Background

A leading purchaser, installer and distributor of building materials recognized that the absence of a cohesive data strategy was limiting its growth potential and creating issues resulting in lost revenue. Critical data resided on outdated platforms, limited governance and inconsistent data practices hindered quality, and the lack of clear leadership and capabilities in data strategy held the organization back.

To drive transformative growth, the client engaged L.E.K. Consulting to develop a comprehensive data strategy, laying the foundation for an advanced, streamlined technology infrastructure. With this new strategy, the client is now positioned to enhance data quality, leverage insights more effectively, harness the power of artificial intelligence (AI) and fuel sustainable growth, strengthening its market leadership and operational efficiency.

Approach

To establish a strong foundation for the client’s digital transformation, we began by assessing current data capabilities and mapping future data needs to enable goals such as ecommerce, automation and AI. This deep analysis revealed critical technology investments, necessary enhancements to data processes and structures, and adjustments to team organization and the operating model.

After a rigorous cost-benefit analysis and close collaboration with client leadership, our team prioritized high-impact investments that would drive measurable value. For each initiative, we crafted a business case, clearly outlining projected costs, benefits and potential challenges, supported by detailed implementation roadmaps with designated owners, timelines and key steps for success.

To ensure sustainable growth, our team also designed an optimized operating model. This framework specified the future-state roles and team structure, key governance processes, and important considerations for managing complexities over time.  

Results

Through its collaboration with our team of experts, the client gained a comprehensive framework for a data strategy, including a macro-operating model, essential roles and an optimized team structure. Equipped with this strategic clarity, the client implemented targeted initiatives that transformed data into a growth-enabling asset, allowing it to drive business performance and capture new opportunities in the market. Now the client is positioned to capitalize on data-driven insights, accelerate digital growth and maintain a competitive edge in the evolving market.

For more information, please contact us.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2025 L.E.K. Consulting LLC

Indirect spend — often invisible, decentralized and unchallenged — can quietly absorb 10% of a company’s revenue. Yet unlike direct costs, it rarely receives structured oversight. For chief financial officers (CFOs), it represents a largely untapped lever to drive enterprise-wide impact.

While direct materials and labor are usually closely managed, indirect spend is typically scattered across departments, inherited over time and overseen by functional leaders without the time, context or incentive to optimize for value. Here’s what that can look like in practice:

• A mid-market tech company pays three different rates for identical cybersecurity services.
• A global brand uses more than 70 marketing agencies across regional teams with overlapping capabilities.
• A software as a service (SaaS) company renews dozens of tools annually without benchmarking or usage reviews.
• An enterprise human resources (HR) team outsources to three separate recruiting firms — all sourcing from the same candidate pool.

These aren’t outliers — they reflect a broader pattern across companies lacking a coordinated approach to indirect spend. Over time, this blind spot creates ripple effects throughout the business, including:

• Budgets growing unchallenged while savings opportunities go unrealized
• Supplier lists ballooning, creating redundant and overlapping services
• Functional teams spending valuable time managing transactional relationships
• Finance leaders lacking visibility for informed capital allocation decisions
• Contracts auto-renewing with outdated pricing or misaligned terms
• Compliance risks growing as oversight fades

Without clear ownership, supplier relationships stagnate. Functional teams stick with what’s familiar, and tactical purchases gradually accumulate into inefficiencies that slow the business and drain resources. 

Procurement as a strategic lever

To get a handle on fragmented, inefficient spend, more CFOs are adopting indirect procurement — using clear policies, shared visibility and smarter sourcing to drive better results.

Done right, indirect procurement introduces structure and discipline into spending that often goes unmanaged. It helps organizations consolidate suppliers, clarify ownership and establish clear metrics that drive better supplier outcomes.

Organizations that implement structured procurement practices typically see both hard-dollar savings and operational lift. A well-executed transformation can reduce indirect spend by 10%-15% in the first year while freeing up functional teams and improving supplier performance.

Strong procurement practices also unlock:

• Consolidated spend for improved terms and volume leverage
• Full visibility into supplier performance, overlap and spend
• Reduced administrative burden for business teams
• Clearer trade-offs between cost, quality and service
• Better insight into risk and contractual obligations

Just as important, strategic procurement reframes suppliers as potential partners in your transformation — not simply suppliers of goods or services. When selected and managed intentionally, they can bring in specialized expertise, increase speed to value and help internal teams focus on what they do best.

