Want to Be Better at Decision Making? Here are 5 Steps to Better Data-Driven Business Decisions You often hear entrepreneurs say, "We don't know what we don't know," when talking about deficiencies in data gathering. But when you have data in silos, it's more a case of "We don't know what we DO know."

Making sound business decisions is easier when your business has only 50 to 70 employees and a couple of projects. A small staff means you can maintain good connections with everyone, and staying in the know doesn't take much effort. A small portfolio of projects means you have total control over what is going on in each project.

That changes as the company grows. You need more data to make informed decisions, and that information is often distributed among several siloed systems. HR has a silo, IT has a silo, marketing has a silo, PMO has a silo, etc.

To achieve the hallowed goal of data-driven decision-making at scale, you need to build a data ecosystem that breaks down these silos. Centralizing and standardizing data from all these sources gives you a holistic view that improves data analysis.

This omniscience gives you the power to make decisions backed by concrete evidence, reducing risk and leading to more strategic and accurate choices.

Related: How Small Businesses Can Leverage Big Data For Big Results

The value of a data ecosystem

If you've been hesitant to commit to building a data repository, that's understandable. It can be a considerable investment of time, resources, and budget.

You know there's value in it, but you may not realize the full extent of that value. From my point of view, these are the core benefits of building a data ecosystem, which directly helps in building a robust organization:

• Enhanced Customer Understanding: A data ecosystem allows you to gather and analyze customer data from various touchpoints. This data provides a deeper understanding of customer behavior, preferences, and needs. You can then leverage these insights to personalize marketing campaigns, develop targeted products and services, and improve customer satisfaction.
• Increased Efficiency and Productivity: An AI-driven data infrastructure streamlines processes by automating tasks and eliminating manual data gathering and analysis. The employees who used to handle these tasks are free to focus on higher-level activities.
• Innovation and Growth: Data repositories foster innovation by providing a platform for collaboration and knowledge sharing. By accessing diverse data sets and insights from other participants, you can identify new opportunities, develop data-driven products and services, and hone your business's competitive edge.
• Risk Management: Improved data analysis helps identify and mitigate risks proactively by providing a broader view of market trends, customer sentiment, and potential disruptions. It gives you a leg up on addressing risks and developing contingency plans.

To build a scalable data ecosystem that delivers these benefits, focus on the following five core areas.

Related: 3 Reasons Why You Need Data To Scale Your Company

1. Centralize data for accessibility

When you build a puzzle, you first dump all the pieces on the table and flip them face up. Then, you can start analyzing them to find the edges, fit pieces together, and complete the puzzle to see the picture it makes.

You don't put all the edge pieces in one cup, the blue pieces in another, the red pieces in a third, and so on. Why would you? That would make it harder to see how the pieces connect.

Likewise, having data in silos prevents you from seeing connections. Centralizing your data enhances its accessibility to stakeholders, reduces data silos and enables consistent data analysis across the organization.

To facilitate this level of comprehensive data access, collect and integrate data from various business operations (such as HR, project management, and code repositories) into a data lake. You can use services like AWS, Google Cloud or Azure to create robust, secure and scalable data lakes.

2. Leverage technology for data integration

Once you have a centralized data repository, you need a scalable process that keeps the data timely and accurate. You'll quickly find the manual processes you've been using aren't up to the task.

As more and more data floods into your business, automation becomes key. APIs and webhooks can automate the data ingestion and integration process, pulling data from diverse systems into your data lake.

3. Use advanced analytics tools

Visualizing and analyzing this tidal wave of data requires advanced business intelligence (BI) and analytics tools like Tableau, Power BI or custom dashboards developed on platforms like Shiny, Apache Superset or Dash.

These tools generate real-time insights and forecasts that support strategic decision-making. This might include analyzing project timelines, workforce productivity or software development cycles.

4. Foster a data-driven culture

Once you have the technology in place, the next step is to create a data-driven culture within your organization. Invest in training programs to enhance data literacy among employees. Data literacy empowers team members to understand and utilize data effectively in their daily decision-making processes.

Take steps to ensure widespread access to data and analytics tools across the organization. This inclusivity encourages data-driven decisions at all levels.

Related: This Is How You Can Build A Successful Data-driven Business

5. Maintain data governance and compliance

Many laws regulate the kinds of data you can collect, how it can be used and how it must be protected. Noncompliance with these laws can result in steep fines, not to mention the costs of mitigating the damage should you be hit with a data breach.

Develop and enforce a data governance policy to protect your business and maintain the integrity and security of your data. This policy describes how your company uses and manages its data, who can access data and how it can be used. It also establishes rules to help safeguard data, defines the roles and responsibilities of data governance officers, and sets standards for data security and quality.

Your data governance officers should regularly review legal and regulatory requirements related to data privacy and security, especially in different geographical jurisdictions. Regulations change, and there are many of them to keep up with.

Related: How Data-Driven Marketing Strategies Help You Achieve Growth

Business, know thyself

You often hear entrepreneurs say, "We don't know what we don't know," when talking about deficiencies in data gathering. But when you have data in silos, it's more a case of "We don't know what we DO know." The information is there, but you're just not able to put all the puzzle pieces on the table.

Focusing on these strategic areas, however, can help you build an effective data ecosystem that facilitates informed decision-making as your business scales. This leads to improved operational efficiencies, enhanced strategic planning, and a competitive edge in the marketplace.