Turn Your CRM From Liability Into Asset
Duplicate records. Outdated contacts. Fields nobody uses. Searches that return garbage. Your ATS or CRM was supposed to make work easier, but years of accumulated data debt have turned it into something your team works around instead of with. I fix that.
The Slow Death of a CRM
Nobody wakes up one day with a broken CRM. It happens gradually. A few duplicate records become a few thousand. Custom fields multiply until nobody remembers what half of them mean. Workarounds become standard practice. And eventually, your most expensive system becomes your least trusted.
The same candidate appears three times with slightly different information. The same company has five records from five different years. Merging them is terrifying because you don't know what data you'll lose. So they multiply.
Custom fields added for projects that ended years ago. Dropdowns with options nobody uses. Required fields that people fill with garbage just to get past the screen. Your data model is archaeology, not architecture.
Your recruiters don't trust search results. They've learned that finding someone requires checking multiple places, because the "single source of truth" isn't. So they maintain their own spreadsheets.
Reports look complete, but everyone knows the numbers are fuzzy. Incomplete records, inconsistent data entry, and duplicate counting give leadership confidence they shouldn't have.
Each problem makes the system less useful. Less usefulness means less investment in keeping data clean. Less clean data means more problems. The spiral continues until the CRM is a formality, not a tool.
I've inherited CRMs with 40% duplicate rates and fields that hadn't been used in years. They're fixable, but it requires someone who's done it before and knows how to do it without breaking what still works.
Systematic Cleanup, Lasting Results
Optimization isn't a one-time cleanup. It's about establishing systems and practices that keep your CRM healthy. I fix the immediate mess, then help you build the habits that prevent it from returning.
- I Understand Operational Reality.
After years as a systems admin, I know that data problems aren't just technical. They're human. People create workarounds for reasons. Understanding why things got messy is the first step to fixing them properly.
- I Preserve What Matters.
Cleanup shouldn't mean losing history. I develop merge rules, archival strategies, and validation processes that consolidate data without destroying institutional knowledge.
- I Build Prevention Into the Fix.
Every cleanup includes configuration changes, validation rules, and process adjustments that make it harder for the same problems to return.
What Optimization Includes
Data Cleanup & Deduplication
Thousands of duplicate records make search unreliable and reporting inaccurate.
The Solution
- Analyze duplicate patterns and root causes
- Develop merge rules that preserve critical data
- Execute controlled deduplication with validation checkpoints
- Implement prevention: duplicate-blocking rules, entry validation
Typical Result: 30-50% reduction in record count with zero data loss
Configuration Audit & Refinement
Field layouts, picklists, and workflows were set up years ago and haven't kept pace with how your team works.
The Solution
- Audit every custom field, picklist, and workflow
- Identify unused, redundant, or confusing elements
- Redesign interfaces for current workflows
- Simplify without losing necessary functionality
Typical Result: Cleaner screens, faster data entry, happier users
Data Quality Framework
Even after cleanup, bad data creeps back in without governance.
The Solution
- Define data quality standards for key fields
- Implement validation rules at point of entry
- Create ongoing monitoring dashboards
- Establish ownership and accountability
Typical Result: Sustained data quality with early warning when standards slip
Integration Health Check
Connected tools create data inconsistencies when sync rules don't match.
The Solution
- Audit data flow between systems
- Identify sync conflicts and failures
- Align field mappings across integrations
- Establish monitoring for integration health
Typical Result: Consistent data across your tech stack
Search & Reporting Optimization
Users can't find what they need, and reports don't reflect reality.
The Solution
- Optimize search configurations and relevance rules
- Clean up the data that makes search unreliable
- Rebuild key reports on solid data foundations
- Create dashboards that surface actionable insights
Typical Result: Search your team trusts, reports leadership can rely on
How Optimization Works
1. Assessment
Data quality audit (duplicates, completeness, accuracy), configuration review (fields, picklists, workflows, permissions), integration inventory, and user interviews to understand how people actually work vs. how they're supposed to.
Deliverable: Health assessment with prioritized issues and recommendations
2. Cleanup Planning
Prioritize issues by impact and risk, develop merge rules and validation logic, plan migration of valuable data from deprecated fields, design testing and rollback procedures.
Deliverable: Detailed cleanup plan with risk mitigation
3. Execution
Execute cleanup in controlled batches, validate results against expected outcomes, adjust approach based on what we learn, maintain full audit trail for accountability.
Deliverable: Cleaned and optimized system with documentation
4. Prevention
Implement validation rules and duplicate blocking, configure monitoring dashboards, train team on new standards and practices, document governance procedures.
Deliverable: Sustainable data quality program
What You Get
- A System Your Team Actually Uses.
When search works and data is reliable, people stop working around the CRM and start working with it. Adoption improves because the system deserves trust.
- Confident Decision-Making.
Reports built on clean data mean leadership can trust the numbers. No more asterisks on every dashboard.
- Faster, More Accurate Work.
Recruiters find candidates on the first search. Account managers see complete client history. Everyone spends less time hunting and verifying.
- Scalability.
A clean system handles growth. A messy one amplifies problems with every new user and record.
typical reduction in duplicate records
improvement in search accuracy
faster data entry after UI optimization
systems cleaned and optimized
Is This Right for You?
This service fits if:
- Your team doesn't trust search results and maintains their own spreadsheets
- Duplicate records have multiplied faster than you can merge them
- Custom fields and layouts haven't been reviewed in years
- Reports require manual adjustment to be accurate
- New hires are confused by the system complexity
- You're preparing for a migration and need clean data first
Signs you're ready:
- Leadership acknowledges data quality is a problem
- Team will cooperate with new data entry standards
- You have time to implement changes (not mid-crisis)
- Willing to invest in prevention, not just cleanup
Might not be the right fit:
- You're planning to replace the system entirely (let's talk about migration instead)
- Nobody will enforce new standards after cleanup
- You need a quick fix without addressing root causes
Systems I Optimize
Primary Expertise
Bullhorn
Deep experience with configuration, customization, and data management
Automation
Workflow optimization, automated triggers, and candidate engagement flows
Amplify
AI-powered talent engagement and candidate communication
Also Works With
The principles of data quality apply across platforms. Even if your system isn't listed, chances are I can help.
Common Questions
Let's See What's Possible
A 30-minute conversation will help you understand the state of your data and what it would take to fix it. You'll get honest assessment. Sometimes the answer is "this is manageable internally," and sometimes it's "you need help." Either way, you'll have clarity.