The indirect procurement checklist

For many companies, the need to formalize indirect procurement creeps up gradually until it becomes impossible to ignore. That inflection point often comes around the $250 million revenue mark, when complexity begins to outpace the systems, policies and informal controls that once worked (but it’s worth noting that even companies below this mark can benefit from early structure that prevents inefficiencies from taking root).

At this size, purchasing decisions multiply, often without clear coordination or accountability. What starts as a series of local workarounds can quickly become a structural liability. 

The following questions may help assess your organization’s current indirect procurement capabilities:

• Can you identify your top 20 indirect suppliers by total enterprise spend without running a special report?
• Do you have visibility into auto-renewals across your SaaS and service contracts?
• Has anyone benchmarked your pricing against the market in the past 18 months?
• Is there a clear owner for supplier performance management across key categories?
• Do you have a consistent process for bringing on new suppliers that includes competitive bidding?
• Is supplier spend challenged as a part of your budgeting process across corporate functions?
• Are business units and corporate functions bringing cost-savings ideas to reduce party spend?
• Are there policies and controls in place to manage indirect spend?
• Are there visibility tools and controls in place to manage purchasing card spend?
• Do you have visibility into your supplier risk exposure?

If you answered “no” to one or more of these questions, indirect procurement could be a meaningful lever to drive value in your business.  

The case for center-led procurement

One proven approach is a center-led procurement model. Unlike fully decentralized or rigidly centralized systems, this hybrid model balances local autonomy with enterprise-wide coordination. It allows teams to tailor supplier relationships to their needs while benefiting from shared insights, negotiated terms and aligned goals.

This approach creates a procurement center of excellence that:

• Sets policies and standards
• Negotiates enterprise agreements
• Provides sourcing expertise to business units and corporate functions
• Maintains visibility across all significant spending
• Tracks and reports on savings and value creation 

By treating procurement as a strategic enabler — not just a back-office function — CFOs can realize new efficiencies, reduce risk and unlock competitive advantage through smarter indirect spend.

Transform your indirect spend

L.E.K. Consulting’s Supply Chain and Operations team helps CFOs turn fragmented, inefficient spend into a source of lasting value. In one recent engagement, we partnered with a global manufacturer to build a structured indirect procurement function from the ground up — delivering 15% annual savings across freight, packaging, maintenance and HR services while laying the foundation for long-term efficiency (read more here: Creating Value Through Indirect Procurement in Manufacturing).

Contact us to learn how we can help your organization turn indirect spend into a source of strategic advantage.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2025 L.E.K. Consulting LLC 

L.E.K. Consulting’s latest Brand Heat Index report reveals the footwear and apparel brands gaining traction with consumers across demographics. In a market driven by rapidly shifting trends and preferences, brand strength has become a key differentiator — and a powerful lever for driving business value.

This year’s findings show that consumers are gravitating toward classic, iconic silhouettes that blend comfort with style. While established legacy brands continue to hold some of the top positions, emerging brands are gaining momentum across categories and demographics, challenging the dominance of industry stalwarts.

Explore our infographic to see which brands are rising — and which are cooling off — or download the full Brand Heat Index Special Report for deeper insights. 

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2025 L.E.K. Consulting LLC

Quantum computing — what can it do for biopharma?

Rising clinical thresholds, the growing need for complex drug modalities and extended development timelines are making novel molecular entities (NMEs) increasingly difficult to develop. The annual R&D spend per NME, from discovery to launch, is estimated at $1.5 billion-$3.5 billion, with annual R&D spend across the top 15 pharmaceutical companies (PharmaCos) growing roughly one and a half times since 2010 and projected to reach up to $18 billion by 2030.¹ 

Compounding this challenge, biopharma faces mounting pressure to accelerate innovation due to compressed product life cycles under the Inflation Reduction Act, and more than $200 billion in biopharma revenue is potentially at risk from loss of exclusivity by 2030.  

Could technological advances in artificial intelligence (AI) or quantum computing (QC) help address biopharma’s throughput and spending challenges? AI has seen explosive growth in the past five years, and QC is following suit, as evidenced by increasing publication trends (see Figure 1). QC leverages principles from quantum mechanics to process information exponentially faster than classical computing. The potential for QC and AI to revolutionize the biopharma industry together by offering unprecedented computational power and problem-solving capabilities is enormous.

