Solve the problem behind the problem

Let's start with a scenario every consultant has lived through:

Customer says: "We need a dashboard that shows real-time transaction data"

Consultant builds: Beautiful real-time dashboard with live transaction feeds

Customer reaction six months later: "This is nice, but it doesn't help us with our actual problem—we can't predict our monthly revenue because customers transact randomly throughout the month"

You built exactly what they asked for. But you solved the wrong problem.

Problems v Symptoms

Here's the dangerous assumption most implementations make: if we perfectly capture what customers say, we'll build what they need.

But customers don't speak in requirements. They speak in symptoms.

When they say "we need better reporting," they might mean:

• Our current reports have the wrong data (data quality problem)

• Our reports are too slow (performance problem)

• Our reports exist but nobody uses them (usability problem)

• Our reports don't tell us what we need to know (metrics problem)

• We don't trust our reports (validation problem)

• Our board wants different information (stakeholder problem)

Each of these represents a completely different solution in the new system.

Where Great BAs Shine

This is where expert consultants add their real value: understanding the problem behind the request.

A good consultant hears "better reporting" and asks:

• "What decisions are you trying to make with this data?"

• "What happens when you can't get the information you need?"

• "Walk me through the last time reporting was a problem for you"

• "What would 'success' look like for your reporting process?"

But here's the challenge: doing this kind of deep problem analysis takes time and expertise. And most consultants are drowning in administrative overhead.

AI Changes Everything

This is where AI becomes a strategic amplifier, not just a transcription service.

Glossa doesn't just capture what customers say—it analyzes the context around what they're saying:

Surface-level request: "We need automated email receipts"

Glossa's context analysis:

• Client mentioned their customers complaining about slow response times

• Current process requires manual email creation for each transaction

• Staff spending 10+ hours per week on receipts

• Board concerned about customer retention rates

• Underlying problem: Manual process creating customer satisfaction issues and staff burnout

Now you can design a solution that addresses the real problem: customer relationship management, not just email automation.

The Glossa Advantage

Here's where Glossa really shines: identifying patterns across all customer input that humans might miss.

A customer might mention in different conversations:

• Week 1: "Our reporting takes forever"

• Week 3: "We're always scrambling for board meeting data"

• Week 5: "Our auditors need information we can't easily provide"

• Week 7: "Department heads complain they can't get the data they need"

Individually, these seem like separate reporting requests. But Glossa's analysis can identify the pattern: this organization has a systemic data accessibility problem, not just individual reporting needs.

The solution isn't four different reports—it's a comprehensive data strategy.

Requirements Quality Check

Glossa's Requirements Quality Check doesn't just organize what customers say—it identifies when they're describing contradictory needs:

Monday's conversation: "We need real-time dashboards so we can see what's happening immediately"

Wednesday's conversation: "Our data is often wrong until we do our monthly cleanup process"

A human BA might capture both as separate requirements. Glossa flags the contradiction: you can't have reliable real-time dashboards with monthly data cleanup.

The real problem isn't dashboard timing—it's data quality processes.

Embedded Best Practices

Here's where Glossa becomes a strategic advisor: it can incorporate your SI’s implementation best practices into problem-solving.

Customer request: "We want to track everything about our customers—every interaction, every preference, every family member"

Best Practice guidance:

• Similar organizations with comprehensive tracking often struggle with data maintenance overhead

• Privacy regulations may limit how much personal information can be stored

• Staff typically use 20% of tracked data for 80% of decisions

• Recommended approach: Start with high-impact data points, build feedback loops to identify what's actually useful

Perspective Synthesis

Different stakeholders often describe the same underlying problem from different angles:

Executive: "We need better visibility into our programs" 

Program Manager: "I spend too much time creating reports instead of managing programs"

Development Director: "I can't show donors the impact of their gifts" 

Finance Director: "We can't easily track restricted fund compliance"

Glossa can synthesize these perspectives to identify the core issue: fragmented data preventing effective organizational storytelling and compliance management.

Workflow Redesign Opportunities

Sometimes the best solution isn't building what customers describe—it's redesigning how they work.

Customer description: "We need a complex approval workflow with seven signature requirements and escalation rules"

Glossa analysis: Current process designed around paper-based approvals from 1995. Modern alternatives could include:

• Risk-based approval thresholds

• Digital signature integration

• Automated compliance checking

• Exception-based workflows

The technology enables process improvement, not just process replication.

BA Amplification

AI doesn't replace expert judgment—it amplifies it by handling the analysis overhead.

Instead of spending hours manually reviewing customer conversations to identify patterns, consultants can:

• Review AI-generated problem summaries and add strategic context

• Validate AI-identified contradictions and design resolution approaches

• Evaluate AI-suggested solutions against specific customer constraints

• Focus on high-level solution design instead of detailed requirements capture

When Glossa handles the analytical heavy lifting, consultants can have strategic conversations instead of administrative ones:

Traditional conversation: "Let me walk through these 47 requirements we captured from your interviews"

Glossa-enabled conversation: "Based on our analysis, you have three core challenges. Let's talk about which solution approach would work best for your organization"

Elevating Consultant Work

But here's the crucial part: AI insights must be validated with customers, not just implemented blindly.

AI might identify that the real problem is data quality, but the consultant still needs to:

• Confirm this analysis with stakeholders

• Explore the organizational readiness for data quality improvements

• Design change management around process improvements

• Validate that solving the underlying problem addresses the symptoms customers mentioned

The future isn't about AI replacing consultant expertise—it's about elevating what consultants do.

Instead of: Requirements capture and documentation
Consultants focus on: Problem diagnosis and solution design

Instead of: Managing spreadsheets and version control
Consultants focus on: Strategic thinking and stakeholder management

Instead of: Transcribing what customers said
Consultants focus on: Understanding what customers need

Competitive Differentiation

Consultants who master AI-amplified problem analysis will differentiate themselves by:

Delivering better outcomes: Solutions that address root causes, not just surface symptoms
Providing strategic value: Insights about what customers need, not just what they asked for
Building stronger relationships: Customers trust advisors who understand their real challenges
Reducing rework: Getting to the right solution faster because you identified the right problem

Solving the Real Problems with Glossa

The best implementations have always been about solving the right problem, not just building the right features.

Glossa makes it possible to do this kind of deep problem analysis at scale and speed. Not by replacing human insight, but by giving human insight the analytical foundation it needs to be strategic.

Your customers need advisors who can see beyond their symptoms to their underlying challenges. AI gives you the analytical capability to be that advisor consistently and comprehensively.

The question isn't whether you'll use AI to transcribe customer conversations. The question is: will you use it to understand what those conversations really mean?

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Ready to solve the problems behind the problems? See how Glossa's AI analysis helps you identify the real challenges customers face—so you can design solutions that actually work.