The Intersection – Episode 11: Good Data In, Good Decisions Out — Why AI Can’t Fix What You Never Collected

Summary

AI can only be as useful as the information behind it. In this episode, Megan Kacvinsky, Steve Coffey and Denine Harper explore how disconnected or incomplete marketing, sales and production data can lead to convincing but flawed AI recommendations - and what manufacturers can do to build cleaner, connected data systems for better decisions.

Key Insights

• AI makes data quality more consequential. Incomplete records can still produce persuasive recommendations, creating risk when leaders act without the full context.

• Marketing and sales need a shared record of how demand becomes profitable revenue. In building materials, the person influenced by marketing is often not the person who ultimately purchases the product.

• Shared definitions matter. If teams or regions define qualified leads, opportunities or other lifecycle stages differently, AI analysis can amplify those inconsistencies rather than resolve them.

• Data silos extend beyond sales and marketing. Finance, procurement, supply chain and production-floor data can add critical context about margin, capacity, scrap, fulfillment and customer value.

• Apparent performance can be misleading without context. A high-performing sales rep, product or region may look successful because of underlying customer or market conditions rather than the tactics being measured.

• Manufacturers selling through dealers and distributors face an additional visibility gap. Connecting project, order and transaction identifiers can help trace influence from marketing activity through the final sale.

• Production-floor visibility can uncover incremental efficiency and margin opportunities by showing what is happening at individual workstations and across facilities in real time.

• The best starting point is the decision itself: define the evidence required to answer a business question, then work backward to determine what information must be captured and connected.

Practical Takeaways for Manufacturers

• Start with a specific business question - such as which marketing efforts produce profitable customers - before deciding what data to collect.

• Create shared definitions across marketing, sales and other teams for leads, opportunities, lifecycle stages and other critical fields.

• Connect CRM, ERP, financial and production information wherever possible so analysis reflects the full customer and operational journey.

• Build data capture into employees' existing workflows. Use automation and AI-assisted tools to reduce repetitive manual entry, while maintaining human checks for accuracy.

• Record information as activity occurs instead of relying on employees to reconstruct calls, transactions or production activity later.

• Assign managers responsibility for data quality, including whether records are complete, current, accurate and consistently entered.

• For channel sales, explore common identifiers that can connect marketing leads, project activity, purchase orders and dealer or distributor transactions.

• Treat AI output as analysis that still requires context and validation - not as a substitute for governance or informed human decision-making.

About the Hosts

Megan Kacvinsky — CEO | Point To Point

Megan Kacvinsky helps Building Product Manufacturers drive specification through targeted AEC marketing. As a partner at Point To Point, she specializes in demand generation, customer engagement, and strategic content marketing that fuels sales success.

With 15+ years of experience, Megan combines digital marketing expertise with sharp business acumen to bridge the gap between marketing strategy and real-world impact. She has transformed marketing programs for Fortune 500 companies, mid-market firms, and startups—adapting strategies to fit each organization's unique needs. Known for her tailored, results-driven approach, Megan crafts high-impact solutions that help brands thrive in the competitive building and manufacturing industries.

Denine Harper — Founder | DHx Consulting

Denine Harper is the founder of DHx Consulting and a Fractional CMO who helps building materials manufacturers turn strategy into measurable growth. She works at the intersection of brand, demand generation, and go-to-market execution—aligning sales, marketing, and operations to drive revenue without friction.

With experience leading large-scale brand and performance initiatives, Denine brings a practical, operator’s perspective to growth. She is known for building systems that improve visibility, strengthen positioning, and help companies scale with confidence.

Steve Coffey — Senior Managing Partner | Coffey & Co

Steve Coffey is the co-founder of C&C and has spent nearly a decade working closely with building materials manufacturers across the residential and commercial construction industry. His experience spans executive strategy, plant operations, and job site realities, giving him a practical understanding of how products actually make it into buildings. Today, he helps companies bridge the gap between innovation and execution by aligning teams, improving visibility, and building systems that enable scalable growth.

Quotable Moments

• “The quality of your information [is] more consequential [with AI] because it can turn an incomplete data point or an incomplete data record into a very persuasive recommendation.” - Steve Coffey

• “Start with the end in mind and work your way backwards.” - Megan Kacvinsky

• “Make managers accountable for evidence quality.” - Steve Coffey

Next Steps for Manufacturers

Manufacturers do not need to connect every system at once. Begin with one important decision, identify the evidence required to make it well, and map backward to the marketing, sales, financial or production data that supports it. Standardize definitions, make capture part of everyday work and give managers ownership of data quality. With cleaner, connected information, AI can become a more reliable tool for improving growth, efficiency and margin.