To date, AI has seen significantly more investment due to its relative maturity, accessibility and market readiness. However, AI’s gain is not QC’s loss. QC and AI are complementary. QC can enable faster training of and inference from AI systems and brings an ability to process data in ways classical computers cannot. Through this it can unlock computational possibilities that are currently unobtainable.

Investment in QC has grown globally. Cumulative investment in the QC market is fueled by both the public and private sectors, totaling around $8 billion in the U.S., approximately $15 billion in China and about $14.3 billion across the U.K., France and Germany through 2024. While private investments in quantum technology have declined from COVID-19 highs due to tightening funding environments and higher interest rates ($2.3 billion worldwide private investment in 2022 versus around $1.3 billion in 2023), quantum intellectual property (IP) development over the past 10 years has increased significantly.

Beyond growth in investment and IP development, the capacity of quantum computers via qubits — the fundamental units of quantum information — has expanded dramatically. IBM progressed from a 5-qubit processor in 2016 to a 433-qubit processor in 2022, with plans to achieve more than 1,000 qubits in 2025. This advancement extends across the industry, with companies such as Google, IonQ and QuEra also demonstrating remarkable improvements in qubit capacity. 

Pioneering QC applications in drug discovery and clinical trials

QC has the potential to revolutionize the biopharma value chain by overcoming classical computing’s limitations in handling complex datasets and simulations (see Figure 2). The most impactful areas are expected to be in drug discovery and research. QC directly addresses the inherent limitations of classical computing in computer-aided drug design because molecules operate by quantum rules — their behavior fundamentally involves dealing with exponentially large-state spaces, which classical systems can only approximate at great computational cost. 

Quantum-enhanced generative models can also explore vast chemical spaces faster than classical techniques can, leading to the discovery of more novel drug candidates previously inaccessible for many years with classical computing, reducing R&D timelines, lowering costs and improving success rates. 

In clinical design and operations, QC can enhance patient stratification and trial optimization by analyzing complex genomic, biomarker and real-world patient data. Quantum machine learning can identify optimal patient subgroups for personalized medicine, reducing trial failures and improving efficacy predictions. Quantum optimization can also refine trial site selection and adaptive trial designs, increasing efficiency and reducing costs.

Beyond R&D, QC can drive efficiencies across other areas of the value chain. QC can help optimize manufacturing and supply chain processes, improve predictive analytics for commercial functions, and increase efficiency of operations to improve sustainability.

While still evolving, QC’s ability to tackle biopharma’s most computationally challenging problems could lead to groundbreaking efficiencies and transformative advancements. 

Emerging interest is driving QC into a pre-utility phase in biopharma

With these high-value QC use cases, it is not a surprise that an L.E.K. Consulting survey of roughly 300 U.S. and EU biopharma stakeholders indicated that over 90% of them are aware of QC and its potential. Additionally, about 50% of respondents, representing 110 unique biopharma companies, stated they understand key concepts and have had exposure to QC or have experience studying its applications (see Figure 3). 

Biopharma participants suggest that QC is making significant early strides, transitioning from academic research to a specialist, pre-utility phase. In this phase, there is a focus on developing practical algorithms and applications to lay groundwork to drive commercial value. Approximately 44% of biopharma stakeholders are in the “early majority,” awaiting evidence before integrating QC, while 30% are innovators or early adopters eager to drive innovation. Investment in QC is set to grow, with 50% of PharmaCos planning annual budgets of $2 million-$10 million and 20% expecting $11 million-$25 million over the next five years. This reflects a growing recognition of QC’s benefits (see Figure 4). 

PharmaCos are experimenting with QC applications across the pharmaceutical value chain, first focusing on drug discovery and clinical trials (see Figure 5).

Expansion of capabilities within sustainability, commercial operations, manufacturing and product development may also be enabled by QC technology. However, the exact impact and best-suited QC modalities for each use case are still being defined.

