Big data and business analytics are the some of the most important disruptive innovations of the last couple years. According to PC Mag, 2016 will see more of a shift to business-led, self-service analytics. Aggregating data successfully means you have the information about your customers and your products to continue to innovate and identify solutions with actual evidence. However, many business intelligence software companies just build dashboards without setting specific goals or applying them to your overall strategy. Here’s how to use your data in a way that isn’t overwhelming and makes sense for your business.

1. Gather requirements before gathering data.

Make sure your big data analytics (BDA) projects align with your business goals. Rather than approaching a marketing project with a tactic in mind, focus on the goal and let the goal guide your specific actions. A major misstep many companies make is believing that business intelligence (BI) software will provide the solutions to marketing problems.

A recent article in McKinsey Quarterly points out: “The power of a plan is that it provides a common language allowing senior executives, technology professionals, data scientists, and managers to discuss where the greatest returns will come from and, more important, to select the two or three places to get started.”

Once you have your requirements and your plan in place, you can begin implementing a strategy.

2. Don’t confuse BI and BDA.

BI and BDA are connected, but they don’t mean the same thing. BDA analytics should build on BI and allow you to ask the questions that will get you closer to your plan. Traditionally, BI is the component that visualizes your data. BDA is the piece that gives insight and action to your BI. These two put together allow many members of a team to get involved in data-driven decisions.

Starting small with your team is key. Stick to the plan, start with a small use case and a limited team, and make sure it’s supported by the right people.

3. Don’t overestimate your organization’s analytics maturity.

BDA is a wide-open and rapidly growing component of a business operating strategy. Not everyone will understand exactly how it works right away, and that’s okay. Data-driven decisions make sense, but they will require some changes to the management approach. Understanding where your business falls in analytics maturity can help determine where to start your business intelligence strategy.

The most crucial component of growing your analytics maturity is by communicating well and often. After you’ve implemented a strategy, your results will bring on more adopters. Once you’ve had a chance to look at your own data, you can begin to show others how it can work on a larger scale.

4. Find the right use cases.

With your plan and team in place, choosing a project that will show the maximum amount of impact will help get you the data and action you want quickly and successfully. Here are some key components to identifying a use case when you are just beginning to utilize BI and BDA:

• Data is known and understood by users
• Small variety of data—structured data is better
• Small volume of data
• Outcome is clear
• Outcome has measurable value
• Clear timeline for the project
• Users can be involved in the approach, allowing for a more agile and less traditional project management approach

Finding effective use cases can be as simple as learning how your customers shop or ways to remove inefficiencies in specific tasks in your business.

5. Trust the results.

Once you’ve received results on a use case, you may find that the outcome is different than expected. However, if you’ve received engagement from the beginning, it’s much easier to allow the data to guide results. Effective communication and engagement helps those involved in the process look objectively at the data and trust that the results are accurate. Without this communication, some users may not understand how these results could possibly be correct.

Big data and business analytics are here to stay. Because of the analytic and predictive value regarding consumer behavior, it’s in every business’s best interest to find meaningful ways to quantify data. By gathering requirements, understanding the main components of BDA and BI, working within the parameters of your organization’s analytic maturity, finding the right use cases, and trusting the results, you are well on your way to building a strong business intelligence platform.