Building Your Data Quality Roadmap: From Standards to Scorecards

Kade Brewster • November 21, 2024

Building Your Data Quality Roadmap: From Standards to Scorecards

If I had a dollar for every time I've heard, "We don't trust our data" or "Our data isn't accurate" or "These reports don't match", I'd be happily retired and certainly wouldn't spend time writing this blog. Issues with data quality are extremely prevalent in a majority of businesses, but in today’s data-driven world, ensuring high-quality data is not just a technical necessity, it’s a strategic advantage. To achieve this, organizations must craft a comprehensive Data Quality Roadmap—one that leads from clear policies and standards all the way to measurable execution outcomes. Let's explore how to create an effective roadmap that ensures your data is trustworthy, consistent, and ready to drive business decisions.

Laying the Foundation: Enterprise Data Management Policy

Building a robust data quality framework starts at the top with an Enterprise Data Management Policy (EDMP). This policy is the "what" of data management—establishing foundational principles that guide how data should be handled throughout the organization. It serves as the cornerstone of all data quality initiatives, ensuring alignment between data management practices and strategic business goals. Without a clear policy, organizations often struggle with quality, compliance, and operational consistency.

Setting the Standards: Data Management and Governance (DM&G)

Once a solid EDMP is in place, the next step is to establish Data Management and Governance Standards. These standards are the "specifications" that outline the requirements for data management, including quality. They provide detailed guidelines to promote consistency, accuracy, and interoperability across data domains. Think of these standards as the objectives that outline the desired quality and consistency of data, serving as benchmarks for an organization to strive for.

Execution Strategies: Bringing Data Quality Standards to Life

With policies and data quality standards defined, the focus turns to the "how" of data quality management. Execution Strategies outline the processes, tools, and technologies needed to adhere to the standards. They are critical for translating high-level principles into day-to-day activities, allowing organizations to manage data quality consistently while adapting to changing needs. These strategies pave the way for data quality practices, ensuring scalability and continuous improvement.

Components of Data Quality Standards

Data Quality Concepts

These are the core concepts, or types of data quality, that ensure data is fit for purpose:

Accuracy: Data should be sufficiently accurate for its intended purposes. Accuracy is most likely to be secured if data is captured as close to the point of activity as possible. Data should be captured once only, although it may have multiple uses. The importance of the uses for the data must be balanced with the costs and effort of collection. Where compromises must be made on accuracy, the limitations of the data should be clear.

Consistency: Data should remain consistent across different data domains and maintain uniformity and coherence.

Reliability: Data should reflect stable and consistent data collection processes across collection points and over time. Users of the data should be confident that improvements reflect real changes rather than variations in data collection approaches or methods.

Timeliness: Data should be captured as quickly as possible after the event or activity and must be available for the intended use within a reasonable time.

Completeness: Data requirements should be clearly specified based on the information needs of the body and data collection processes matched to these requirements. Monitoring missing, incomplete, or invalid records can provide an indication of data quality and can also point to problems in the recording of certain data items.

Pillars of Quality

Key definitions for three major components of overall quality efforts:

Metadata: Metadata is “data about data”. It provides detailed and contextual information about the content, format, structure, and origin of data. Metadata is a critical component of data quality standards as it improves data understanding, documents data ownership and usage, identifies critical data elements, and provides information to enable the tracking and assessment of data quality over time.

Data Lineage: Data lineage refers to the life cycle of data, tracing its flow from origin through various transformations and uses, to its final form(s) or destination(s). Data lineage is often recorded in a visual diagram format and is critical for transparency in data usage, error tracing and resolution, and providing the ability to conduct impact analysis on data quality issues.

Data Quality: Data quality is a measure of the condition of data, assessed by quality the quality concepts accuracy, consistency, reliability, timeliness, and completeness. Having data quality measures are critical to provide clear, measurable targets for improving data quality, managing data quality across the data lifecycle, and ensure the successful integration of data into business processes.

Data Element Concepts

Essential building blocks for structuring and managing quality data:

Critical Data Elements (CDEs): Critical Data Elements are data points that are essential to an organization’s core operations, decision-making processes, regulatory requirements, and risk management. Critical Data Elements warrant stricter data governance practices and quality measures. Both Entities and Attributes can be Critical Data Elements.

Non-Critical Data Elements: Non-Critical Data Elements are all data points that do not meet the criteria to be considered Critical Data Elements.

