Junaid Farooq
Senior Advisor – Data & AI
Why the Time to Act Is Now—and How to Do It Right
As middle market companies scale, data is no longer just an operational byproduct—it’s a critical asset for driving growth, controlling costs, and outperforming competitors. Yet despite rising awareness, most companies still struggle to turn their raw data into reliable, value-generating insights. AI adoption remains aspirational. Data silos, unclear ownership, and inconsistent quality stifle potential. And while large enterprises can afford to spend years architecting next-gen data ecosystems, middle market companies must move faster—with discipline.
At Emerytus Advisors, we believe data should be treated as a product—not just a byproduct. That means applying product thinking to data delivery, treating it with the same rigor and governance as a physical or digital offering. By integrating governance, quality controls, modeling, and user-focused design, “data products” become powerful tools for strategic decision-making.
The Middle Market Data Challenge
Most middle market firms are awash in data—but unable to leverage it.
- Siloed systems: Finance, sales, ops, and HR each own disparate databases with little coordination.
- Data quality concerns: Inconsistent definitions, missing values, and duplication reduce trust.
- Lack of clear ownership: Data is everyone’s responsibility and no one’s accountability.
- Delayed decision-making: Business users wait days or weeks for insights, reducing agility.
- Failed AI initiatives: Pilots launch without reliable training data or defined business outcomes.
What’s more, the cost of inaction is rising. Companies that fail to modernize their data capabilities will lag on key metrics: customer responsiveness, capital efficiency, innovation cycles, and ultimately valuation at exit. As PE sponsors demand tighter execution and faster insights, data maturity has become a make-or-break factor.
Why “Data as a Product” Changes the Game
Data as a Product (DaaP) reorients teams to build consumable, governed, reliable data assets—curated specifically to drive defined business outcomes. According to Gartner, a “data product” includes not only curated data but also metadata, governance, access controls, models, and APIs—all wrapped in a service model built for reusability and ROI.
At Emerytus, we use a maturity framework that moves clients along a five-step path:
- Raw Ingestion: Data is collected “as-is” from multiple source systems, with minimal structure or controls.
- Foundational Data Products: Subject-area-level cleansed datasets become sources of truth.
- Integrated Data Products: Business rules are applied across domains to create trusted views.
- Aggregated Data Products: Purpose-built, cross-functional datasets for strategic KPIs and dashboards.
- Analytics Products: Advanced analytics, dashboards, and AI/ML applications run on certified, trusted data.
Each level requires different technical architectures, governance practices, and user education—but accelerates ROI exponentially .
Common Pitfalls in the Middle Market
Even well-funded efforts can fall short. EA has seen five recurring traps that derail data and AI initiatives:
- Technology-first thinking: Implementing new platforms (e.g., Snowflake, Databricks) without clear business use cases.
- Underinvestment in governance: Data contracts, quality rules, and stewardship are often missing or reactive.
- No product ownership: Without product managers, data efforts lack prioritization and user alignment.
- Overlooking “time-to-insight”: Fancy dashboards mean little if they take weeks to populate or refresh.
- Skipping the MVP phase: Companies chase perfection instead of launching small, functional products.
These traps lead to wasted spend, frustrated users, and “zombie dashboards” that are rarely used or trusted.
The Urgency to Act—Now
In a recent survey, 64% of middle market executives cited “access to real-time insights” as critical to delivering on their 2025 strategic plans, yet fewer than 25% said they had such access today¹. The AI arms race is only accelerating—early adopters are using GenAI to streamline reporting, automate reconciliations, and model revenue scenarios in real time.
Waiting is no longer neutral—it’s risky. Data maturity must be proactively addressed before you reach the next inflection point: a capital raise, acquisition, ERP transformation, or IPO.
Top 5 Actions Middle Market Companies Can Take Now
- Define Business-Centric Data ProductsIdentify 3–5 critical data products that link to revenue, margin, customer experience, or working capital. Prioritize clarity, usability, and repeatability.
- Assign Product Ownership & GovernanceEstablish data stewards and product managers to own the lifecycle—from requirements through evolution.
- Accelerate with Agile DeliveryUse sprints to prototype, test, and iterate on data products. Avoid multi-year waterfall plans.
- Measure ROI & UsageTrack adoption, value realization, and cost savings (e.g., fewer manual reconciliations, faster close cycles).
- Pilot AI on Trusted DataApply GenAI or machine learning to a small, controlled data product—like cash forecasting or customer churn—where quality and governance are already high.
How Emerytus Advisors Helps
EA’s Data & AI practice brings a practical, hands-on approach grounded in execution, not hype. We help clients:
- Define the right data strategy based on current maturity and business imperatives.
- Design and deliver data products that are governed, usable, and integrated into decision cycles.
- Enable modern data architecture leveraging cloud, ETL pipelines, and self-service analytics tools.
- Coach teams on product thinking, governance, and agile delivery methods.
- Implement GenAI solutions that are grounded in clear business needs and trusted data foundations.
By aligning technology, governance, and business outcomes, Emerytus helps middle market companies transform data from a liability into a competitive asset.
Conclusion
Middle market firms no longer have the luxury of viewing data as a back-office IT concern. It’s now central to value creation, risk mitigation, and strategic agility. Those who act now—grounded in product thinking and agile execution—will lead the next generation of industry leaders.
Emerytus Advisors stands ready to guide the journey from fragmented data to actionable intelligence, from spreadsheets to strategic foresight, from AI experiments to AI-enabled enterprise.
Sources
- National Center for the Middle Market, “Middle Market Indicator,” Spring 2024.
- Gartner, “Innovation Insight for Data as a Product,” 2023.
- McKinsey & Company, “Data Transformation: Moving from Good to Great,” 2024.
- Harvard Business Review, “Why Data and AI Efforts Often Fail,” Jan 2023.
- Internal Emerytus Advisors content: Data Product Framework .