Incremental Profit From New Sales

Evidence and data. By implementing clean, enriched data from Dun & Bradstreet, the interviewees’ organization unlocked significant financial gains through strategic solution selling and intentional cross-sell initiatives. Interviewees noted that this transformation led to measurable improvements in profit margins and generated millions in additional revenue by enabling collaborative, data-driven sales across business units. By enabling clean data segmentation and hierarchy mapping for the CRM rollout, Dun & Bradstreet’s data management solutions played a key role in contributing to a 2% uplift in revenue from selling initiatives.

• Revenue lift from improved data visibility. The interviewees’ organization experienced additional revenue attributed to improved cross-sell visibility and strategic selling. Interviewees said clean data enabled teams to identify cross-sell opportunities that were previously hidden due to fragmented systems and duplicative records. The head of analytics strategy said, “By adopting a more collaborative, solution-selling approach, we generated an additional $300 million in business within the first two years.”

• More intentional solution selling. Prior to implementation, cross-selling at the interviewees’ organization was often unintentional and siloed. Post-implementation, teams collaborated across business units to present unified solutions, increasing deal size and margin. The VP of solution operations explained: “We didn’t even know we were cross-selling until we saw the data. Now we’re doing it intentionally and collaboratively.”

• Higher profit margins. The head of analytics strategy described a significant uplift in profit margins due to solution selling enabled by clean, enriched data: “When we delivered a full solution selling initiative, we saw 10% higher margins on many of our deals. ... The profit margin applies to roughly half of solution-selling initiatives. It doesn’t work in every scenario, but there is a definite uplift now that we have visibility into our market.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the organization:

• The organization’s annual revenue is $1.5 billion.

• Benefits begin to accrue during Year 1 due to the organization’s early access to cleansed data even before full CRM consolidation; the organization realizes 30% of the benefit in Year 1. The organization experiences 100% of that benefit in Years 2 and 3.

• Dun & Bradstreet’s data management solutions enable clean data segmentation and hierarchy mapping for the CRM rollout and contribute directly to the 2% uplift in revenue from cross-selling and solution selling initiatives.

• The organization’s net profit margin is 12.5%, and it realizes a 10% uplift in net profit margin on 50% of its solution-selling initiatives due to improved customer insights and collaboration.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• The sales team’s maturity and ability to implement structured solution selling and cross-sell programs.

• The organization’s data readiness and hygiene.

• The complexity of CRM integration and system fragmentation.

• The organization’s change management effectiveness and sales team adoption of data tools.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $5.9 million.

Supplier Management And Spend Optimization

Evidence and data. The interviewees highlighted how normalized supplier data improved visibility, reduced risk, and enabled smarter procurement decisions that led to measurable cost avoidance and operational efficiency.

• Supplier visibility and fraud risk mitigation. The interviewees’ organization benefited from enriched supplier profiles and access to current business information, which supported more informed procurement decisions. Their teams used Dun & Bradstreet’s portal to accelerate supplier analysis and validate payment details, reducing exposure to fraud and enabling faster collections. The head of analytics strategy noted: “We gave the procurement team licenses into the Dun & Bradstreet portal so they could validate whether a supplier’s invoice was valid and identify fraudulent invoices. We probably have saved millions by reducing fraud. Also, Dun & Bradstreet flagged suppliers that are likely to go out of business within 12 months. That helped us collect faster and avoid losses.”

• Price and contract optimization. Interviewees noted that normalized and enriched supplier data enabled procurement teams to better understand who their suppliers were and where they operate, helping them identify duplicates, consolidate contracts, and negotiate more effectively. These improvements led to an estimated $2.1 million in annual avoided supplier spend, driven by a 0.25% optimization in procurement spend. The VP of solution operations said, “Just understanding who our common suppliers are and normalizing that data helped us save millions.”

• Savings from operational efficiency. According to interviewees, implementation of Dun & Bradstreet data streamlined supplier data management. Manual data scrubbing, previously requiring three full-time employees, was automated, freeing up those resources for more strategic roles. The head of analytics strategy explained: “We had three people working full-time just to scrub supplier data. Now that’s automated.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the organization:

• The company spends approximately $853.1 million annually on suppliers (cost of goods sold).

• Benefits begin to accrue during Year 1 due to the organization’s early access to cleansed data even before full CRM consolidation; the organization realizes 30% of the annual benefit in Year 1. The organization experiences 100% of that benefit in Years 2 and 3.

• With improved supplier data visibility, the organization avoids paying fraudulent invoices totaling 0.25% of its suppliers’ spending.

• The organization optimizes 0.15% of supplier spend through better contract negotiations.

• Sixty-five procurement and credit analyst FTEs see their work simplified by better data visibility, leading to labor cost savings of 5% which equals a total of three procurement and credit analyst FTEs reallocated due to automation and improved data quality.

• The average fully burdened annual salary for these roles is $75,000.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• The availability of supplier data and ability to normalize and detect fraud.

• The maturity of the organization’s procurement process and analytics capabilities.