Entities: A data entity represents a real-world object or concept within an organization’s data ecosystem (e.g. People or Products). Entity definition is crucial for ensuring structural integrity of data, and the mapping of relationships between entities.

Attributes: Attributes provide descriptive details about an entity, characterizing its properties or qualities (e.g. Date of Birth). Attributes are data that is collected about each entity.

Service Level Objectives (SLOs): SLOs are specific, measurable goals related to the quality of data elements. SLOs should be created for each specific data domain and measure the quality of data elements in relation to the concepts of quality. SLOs provide clear quality benchmarking, as well as management and escalation pathways for quality issues.

What Does Executing on a Data Quality Roadmap Look Like?

Executing a Data Quality Roadmap is not a one-off project—it's an ongoing process. As seen in our graphic at the top of this page, the steps include:

Identify Systems of Record (SOR): Capture all the datastores that are authoritative for the data elements coming into your data quality management.
Identify Critical Data Elements (CDEs): Identify the business-critical data elements (e.g., supports critical initiatives, financially impactful) to focus efforts on what’s most important.
Metadata Catalog: Capture the necessary details about the data to manage it effectively (e.g., data steward, security classification, source system).
Business Glossary/Data Dictionary: Align the data to real world concepts in the business to ensure a consistent understanding of that data.
Systematic Lineage: Create traceability for data elements to ensure data consumers have clarity and trust of accuracy into the origin of the data they are using.
Service Level Objectives (SLOs): Establish data quality service level objectives to ensure that the data under management has well defined and well understand quality thresholds.
Monitoring and Remediation: Monitor data quality service level objectives, driving the remediation and root cause analysis for deviations, as appropriate. This is usually done with the creation of data quality scorecards.

Data Quality Scorecards: Measuring Success

An essential tool in this roadmap is the data quality scorecard. These scorecards provide a measurable way to track progress and enforce data quality across the enterprise. By monitoring key metrics such as accuracy, completeness, and timeliness, scorecards not only highlight areas for improvement but also foster accountability among data stakeholders. Effective data quality scorecards give organizations the confidence they need to use their data for strategic decision-making.

Conclusion: Driving Business Value with High-Quality Data

A successful Data Quality Roadmap takes an organization from foundational policies to precise standards and actionable execution. By focusing on core concepts like Critical Data Elements, metadata, data lineage, and using data quality scorecards, organizations can ensure that data remains accurate, reliable, and valuable. This journey is vital for transforming data from a simple resource into a powerful tool that drives business innovation and competitive advantage.

Ready to start your data quality journey? Ensuring data quality isn't just about compliance; it’s about building a foundation for business growth and efficiency. Take the first step today by establishing clear policies and standards, and soon you’ll see the transformative power of high-quality data in action. If you'd like to discuss how you can get started on your data quality journey, please book a meeting with us directly, or reach out via one of our channels.

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At Brewster Consulting Group, we recognize that managing data can be a daunting task for small and mid-sized enterprises. Allow us to assist you in harnessing the potential of operational intelligence! Reach out to one of our specialists today to refine your data strategy, optimize your processes, and establish solid governance. Ready to cultivate data analysis and propel scalable growth? Your journey begins right here!

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How Small Marketing Firms Can Scale Smarter with Fractional Project Management