Recent key advances in QC lead to the need for biopharmas to engage with quantum processing units and enablers

Given the excitement and investment in the space, the landscape of QC is quickly evolving, marked by significant technological advances across the ecosystem. Major milestones from large tech players in 2024 include:

• IBM’s launch of Quantum Heron, its most advanced quantum computer with 156 logical qubits
• Google Quantum AI’s new Willow chip, which enables exponential error reduction and enhanced performance in superconducting quantum systems 

Pure-play QC players have also made substantial strides, including:

• IonQ’s Tempo quantum computer achieving 99.9% 2-qubit gate fidelity, positioning the company as a leader in trapped-ion technology
• Quantinuum’s achievement of 12 logical qubits with its system model H2, a threefold advance over previous models

With these advancements in QC, two key stakeholder groups are emerging: the quantum processing unit providers and the enablers that facilitate access to QC. These stakeholders drive momentum and funding for QC. Like engaging with AI players, biopharma stakeholders should proactively collaborate with these diverse QC ecosystem players to fully harness these technologies and stay competitive in this evolving field (see Figure 6). 

Strategic partnerships needed to compete within a specialized market

Due to the growing complexity of the QC ecosystem, successful integration of workflows depends on building capabilities through strategic partnerships. Notable collaborations include:

• IBM Quantum with GSK, Moderna and AstraZeneca: Optimizing messenger RNA research and clinical data imputation using IBM’s Quantum Heron and Condor processors
• Google Quantum with Boehringer Ingelheim: Exploring molecular simulation algorithms to aid in drug discovery with Google’s Sycamore processor

Partnerships underscore the industry’s commitment to integrating QC into pharmaceutical workflows, highlighting the collaborative efforts needed to overcome technical challenges and achieve utility (see Figure 7). Building in-house expertise and fostering external partnerships will be crucial to leverage necessary talent quickly. Companies that act swiftly will gain a competitive advantage, positioning themselves as leaders in this emerging field. 

Strategic partnerships needed to compete within a specialized market

Due to the growing complexity of the QC ecosystem, successful integration of workflows depends on building capabilities through strategic partnerships. Notable collaborations include:

• IBM Quantum with GSK, Moderna and AstraZeneca: Optimizing messenger RNA research and clinical data imputation using IBM’s Quantum Heron and Condor processors
• Google Quantum with Boehringer Ingelheim: Exploring molecular simulation algorithms to aid in drug discovery with Google’s Sycamore processor

Partnerships underscore the industry’s commitment to integrating QC into pharmaceutical workflows, highlighting the collaborative efforts needed to overcome technical challenges and achieve utility (see Figure 7). Building in-house expertise and fostering external partnerships will be crucial to leverage necessary talent quickly. Companies that act swiftly will gain a competitive advantage, positioning themselves as leaders in this emerging field. 

The near-term impact: Intersection of QC, AI and classical computing

The most promising near-term advancement is combining QC with AI and classical computing in hybrid workflows. This combination leverages the strengths of all technologies, enabling more accurate simulations of complex systems, enhanced machine learning models and improved process optimization for larger datasets at significantly faster speeds. More than 70% of biopharma stakeholders anticipate that QC will augment classical computing and AI, offering more precise and efficient solutions, especially in navigating breakthroughs in drug discovery and development.

For example, Qubit Pharmaceuticals leverages QC for advanced target characterization and molecular dynamics within small-molecule drug discovery while simultaneously utilizing AI-driven generative modeling, virtual screening and predictive analytics. Additionally, Qubit has partnered with Pasqal to leverage both classical computing and QC to model proteins, NMEs and water molecules at high levels of accuracy. 

Further, IonQ’s collaboration with AstraZeneca includes the creation of an applications development center within AstraZeneca’s BioVentureHub to advance QC for drug discovery and development. In addition, IonQ has collaborated with NVIDIA, AstraZeneca and AWS to advance drug development using computational tools — achieving 20x speedups in molecular simulations versus AWS’ previous implementation — and paving the way for quantum-accelerated biopharma and materials science.

Further advancements, including running AI on quantum computers, are exciting but not expected to be seen for longer periods of time.

The path forward for QC in biopharma

The integration of QC into the pharmaceutical industry holds immense potential to revolutionize drug discovery and clinical trials. While QC represents a longer-term (five-to-10-year) strategic investment requiring scalable hardware, advanced error mitigation and correction, and specialized algorithms, the opportunities it presents are significant. QC can enhance predictive analytics, optimize clinical trial designs and expedite the discovery of novel therapies, ultimately accelerating drug development and reducing time to market for new treatments.

