Synchronized Data: The Foundation for Better Decision Making

Recently, the global economy has been unmistakably shaken by various disruptions. A global pandemic, supply chain shortages, high inflation, and international conflicts, among the most recent, are still impacting businesses across industries.

As organizations navigate these challenges, many struggle to be responsive to near-constant change. For those without a clear data blueprint, agility remains elusive. Yet, those that have mastered the use of their data in pursuit of growth and resilience are well positioned to thrive in an uncertain future.

Over the last several years, many businesses identified a gap between the rapidly shifting market and their ability to quickly align data to plan and forecast effectively. Organizations no longer have the luxury of time as they struggle to make sense of the wide volumes of data available to them. And a lack of data consistency and literacy limits proactivity.

Through 2025, analysts predict that 80% of organizations seeking to grow their digital business will fail due to their refusal to take a more modern approach to data governance. To survive, leaders must look beyond traditional methods to view, compare, and analyze data more dynamically and with much less manual effort.

That’s why forward-thinking leaders are working to synchronize their data — operational, financial, and managerial — in one place. Businesses must employ a 360-degree view of aligned data across systems to enable leaders to use timely, accurate data to make smart, quick decisions.

To enable data insights that are meaningful and provide accurate information for planning (make/buy decisions, pricing, marketing campaigns, and production, etc.), businesses need a solid data foundation that includes:

• Enterprisewide access to and coordinated use of data.
• Quality automated reporting.
• The regular translation of transaction data into views that support profitability analysis.

Information design is the practice of taking data and presenting it in a way that makes it easily understood. This is a critical capability for modern businesses.

A study conducted by the International Data Corporation (IDC) found that data professionals are spending more than twice as much time searching for and preparing data than they are analyzing it. In today’s digital revolution, simplifying and fast-tracking the transition from data extraction to data visualization is not just nice to have; it’s required.

There are six key drivers of success when designing information models across domains and processes.

1. Common vocabulary: Clearly defining what each term represents, along with what it includes (and doesn’t), can be a real game changer for scaling businesses.
2. Discrete terms: Each term used within the model should align to a single concept.
3. Business context: Each term should be defined using business terminology and concepts rather than those related to a specific technology.
4. Broad application: Standards and definitions should be broadly applicable across teams or functions rather than specific to an application, project, or business segment.
5. Enforcing relationships: Attributes of an entity are modeled and defined across the organization’s business solutions (customer relationship management, human capital management, enterprise resource planning, enterprise performance management, and data and analytics).
6. Organization: Hierarchies, groupings, ranges, and other mechanisms are used to organize master data.

A business information model approach can help organizations meet the six criteria above.

The creation and maintenance of an enterprisewide business information model can help maxed-out leaders more easily manage their data and use it to support their decision making. This model defines, synchronizes, and organizes the key business terms necessary to operate, monitor, manage, account for, evaluate, analyze, report, and forecast data across the enterprise.

In a nutshell, this resource can help to:

• Assess, define, and align how the business uses data.
• Identify how data insights are leveraged across the enterprise.
• Define a synchronized set of data dimensions and hierarchies.
• Align data across various sources.

Beyond improved decision making, better and more robust data governance can also deliver other returns on the investment. These might include increased profitability, improved customer satisfaction, and more resilience in the face of disruption.

• Increased profitability: When data is managed efficiently, businesses have a deeper understanding of budgeted costs versus actual costs, allowing them to more strategically decide where to invest and where to cut costs. It also creates better visibility into current and past losses to allow for dynamic forecasting and avoid future revenue leakage.
• Improved customer satisfaction: More accurate data means a better understanding of the demographics, needs, and preferences of businesses’ core audiences, enabling better communication and the creation of products and services better aligned to customers’ expectations.
• More resilience in the face of disruption: Having a clear view of the entirety of the business and how decisions in one part of the organization may impact the rest allows businesses to pivot quickly, when needed, to meet new market demands. This skill combined with more robust forecasting capabilities creates and fosters resilience in organizations, even in the face of significant disruption.

Though change has been unrelenting in recent months and years, the pace is unlikely to slow any time soon. The most efficient course of action for businesses focused on growth and sustainability in the long term is to augment their data and technology architectures to insulate themselves against the ebbs and flows of an unstable economy. One of the best ways to do that is to focus on designing an intentional, enterprisewide information model that supports strategic decision making, drives growth, and enables resilience.