Advisory Services
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Best for teams whose CRM data has degraded to the point where nobody trusts it
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.
- 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
- 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
- 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
- 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
- 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
- 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
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?
- Team distrusts CRM search and relies on spreadsheets instead
- Duplicate records multiply faster than anyone can merge them
- Leadership acknowledges the data quality problem and will enforce new standards
- Not planning to replace the system entirely (optimization, not migration)
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.