Despite current challenges such as talent acquisition and a steep learning curve, strategic investments, partnerships and AI integration can enable the industry to harness QC’s transformative power. Continued collaboration and innovation will be crucial.

Biopharma stakeholders should address the following key questions to effectively utilize QC’s benefits and remain competitive:

• Does my organization have a clear plan on how to experiment with and deploy QC within key functions, especially R&D?
• Within R&D, are there specific use cases that would be most appropriate for QC? On what basis should these be identified?
• How do I balance external partnerships and collaborations alongside internal capabilities to accelerate realization of the potential from QC in R&D?
• To implement QC effectively, what key internal operating model requirements must be met, specifically regarding talent, hardware, data infrastructure and software?
• To what extent should QC be leveraged alongside AI? Is there a benefit from integrating early (e.g., hybrid workflows) or operating independently prior to integration? What is the optimum roadmap for my organization?

By considering these questions and investing strategically in QC, the pharmaceutical industry can harness new opportunities and achieve remarkable progress across drug discovery, clinical development and operation, the supply chain, and manufacturing.

Note: L.E.K. conducted a number of interviews with both AI and pharma experts including Google, IONQ, Qubit and others to help triangulate and inform the findings.

For more information, please contact us.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2025 L.E.K. Consulting LLC

Endnote
¹L.E.K. analysis of Evaluate Pharma. 

Background and challenges

A global medical device manufacturer had experienced a significant “pull forward” of capital product sales during the COVID-19 pandemic that resulted in stunted demand and revenue in the following years. COVID-19-related commodity dynamics impacted cost, further compressing margins.

Management engaged L.E.K. Consulting to perform a thorough assessment of the company’s strategic and operational options to return to profitable growth in the near term. We completed a cost optimization assessment, with a focus on manufacturing, procurement and working capital.

Approach

The L.E.K. team employed its operations and supply chain expertise to identify opportunities, model value and develop a roadmap to improve profitability. Three opportunities were identified and developed with the management team: manufacturing strategy, indirect procurement and working capital.

Manufacturing strategy

The company’s manufacturing strategy was inflexible, with long lead times, high costs and significant geopolitical risk. The company still relied on an outsourcing model primarily based in China. Competitors had successfully transitioned to Mexico and the US over the last ten years. Competitors also had more operational flexibility, with a mix of owned manufacturing and electronic contract manufacturing (ECM) partners.  

First-administration Trump-era tariffs had broadly been passed along to customers in the market, but competitors who had nearshored or re-shored were enjoying margin uplift.

A new operations leadership team wanted to undertake a nearshoring transformation but had not yet developed the strategy or quantified the margin uplift. The L.E.K. team completed a rapid manufacturing footprint optimization study, including:

• Market research into peer and analog manufacturing strategies
• A business case to model financial benefits and one-time costs
• A sensitivity analysis of forecasted demand and impact on the business case
• Global ECM market research to identify potential partners, with a focus on Mexico and Southeast Asia
• Opportunities to leverage ECM capabilities, simplify manufacturing processes and reduce costs were identified and developed

Indirect procurement

The company had an established corporate supply chain team that managed its direct and logistics spend but had not centralized its indirect procurement. The indirect procurement team had less than a third of indirect spend under management and did not have spend visibility or a productivity pipeline.

The L.E.K. team deployed L.E.K.’s Rapid Sourcing Diagnostic solution to develop a perspective on spend, savings opportunities and strategic sourcing levers.  

• A spend cube was developed to categorize spend, evaluate category complexity and develop supply chain opportunities  
• A contract review was completed to evaluate commercial terms and identify constraints  
• Business stakeholders were interviewed to understand how categories and suppliers had historically been managed  
• Category savings estimates and sourcing levers were developed through L.E.K. team-led workshops and value analytics  

Working capital

In addition to cost pressure, the company lagged peers in its cash conversion cycle (CCC), which was driven by differentiated peer revenue models and a lack of focus on working capital management with suppliers and customers.