• Current spending volume and supplier engagement scale.

• The organization’s internal capacity and automation readiness for analyst reallocation.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $5.7 million.

CRM Consolidation Savings

Evidence and data. The interviewees’ organization employed Dun & Bradstreet to unify customer and supplier data and deliver cleansed records into its enterprise data platform, giving teams early access to high-quality information and a clearer understanding of their active and prospective customers. This integration of disparate data sources into a consistent, enriched foundation enabled the interviewees’ organization to simplify its technology stack and sunset redundant systems. With a unified view of customer and supplier entities, the interviewees’ organization successfully migrated to a single CRM environment, enhancing visibility and supporting more efficient operations across teams.

• CRM consolidation. The head of analytics strategy explained how clean customer data was a prerequisite to successfully consolidate their organization’s five separate CRM systems into a single CRM instance: “Clean data was the foundation. Without it, CRM consolidation would have been much harder.” The VP of solution operations added: “We were operating at least five different CRMs. Now we’re down to one.”

• Cost savings. Interviewees said that decommissioning 80% of legacy CRM systems and instances across their organization resulted in significant cost savings related to software licensing, support, and maintenance. The head of analytics strategy noted, “We’re turning off legacy CRMs and saving hundreds of thousands per system.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the organization:

• The organization operates five CRM systems prior to the data management solutions implementation.

• Following data cleansing and consolidation, 80% of these systems are decommissioned, resulting in four systems being retired.

• The average attributable annual cost of a decommissioned CRM system is $500,000.

• Seventy-five percent of these savings are realized in Year 2 of the deployment while all of these costs are phased out by Year 3.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• The number of existing legacy systems and CRM decommissioning potential.

• The organization’s licensing and contract terms for CRM platforms.

• The availability of IT resources for CRM integration and architecture.

• The organization’s data migration complexity and standardization readiness.

Results. To account for these risks, Forrester adjusted this benefit downward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.6 million.

Sales Efficiency Improvement

Evidence and data. Interviewees reported that trusted, unified customer data streamlined sales planning, reduced territory disputes, and empowered more strategic engagement across their organization’s business units.

• Time savings and productivity gains. At the interviewees’ organization, improved data quality and visibility led to measurable time savings for 200 sales representatives, each saving an estimated 30 minutes daily. The VP of solution operations said, “Trusted data has reduced internal disputes and enabled more strategic engagement.” The executive noted that 95% of that time is now reinvested in selling activities, adding: “That time is now spent selling. It’s not just saved — it’s reinvested.”

• Strategic engagement and collaboration. Interviewees said that clean, trusted data transformed how teams operate, reducing internal disputes, enhancing cross-team collaboration, and enabling more strategic engagement. The head of analytics strategy shared, “It has totally changed our dynamic, totally changed our thought process on how we do business.” This shift also supported more collaborative, insight-driven solution selling as per the VP of solution operations: “The solution selling is a collaborative endeavor; they all have their own business unit responsibilities but now they share insights across teams.”

• Improved business reviews and decision-making. Enhanced data quality elevated the value of strategic business reviews (SBRs) at the interviewees’ organization, enabling more confident, data-driven decisions. The head of analytics strategy noted: “Those strategic business reviews have become infinitely more valuable. We go in knowing who our unique entities are and where cross-selling already exists.”

• Territory alignment and customer engagement. According to interviewees, unified customer views noticeably reduced territory disputes and improved team alignment. The head of analytics strategy explained, “Ownership is moving away from individual sales reps to a more collective view, which helped us gain better traction with customers and created more stickiness.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the organization:

• The organization has 200 sales representatives.

• Prior to implementation, each representative spent an average of 60 minutes per day on data analysis and territory planning tasks.

• Post-implementation, this time was reduced to 30 minutes per representative. With the implementation of clean, enriched data, sales teams reduced time spent on data analysis and territory planning tasks by 50%.

• The average fully burdened annual salary for a sales representative is $125,000.

• Ninety-five percent of the time saved is recaptured as productive selling time.

• Benefits begin to accrue in Year 1 with 30% of the total benefit realized during implementation due to early access to enriched data. The organization realizes 100% of the total benefit in Years 2 and 3.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• The organization’s sales team size and aggregate productivity potential

• The organization’s territory complexity and suitability for planning automation

• The organization’s tool adoption and data-driven workflow uptake

• The organization’s baseline inefficiencies and enablement platform maturity

Results. To account for these risks, Forrester adjusted this benefit downward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.4 million.

Data Management Efficiencies

Evidence and data. Interviewees said that automation and data cleansing drastically reduced data duplication, manual effort, and maintenance costs, freeing up data management resources for higher-value activities at their organization.

• Automation and resource reallocation. Prior to implementation, the interviewees’ organization relied heavily on manual data cleansing with eight full-time data analysts dedicated to maintaining customer records. The head of analytics strategy pointed out: “We had eight analysts manually cleansing data. Now, only one is needed.” After deploying automated data refreshes and cleansing processes, the interviewees’ organization reallocated seven of these analysts to more strategic roles.

