quality could not be trusted, consultants routinely bypassed the repository and rebuilt materials, creating duplication and waste.
Fragmented storage and governance
Assets were spread across tools designed for other purposes, with no system-level monitoring or accountability.
Further analysis showed that asset ageing alone accounted for over 80% of observed defects, making it the single highest-leverage improvement opportunity.
Data Accuracy
In today’s data-driven business environment, data accuracy is fundamental to successful asset management and process improvement. Accurate, reliable data underpins every decision related to asset performance, maintenance schedules, and resource allocation. Without high-quality data, organizations risk making costly mistakes—such as unnecessary repairs, missed opportunities for cost savings, or even compliance issues—that can undermine operational efficiency and customer satisfaction.
To achieve operational excellence, organizations must invest in robust data management systems that ensure data is collected, stored, and analyzed with precision. This includes integrating data from multiple sources—such as sensors, maintenance logs, and operational records—to provide a comprehensive view of asset health and performance. Regular data audits, validation routines, and the use of advanced analytics or machine learning can further enhance data accuracy, enabling teams to identify trends, predict failures, and implement targeted process improvements.
Prioritizing data accuracy not only streamlines asset management processes but also supports effective change management and informed decision making. With accurate data, organizations can reduce costs, boost productivity, and deliver improved customer satisfaction by ensuring assets are always performing at their best. Ultimately, a commitment to data accuracy empowers businesses to implement strategies that drive continuous improvement, support business success, and create lasting value for clients and stakeholders alike.
Improve Phase: Designing a Practical, Scalable Solution
Rather than introducing a complex enterprise content management system, the project team deliberately chose a pragmatic solution using existing tooling, redesigned for a new purpose. By leveraging software and embracing digital transformation, the team was able to streamline processes, optimize workflows, and set the foundation for future scalability.
Key elements of the solution included:
- A centralised asset directory acting as the single source of truth
- Mandatory ownership and automated review cycles for each asset
- Peer-review before assets could be marked as “approved”
- Visual management dashboards highlighting ageing and coverage gaps
- Lightweight workflow automation to prompt reviews and celebrate contributions
Technological advancements and innovative solutions were considered throughout the system design to ensure the approach remained adaptable and competitive.
Lean principles such as 5S, visual management, and mistake-proofing were embedded directly into the system design.
A pilot was launched on a subset of high-use assets to validate the approach before scaling.
Pilot Results
The pilot delivered immediate and measurable improvements:
- Defects reduced from 49 out of 57 assets to 1 out of 10 in the pilot group
- DPMO reduced from ~620,000 to ~33,000
- Asset ageing brought under control, with the majority meeting defined freshness criteria
- Consultants reported increased confidence and reduced preparation effort
This progress highlights significant strides toward operational excellence, with clear improvements in asset performance and efficiency.
The pilot demonstrated not only technical improvement, but also behavioural adoption—a critical success factor.
Control Phase: Sustaining the Gains
To ensure the improvements were sustained, the project embedded control mechanisms into normal operations:
- Automated assignment of owners and review dates for every asset
- Regular review cadence built into team routines
- Ongoing visual dashboards tracking ageing, coverage, and quality
- Clear escalation paths for overdue or non-compliant assets
The solution transitioned smoothly into business-as-usual, with minimal additional overhead.
Business Impact
The project delivered value across multiple dimensions:
Time savings
By eliminating rework and asset recreation, consultants recovered hundreds of hours per quarter that could be redirected to customer delivery
Quality and risk reduction
Outdated design and embedded customer data were effectively eliminated from approved assets, significantly reducing reputational risk.
Operational scalability
The organisation now had a repeatable, scalable model for managing delivery assets as it continued to grow.
Cultural impact
Clear ownership, recognition, and transparency encouraged proactive contribution rather than passive consumption.
Key Lessons Learned
Several lessons emerged that are applicable well beyond this organisation:
- Poor asset management creates hidden waste that scales rapidly
- Trust in quality is a prerequisite for reuse
- Simple systems, well governed, outperform complex tools with low adoption
- Early pilots are critical to building momentum and credibility
Conclusion
This Lean Six Sigma Green Belt project transformed a fragmented, high-waste asset landscape into a controlled, scalable system that supports speed, quality, and consistency in customer delivery.
By focusing on process discipline, ownership, and visual management, the organisation achieved dramatic reductions in defects and unlocked significant capacity—without introducing unnecessary complexity.
It stands as a strong example of how Lean Six Sigma can be applied effectively to knowledge work and professional services, not just traditional operations.