Our team deployed L.E.K.’s Rapid Working Capital Assessment to benchmark the company to its peers and develop a set of opportunities to improve its cash position:

• Payables, inventory and receivables were benchmarked to peers and analogs
• The company achieving median and top quartile performance were modeled for cash and P&L impact  
• Current collections and payables processes were evaluated to identify operational changes that could improve working capital performance  
• Market research was conducted to identify peer and analog standard terms, revenue models and business process improvements
• A set of opportunities to improve working capital position was developed  

Results

Working closely with the client leadership team, the L.E.K. team developed an integrated operations performance improvement program that included both rapid, near-term opportunities and strategic projects to be executed over a five-year horizon:  

• $60 million in annual cost savings, tripling earnings before interest, taxes, depreciation and amortization
• 40% of savings generated through indirect procurement on a one-year horizon
• 30% increase in cash through working capital unlocks

For more information, please contact us.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2025 L.E.K. Consulting LLC

Background and challenges

A nutraceutical company was considering a strategic investment to expand into new product categories. The new product categories appealed to a younger demographic and would expand its direct-to-consumer (DTC) business, both critical strategies for the business.

L.E.K. Consulting was engaged in an operational due diligence (ODD) to develop a perspective on synergies and risk across the end-to-end supply chain. The three-week due diligence included a risk assessment, estimated synergy cost savings and a time-phased implementation plan. In parallel, we executed a commercial due diligence (CDD) to evaluate the competitive landscape and risks the company faced with a planned expansion from DTC to retail.

Approach

L.E.K. deployed its Synergy Assessment and Operational Health Check solutions to rapidly evaluate the company’s and the target’s supply chain and manufacturing capabilities.

Six synergies were developed that would generate 810 basis points of gross margin improvement for the target, as well as 30 basis points for the company:

1. Consolidate the target’s manufacturing to the company’s high-performance contract manufacturers to reduce conversion costs  
2. Insource a set of product lines to the company’s internal manufacturing platform to take advantage of a differentiated cost structure  
3. Leverage packaging economies of scale with the company’s existing supply base and transition to new packaging design to reduce cost and working capital
4. Capitalize on combined parcel spend and new cost optimization strategies  
5. Insource the target’s DTC distribution to leverage the company’s capabilities and capacity  
6. Change supplier ordering processes to maximize inbound truckload utilization

A phased implementation plan was developed to accelerate speed to value while balancing business and broader integration priorities.  

The Operational Health Check focused on the target’s contract manufacturers, supply chain practices and key raw materials markets. No red flags were identified within the target’s operations. There were challenges with the primary ingredient used in most of the portfolio. The commodity market for this ingredient was experiencing high demand and global shortages that led to volatility in pricing and availability.  

In parallel, the CDD found significant pricing headwinds with major retailers due to changing consumer expectations. The target had little pricing power relative to its peers and a volatile commodity input, neither of which were accounted for in the business case.  

Results

Our team’s Synergy Assessment found a multimillion-dollar margin uplift opportunity for the target, which was nearly twice the initial company estimate. The analysis also found freight synergies for the acquiring company that had not previously been considered.  

The integration of the CDD and ODD was critical to the decision-making process for management. The combination of customer pricing pressure, direct materials volatility and the company’s position in the market led to an acquisition target that was much riskier than it initially appeared.  This critical insight led to further due diligence by the company and ultimately the choice not to move forward with the acquisition, potentially saving the client millions of dollars from a poor investment.

For more information, please contact us.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2025 L.E.K. Consulting LLC 

For many providers of residential services such as roofing, restoration, HVAC, landscaping and more, geographic growth is a key component of their expansion theses. But while many such businesses target the obvious markets — namely, larger metros with above-average income and/or population growth — a more precise approach is needed to unearth the less obvious, and potentially more lucrative, opportunities for both M&A and greenfield expansion. For example, L.E.K. Consulting recently worked with a client that found its business performed best in markets with lower home values but higher income and used that information as the basis for its expansion strategy.

To start, residential services providers that are looking to expand their platforms need to develop an index of what drives demand for their services. Dozens or even hundreds of variables can be evaluated using data science techniques to assess the market potential for building services in regions across the U.S. and serve as catalysts for more-targeted growth and sales efforts. 

Targeting local opportunities is critical, as variations in financial capacity, service demand and operational attractiveness are what propel increased residential remove- and-replace spending in specific areas. Granular analysis, meanwhile, can highlight both in-fill opportunities in existing markets and attractive subregions in potential expansion markets.

