Data architecture: The bedrock of better business outcomes

Data is big business, and for good reason: access to real-time, reliable, enterprise-wide data can help businesses make better decisions about everything from managing inventory to launching new products in new markets. Yet even though modern organizations are teeming with data, leaders are often unsure whether they can trust the information or turn it into actionable insights. In our work with middle-market clients, we’ve seen organizations struggle with outdated legacy systems, piecemeal add-ons, and conflicting “sources of truth,” causing their teams to spend more time playing whack-a-mole buying a mix of software and services than implementing a sustainable data strategy. The missing link is usually data architecture.

Before companies can unlock the benefits of data-driven decision-making, they need to map how data flows through their systems and create a blueprint for managing that data. The right architecture seamlessly leverages software selection/optimization, data governance, and data management with performance management and business intelligence, giving organizations some crucial advantages in today’s hyper-competitive climate.

Five advantages of the right data architecture

Each organization has its own systems, processes, and business objectives that impact how data is managed, so there’s no one-size-fits-all approach to data architecture. There are, however, common best practices and benefits.

1. Own — and trust — your data

Good data architecture harnesses the twin powers of data governance and data management to create a common language that stands the test of time. In many organizations, departments and systems are siloed, and each team uses its own technology populated with its own data language. For example, different job titles used by HR and operations can create different versions of the same “objective” company data, creating confusion and gridlock. Good data governance applies metadata modeling and data dictionaries to impose a common language and set of agreed-upon rules across an enterprise. In doing so, it creates a “single source of truth” that gives everyone an accurate, holistic view of organizational performance. This standardized data forms the foundation of better insights and smarter decision-making. Data management protects well-governed data by creating a repository where it can live safely forever. You will own it regardless of how your source applications or reporting might change in the future. Even if new performance management technologies and BI requirements are introduced, a sound data architecture foundation will persist.

2. Take advantage of new point solutions without disrupting your organization

Techniques and digital tools to capture source data are evolving constantly. Even ERPs — once considered a silver bullet — can’t do it all; in the past eight years, we’ve seen a proliferation of data solutions designed around specific business processes. Compounding the challenge, each category (data governance, data management, performance management, business intelligence, etc.) has its own slew of specialty vendors with wildly different capabilities, and industry-specific nuances bring even more point players into the mix. Navigating the current market is like comparing apples, oranges, and grapefruits.

¹ Infographic 1: Gartner's ERP timeline (2022)

The good news? The right data governance and management, including a sound metadata model and data repository, position your business to handle technology changes with minimal disruption. Departments can take advantage of new point solutions that help them work smarter and faster; and rather than “going rogue,” those new solutions can be put into your existing data architecture. Lengthy rework is avoided, freeing the business to use the saved time, expense, and resource allocation elsewhere.

3. Use lagging and leading indicators to adjust your operations

Data architecture is the key to unlocking the power of actionable analytics. Organizations need both backward- and forward-looking data to understand where they’ve been and to make decisions that drive better outcomes. For example, when a profitable job site ends up losing money because of a single safety incident, the data only tells you what’s already happened — it’s a lagging indicator. Routine on-site safety talks, on the other hand, are an actionable leading indicator: data aggregated across the enterprise tells you these five-minute huddles help predict future behavior and reduce future accidents.

4. Use data to drive your business strategy

Companies don’t pursue data for data’s sake. Well-architected, cleansed data enables trustworthy information, actionable insights, smarter decisions, and better outcomes. Organizations can more accurately forecast sales, manage inventory, better leverage emerging technologies, gauge employee performance, run what-if analyses, and more. For example, if your business plan is focused on driving growth, you might choose to capture insights on your highest-performing products in terms of sales growth and market penetration. If it’s critical that you minimize risk, you might opt to focus on enterprise data that reflects your quality assurance, compliance, and safety progress. Data architecture is the foundation that lets you gain control of your data and put it to work for your business.

5. Prepare for an ever-changing future

“Agility” is today’s buzzword, but few organizations are prepared to pivot quickly as business and technology change. Data architecture equips you to make well-informed business decisions with speed and confidence — at both the strategic and front-line levels. It also lets you take advantage of new technologies as they emerge — and implement them faster than competitors who are struggling with tech disruption and system integration. While they’re busy playing whack-a-mole, you’ve moved on to chess.

In a world where data reigns supreme and change is constant, the right data architecture can help you create competitive advantage, decrease costs, and increase operational capacity. Whether your goal is to minimize risk, penetrate new markets, sell more of the same product, or increase profitability, it’s ultimately data that will deliver the insights you need to achieve your goal.