By Ranae Peterson • October 29, 2025

In the fast-paced world of marketing, agility is everything. But for many small marketing firms , staying organized and executing effectively can feel like an uphill battle. Between juggling client deliverables, managing creative teams, and keeping up with digital trends, it’s easy for even the most talented agencies to lose focus or momentum. That’s where fractional project management comes in - a cost-effective, flexible way for small agencies to gain project management expertise without the overhead of a full-time hire. What Is Fractional Project Management? Fractional project management allows marketing firms to hire an experienced project manager or project management team on a part-time, contract, or as-needed basis. These professionals provide the strategic direction, structure, and accountability of a full-time role, but with the flexibility and affordability that small firms need. Unlike traditional project management roles, fractional project managers adapt to your workflow. They can: Create or refine marketing project management frameworks. Oversee campaign timelines, deliverables, and communication. Manage resources, budgets, and vendor relationships. Introduce project management tools, such as Asana. Provide performance insights to keep campaigns aligned with business goals. The Common Challenges Small Marketing Firms Face: Running a small marketing firm means constantly balancing creativity, client satisfaction, and growth, all while working with limited time, budgets, and staff. While many small agencies deliver incredible results for their clients, their internal operations are often suboptimal. Without proper structure and project management in place, business operations can quickly become reactive instead of proactive. Here are some of the most common challenges small marketing firms face, many of which can be alleviated with the right fractional project management support: 1. Inconsistent Execution of Marketing Strategies Small firms often start projects with enthusiasm but struggle to maintain consistency across campaigns, clients, and platforms. Without a clear project roadmap or centralized process, teams can lose sight of timelines, priorities, or deliverables. This inconsistency can lead to missed deadlines, off-brand messaging, and a loss of client confidence over time. 2. Limited Budgets and Tight Margins Many boutique agencies operate on razor-thin margins, meaning that hiring a full-time senior project manager or operations manager may simply be out of reach. This leads to a “DIY” approach to project coordination, where creative directors, account managers, or even designers end up juggling scheduling and task tracking in addition to their core roles. It’s a recipe for burnout and inefficiency. 3. Attracting and Retaining Talent In the marketing world, top talent wants growth, clarity, and collaboration. When internal processes feel chaotic or constantly changing, employees can become frustrated or disengaged. A lack of structured project management can contribute to high turnover, especially among younger professionals looking for organized environments where they can learn and thrive. 4. Keeping Up with Industry Trends and Technology Marketing trends shift faster than ever, from SEO and social media algorithms to automation and analytics tools. Small firms, often focused on servicing clients, rarely have time to step back and strategically assess which technologies to adopt or how to integrate them effectively into their workflows. This can result in wasted subscriptions, underutilized tools, or outdated methods that slow productivity. 5. Balancing Growth and Quality As marketing firms grow, the complexity of managing multiple campaigns, channels, and clients multiplies. Without scalable project management processes, expansion can lead to growing pains: stretched teams, missed opportunities, and declining quality of work. Fractional project management can help maintain creative excellence while effectively scaling operations. 6. Cash Flow and Resource Allocation Project delays, scope creep, and unclear task ownership often lead to billing inaccuracies and wasted time. Many small agencies underestimate how much untracked work cuts into profit margins. Without proper project visibility or a defined workflow, forecasting becomes guesswork, making it harder to predict cash flow or plan for sustainable growth. 7. Client Communication and Expectation Management Misaligned expectations between the firm and its clients are another major pain point. When communication is informal or scattered across emails and chat threads, misunderstandings arise. A structured project management system creates transparency, accountability, and shared visibility, all key to stronger client relationships. 8. Content Creation Bottlenecks Small firms often pride themselves on creativity, but without workflow organization, content can get stuck in feedback loops. Campaign approvals, revisions, and scheduling can all become bottlenecks that stall production. Over time, this can limit the firm’s ability to scale output or deliver consistently across multiple accounts. 9. Lack of Technology Utilization Even when agencies have invested in tools like Asana, ClickUp, or Monday.com, they often fail to leverage them effectively. Either no one owns the system or team members don’t have time to update it. The result is a fragmented picture of project progress and duplicated effort, both of which fractional project managers specialize in resolving. 10. Burnout and Overwork With so many moving pieces, it’s no surprise that burnout is common among small marketing teams. When deadlines stack up and roles blur, people spend more time reacting to problems than delivering creative solutions. Over time, that stress impacts morale, retention, and ultimately, client results. In short: most small marketing firms aren’t lacking talent, they’re lacking structure. And without a scalable framework for managing people, projects, and priorities, even the most brilliant ideas can get lost in the shuffle. How Fractional Project Management Helps Small Marketing Firms Fractional project management offers both strategic and operational advantages for small agencies, including: Strategic Oversight Without the Cost: Fractional PMs bring senior-level strategy to the table without requiring a full-time salary. They guide teams on where to prioritize resources, how to align goals, and how to scale efficiently. Flexibility and Scalability: Whether your firm manages two clients or twenty, fractional project management services scale with you. You can engage in support during busy periods or for specific initiatives without long-term commitments. Immediate Access to Top Talent: Fractional project managers are seasoned professionals who’ve worked with multiple marketing firms, giving your team instant access to best practices and proven systems. Improved Accountability and Execution: With an external PM keeping projects on track, your creative team can focus on what they do best: creating and delivering exceptional marketing work. Enhanced Profitability and Efficiency: From budget management to workflow optimization, a fractional project manager helps uncover bottlenecks that waste time and money, improving cash flow and project margins. When Should a Small Marketing Firm Consider Fractional Project Management You might not need full-time help yet, but here are a few signs it’s time to bring in a fractional project manager : -You’re juggling too many high-value projects at once. -Projects are constantly behind schedule or over budget. -Your team is overworked, burned out, or missing deadlines. -You lack internal project management expertise. -You feel stuck or overwhelmed trying to manage growth. If these sound familiar, fractional project management might be the missing piece. The Bottom Line For small marketing firms, fractional project management isn’t just about organization; it’s about unlocking growth. With the right systems in place, marketing agencies can scale confidently, deliver better results, and focus on what they do best: creativity and strategy. As the marketing landscape evolves, fractional project management services offer a competitive edge, one that combines flexibility, structure, and cost efficiency.