Core elements of a geographic targeting index

Every provider of residential services needs to develop its own index of the variables that it deems most important to the business. And while every residential services business is different, all their variables will fall into one of three essential categories, which can be identified by answering one or more related questions:

1. Demand — What are the key drivers of demand for the specific residential service: home age, home sales, weather and/or other local factors?
2. Financial capacity — To what extent does the geography feature homeowners with the growing means to pay for residential services?
3. Operations — To what extent does the geography allow a residential services business to act on demand drivers and serve homeowners with the ability to pay? How dense (i.e., within easy access) are the properties that would be served? What level of competition and execution barriers does the geography have?

A composite of prior approaches used by residential services providers surfaces some common variables (see Figure 1). 

Applying these variables to assess metropolitan statistical areas across the U.S. makes clear that attractive growth geographies exist in multiple markets (see Figure 2). 

A review of specific geographies reveals opportunities within metros, all the way down to the ZIP code level (see Figure 3). 

The map surfaces some important findings and actionable insights. To start, there are 132 geographies that are 75-plus on the 1-100 attractiveness rating scale, representing an estimated 79 million people — roughly 24% of the total U.S. population. Unsurprisingly, the most attractive geographies are in the South: The South Census Region accounts for 38% of these geographies and contains 41% of the overall population living in attractive geographies (see Figure 4). 

That said, even within regions one will find a wide variety of geographies, both attractive and unattractive. For example, while the South Census Region contains the most attractive geographies, the East South Central Division contains just 4% of the population living in those attractive geographies (see Figure 5). 

Similarly, when analyzing attractiveness at the state level, pockets of opportunity can be found across regions.

Notably, population does not equal attractiveness. Some states have a comparatively lower population but a high level of attractiveness, whereas some higher-population states have a low level of attractiveness. Roughly 2 million people live in attractive geographies in Alabama, for example, which is a comparatively lower-population state given its population of about 5 million people (see Figure 6). 

And attractive geographies are not all urban. While urban geographies tend to skew toward higher attractiveness, opportunity still exists in more-rural regions. For example, some 40 million people live in rural geographies that score 50-plus on the attractiveness rating scale (see Figure 7).

How to create a geographic targeting index

While the above analysis is based on a set of variables that are relevant to most residential services businesses, each business will want to develop its own index.

For example, a services provider might find that an effective predictor of a successful geography for its business is the percentage of the population that’s enrolled in K-12 versus the U.S. average. The provider can then compare that metric against the geographic attractiveness index (see Figure 8). 

Once again, the analysis shows that while wealthy geographies score higher, but there is still promise in lower-income areas. (see Figure 9).

In another example, a services provider might be most interested in an older and more financially stable population, which aligns best with the provider’s current go-to-market approach. Population growth in the 55-plus bracket highlights clear pockets of opportunity, most acutely in the South (see Figure 10). 

A geographic targeting index in action

We worked with a residential and commercial services company that provides a building repair service and had used geographic analysis to target rural markets, specifically those close to distribution centers that would give it faster access to its installation product.

As we quickly identified, the company’s then-current footprint captured only 19% of demand; there was significant white space left over.

In order to evaluate areas into which the client could expand its services, we performed a robust regression analysis to identify new markets with attributes similar to those of its highest-performing existing markets. In doing so, we discovered that our client performed best in high-income markets with lower median housing values, low vacancy rates and a high concentration of suburban families with young children. We subsequently determined which of these attractive markets were within a reasonable drive time from the company’s regional headquarters and its suppliers’ distribution centers.

With our help, our client was able to prioritize a near-term pipeline of 10-15 new markets that would give it access to an additional $1.2 billion to $1.4 billion in market demand. We also built out a longer-term pipeline of markets that added an incremental $3.5 billion to $4 billion in market access for the company.

As a result of our work, our client has already started entering these new markets with a lot of success, and is considering opening new regional headquarters to help facilitate its entry into markets in other parts of the country.

The world is only getting more competitive, and the residential services space is no exception. That’s why, for providers of residential services, geo-targeting is a necessary component of growth. Getting smarter on data can help companies find the right target in a market that may otherwise not be appreciated.

For more information, please contact us.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2025 L.E.K. Consulting LLC