Nine Data Hygiene Issues Holding Back Sales Operations Teams

Data hygiene—the ongoing process of ensuring that data is accurate, consistent, complete, and up to date—is a key part of data management and analytics, helping organizations make reliable decisions, avoid errors, and improve operational efficiency.

Sales operations (sales ops) team members often face several data hygiene challenges throughout the quote-to-cash (QTC) lifecycle. Let’s take a look at some of the most common ones.

1. Incomplete or inaccurate data entry

Incomplete or inaccurate data is an instant deal blocker. While 98% of sales leaders recognize the importance of complete and accurate data, only 35% of sales professionals completely trust the accuracy of their organization's data." Information is incomplete if it’s missing a key detail, such as a customer’s address, legal entity name, or contact information. Inaccurate data includes typos or incorrect information, like misspelled names or wrong email addresses, or inconsistent formatting—such as dates that appear as MM/DD/YYYY in one record and MM-DD-YY in another. Or, information could be inaccurate because it’s outdated, like old customer data or product data. 

If the underlying data used to generate sales contracts (e.g., customer details, pricing agreements, or product configurations) is inaccurate or incomplete, the contracts will reflect these errors, potentially leading to disputes or revenue leakage.

Preventing delays between order and activation is crucial, and requires gathering the necessary data for provisioning entitlements at the correct point in the quote lifecycle. Electronically capturing all key data elements during the contracting phase is essential for smooth order booking and entitlement activation downstream.

2. Duplicate records

Duplicate records—multiple entries for a customer or account—can undermine the accuracy and reliability of data. When the same individual or entity appears more than once in a system, confusion, inefficiencies, and costly errors can result, especially during contract generation processes. These inconsistencies not only waste time but also increase the risk of legal and operational issues. Maintaining clean, deduplicated records is essential to good data hygiene and can help organizations operate smoothly and professionally.

3. Inconsistent data formatting

Inconsistent data formatting is a common, seemingly minor, yet often overlooked issue that can significantly impact data quality and usability. Variations in how information is entered—such as dates appearing as MM/DD/YYYY in one record and MM-DD-YY in another, or phone numbers formatted as (XXX) XXX-XXXX versus +1 XXX-XXX-XXXX—can create confusion and complicate data processing. Inconsistencies in addresses or the lack of standardized naming conventions further contribute to errors and inefficiencies, which in turn slow down otherwise high-performing teams.  

4. Lack of validation rules

A lack of validation rules can lead to the entry and storage of incorrect or incomplete data, compromising the integrity of entire systems. Without proper checks in place, sellers may input flawed information, such as missing fields, invalid formats, or inconsistent contract terms, which can result in downstream errors and compliance risks. For example, the absence of logic to ensure that contract terms align with company policies can lead to agreements that are legally or financially problematic. Eventually, these errors will have to be faced and addressed, eating into valuable time resources that could be deployed elsewhere. 

5. Manual data entry

Sales representatives spend a considerable amount of time on non-selling tasks, with reps dedicating 70% of their time to such activities, a figure largely unchanged from previous years. A significant portion of this involves manually entering customer and sales information. 

This reliance on manual data entry—like copy-pasting from one system into another—is prone to human error, which can directly affect sales contracts by introducing formatting issues and/or inaccuracies into pricing, customer details, or service entitlements. Such errors can lead to billing errors or timing discrepancies, which are significant causes of revenue leakage.

Additionally, the quoting process lacks high-quality, repeatable workflows. This makes it nearly impossible for sales teams to understand and appropriately apply thousands of pricing options, discounts, and special term language to a booming range of offerings as organizations grow. Though CPQ tools can help with tasks like quoting and billing, they often lack robust integration with subsequent phases such as contracting, thereby increasing discrepancies between documents and introducing pricing mistakes.

6. Integration issues

It’s far easier and much faster for multiple parties to work together on an agreement if everyone has access to the same version of the document, across platforms. No more disparate local files stored in emails or saved on desktops. When every individual party can access a single live file, accessible via a secure central repository and synced properly between Salesforce, for example, and other systems (like ERP, CPQ, and Docusign), the process moves far more efficiently. This frees up legal and similar teams to focus on the actual deal from a commercial perspective, rather than spending their time trying to determine the most current version of a document.

A detailed history of changes helps every party understand the progress of the document in case of an audit or another incident further down the road. If something changes in the contract, an Intelligent Agreement Management tool can do the write-back to update Salesforce or other systems to reflect the final agreement. 

7. Data silos and fragmentation

Data silos are prevalent in over half (51%) of TMT (technology, media, and telecommunications) organizations, preventing a unified view of customers. This lack of integration among sales, marketing, and service functions inhibits coordination and transparency. When customer data is fragmented across multiple unconnected systems, it becomes challenging to ensure that sales contracts are based on complete and consistent information. 

This fragmentation disrupts operational harmony, creates redundancies in customer relationship management, and can lead to missed cross-sell and upsell opportunities that would typically be identified with integrated customer data.

8. Poor visibility into data quality

Poor visibility into data quality can severely hinder an organization’s ability to maintain clean, reliable information. Without effective reporting tools or dashboards to monitor data hygiene, issues like duplicates, formatting errors, or missing information can go unnoticed for extended periods. Additionally, the absence of alerts or notifications means that teams are often unaware of problems until they’ve already caused disruptions. Establishing clear visibility into data quality through regular reporting and real-time monitoring is essential for proactively identifying and resolving issues, ultimately supporting better decision-making and operational efficiency.

9. User training and adoption

User training and adoption play a critical role in maintaining strong data hygiene, yet they’re often overlooked. Sales reps and other team members might not be fully trained on proper data entry practices or may not understand the importance of clean, accurate data. This can lead to inconsistent entries, skipped required fields, or resistance to following standardized processes—all of which degrade data quality over time. Or, sellers might be overtrained and fatigued from being asked to do too much.

Addressing these challenges

Docusign offers leaders the solutions they need when it comes to addressing the challenges of maintaining excellent data hygiene. With Docusign, teams can supercharge sales efficiency by streamlining in-CRM contract creation, merging data from contracts back to the CRM, and more—all while unlocking critical agreement data to optimize revenue engines. With Docusign, there’s less swivel and more selling.

Learn more about solutions to common data hygiene challenges.