Turning Data into Direction: Why Small Businesses Need Fractional Analytics

By Ranae Peterson • October 9, 2025

Many small businesses are laser-focused on growth, sales, and staying afloat. In that constant hustle, one of the most valuable assets, data , often gets overlooked. Even when businesses “look at the numbers,” that doesn’t always mean they’re collecting the right data, tracking the right KPIs, or translating those insights into actionable strategies. Fractional analytics bridges that gap. It allows small businesses to access experienced data analysts or analytics teams on a part-time or project basis, essentially bringing enterprise-level data expertise without the full-time cost. Think of it as analytics-as-a-service for small business owners who need clarity and insight but can’t justify a full analytics department. The Reality: Why Data Gets Overlooked While most business leaders know data is “important,” it can be hard to see its impact until it’s visualized through dashboards, real-time reporting, or guided by a professional who knows how to turn information into action. Without these tools and expertise, business decisions often rely on gut instinct instead of insight, leading to inefficiencies, missed opportunities, and in some cases, failure. Statistics show that: About 20% of small businesses don’t survive their first year. Nearly 50% fail within five years. Around 65% close within ten years. While the reasons vary, from financial mismanagement to poor planning, many of these challenges stem from a lack of data visibility or poor data management . In other words, the root cause often isn’t just financial; it’s analytical . Real World Analogy Imagine running a restaurant without ever checking what inventory levels, most frequent orders, or best margin products. You might think you’re doing well because the restaurant is busy, but when you do the books, you’re not actually making any money. Now, imagine having a fractional analytics consultant helping you organize and visualize your data. They don’t need to be in the kitchen every day, but when they are, they bring order to chaos, tracking inventory and margin by menu item, predicting staffing needs, and saving costs by cutting waste. That’s what fractional analytics does for your business data. It helps you understand what’s really happening across operations, finance, and customer service so you can make smarter, faster decisions. Common Operational Challenges Solved by Fractional Analytics Here are a few common pain points small businesses face that fractional analytics services can address: Inefficient reporting and manual data entry. Lack of clear KPIs or performance tracking. Inconsistent financial forecasting. Missed revenue opportunities due to incomplete data. Poor inventory or resource management. Lack of clarity around customer behavior and profitability. Benefits of Fractional Analytics for Small Businesses Engaging a fractional analytics provider offers far more than just numbers and dashboards. It’s about empowering smarter decisions without breaking the bank. Cost efficiency: Avoid the high salary and benefits of full-time analytics hire. Speed to impact: Gain immediate access to expertise, no lengthy onboarding or training required. Scalability: Bring in analytics support when you need it and scale it up as you grow. Better decision-making: Replace guesswork with data-driven insights and actionable KPIs. Time savings: Spend less time in spreadsheets and more time growing your business. Long-term cost reduction: Identify duplicate payments, missed invoices, and inefficiencies that quietly drain profit. Fractional analytics also enhances cash flow management and enables business leaders to spot opportunities for optimization, often resulting in measurable growth and sustainability. Why It’s a Make-or-Break Decision Choosing whether to work with a fractional analytics consultant could be the difference between surviving and thriving. Many business owners don’t realize that outsourced analytics is even an option, one that offers flexibility, affordability, and strategic insight without high overhead. The truth is, small business leaders don’t have to do it all alone, nor do they need to rush into hiring a full-time team. Fractional analytics gives them the best of both worlds: the expertise of a senior data strategist and the flexibility of a part-time engagement. Final Thoughts In today’s competitive market, data-driven decision making isn’t optional; it’s essential. Small businesses that embrace fractional analytics gain clarity, confidence, and control over their operations. By investing in the right insights today, they set up the foundation for sustainable growth tomorrow. If your business is ready to move from guessing to growing, now’s the time to explore what fractional analytics services can do for you.