• Data cleanup and entity reduction. The interviewees’ organization reduced its unique data records from 500,000 to 130,000 active entities, eliminating over 50% of duplicative and fragmented records — many of which represented partial or inconsistent versions of the same entity. The head of analytics strategy elaborated: “We found out we only do business with about 130,000 active entities. That’s a huge cleanup.” Weekly automated refreshes now maintain over 90% of active revenue records, significantly reducing manual effort. The VP of solution operations shared: “It just refreshes. No manual effort. That’s a game changer.”

• Accelerated decision-making. Interviewees noted that the shift from manual cleansing to automated data management freed up resources and accelerated decision-making. The head of analytics strategy elaborated: “We took 1,500 months’ worth of work and did it in 18. That’s the power of automation.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the organization:

• The organization employed eight data analysts for manual customer data cleansing prior to implementation.

• Post-implementation, seven of these analysts, or 87.5%, were reallocated due to automation.

• The average fully burdened annual salary for a data analyst is $73,700.

• Benefits begin to accrue in Year 1, with 30% of the total benefit realized during implementation due to early access to enriched data. The organization realizes 100% of the total benefit in Years 2 and 3.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• The extent of data duplication and need for cleansing automation.

• The organization’s automation capability and integration infrastructure.

• The willingness to embrace automation and any existing governance constraints.

Results. To account for these risks, Forrester adjusted this benefit downward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $907,000.

Unquantified Benefits

The interviewee mentioned the following additional benefits that the organization experienced but was not able to quantify:

• Strategic decision-making and customer prioritization. Executives at the interviewees’ organization gained a clearer view of customer value after discovering that half of the company’s revenue came from just 4,500 entities. This insight, enabled by Dun & Bradstreet’s data enrichment and entity resolution, fundamentally changed how leadership approached account strategy. The interviewees noted that instead of treating all customers equally, their organization began prioritizing high-value accounts, aligning executive engagement across layers, and tailoring go-to-market efforts based on actual revenue impact. The head of analytics strategy said, “Learning that half our revenue comes from just 4,500 customers reshaped how we go to market, enabling leadership to focus on the right accounts and allocate resources more strategically.”

• Cross-functional collaboration. Previously, departments like sales, marketing, procurement, and credit at the interviewees’ organization operated in silos, each relying on different data sources. This led to misalignment, inefficiencies, and internal account or territory disputes. Interviewees said Dun & Bradstreet’s data management solutions provided advanced identity resolution and data enrichment capabilities that linked internal records with external attributes such as buyer intent, demographics, and ownership. This deeper understanding of customer entities supported more targeted engagement and strategic account planning across the organization’s teams and departments. The VP of solution operations confirmed: “Sales, marketing, procurement, and credit all had to be aligned. That took time but it was worth it.”

• Accelerated AI adoption and analytics maturity. Before implementing Dun & Bradstreet’s data management solutions, fragmented and inconsistent data limited the interviewees’ organization’s ability to scale analytics and AI. With clean, structured data flowing into its enterprise data platform and CRM, teams were able to build smarter models, automate insights, and unlock use cases that were previously out of reach. This transformation accelerated AI adoption by two to three years, allowing the company to leap ahead in its analytics maturity and strategic planning capabilities. The head of analytics strategy noted, “Clean data is the essence that AI needs to be valuable, and we’ve accelerated our ability to bring AI into our company by probably years.”

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Dun & Bradstreet’s data management solutions and later realize additional uses and business opportunities, including:

• Lead generation transformation. To move beyond fragmented sales efforts, the interviewees’ company leveraged Dun & Bradstreet’s enriched data to unify its go-to-market approach. This shift marked a transition from siloed solution selling where individual business units operated independently, to a coordinated strategy that prioritized high-value accounts across the enterprise. Interviewees noted that with improved visibility into customer relationships spanning multiple business units, marketing teams could align campaigns more effectively with sales priorities. This unified view not only enhanced cross-selling and upselling opportunities at the interviewees’ organization but also informed acquisition strategy by identifying markets and customer segments with the greatest growth potential. The VP of solution operations explained: “It gave us visibility into the market where we had the opportunity to inform our acquisition strategy. It certainly informed how we were going to go to market.”

• Enhanced digital engagement and website visitor resolution. The interviewees noted their organization is currently enhancing its digital engagement strategy by integrating additional Dun & Bradstreet tools like D&B Rev.Up, D&B Hoovers, and website visitor resolution to identify anonymous website visitors and match them to known entities. This capability connected digital signals to real business opportunities and enabled marketing and sales teams to target prospects based on intent, uncovered whitespace, and personalized their outreach. These tools also unlocked visibility into “gray space” (underpenetrated existing accounts) and “white space” (new prospects resembling top customers), supporting more precise targeting and lead generation for the interviewees’ organization. The VP of solution operations noted, “Even if visitors don’t fill out a form, we can unmask who they are and pursue opportunities based on their intent to purchase.”

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).