Our lives revolve around decisions. From prioritizing budgets, to deciding who and what to say yes or no to, to choosing a future path for your company, we are bombarded with decisions both big and small.

“The daunting reality,” as Harvard Business Review puts it, “is that enormously important decisions made by intelligent, responsible people with the best information and intentions are sometimes hopelessly flawed.”

In fact, the more you work in an industry built on change the more complex and difficult your decisions become. Online, data — especially big data — has long promised to make these kinds of decisions easier. Unfortunately, it hasn’t really done that. Instead, it's taken the term "information overload" to the extreme.

At least 2.5 quintillion bytes of data is produced every day (that's 18 zeros). In 2012, the entire World Wide Web was estimated to contain approximately 5 billion gigabytes of data. By 2020, the number is expected to grow to over 400 billion gigabytes.

To solve this problem and help you make better decisions using the data, here are four simple steps to follow:

1. Define the Problem

The biggest reason people fear data is scope. With analytics for everything from websites to social media to employee time-off, simply deciding which numbers deserve attention can be daunting all by itself.

Instead of starting with data, start by clearly defining the decision you need to make. This means focusing on the problem you're trying to solve.

As fellow Inc. columnist Lolly Daskal, says, you must "gather all available information; think about the situation from all perspectives." That means you need to have a clear problem statement, which includes identifying the specific concern, the impact it is having, the consequences of not solving the problem, and the ideal goal. Here's an example.

Problem: Our social media fans are not making purchases online.

Impact: We are not getting sufficient returns from social media to justify maintaining the program.

Consequences: The social media program will be shut down.

Goal: Increase the amount of purchases made from social media customers by 10 percent to deliver a positive ROI.

2. Assess Possible Solutions

Another reason people get stuck when they're working with data is because they don't realize they don't need any one particular solution. While with the first step it's highly important to have one clear problem and one clear goal--having multiple solutions is best.

Imagine being interviewed after you've made a decision and someone asks you, "So what did you do?" This is what Don Charlton of the recruiting platform Jazz does. When you use this technique, you force yourself to think about what the possible solutions could be, and which one seems more likely to achieve the desired goal.

At this stage, it is important to keep your options open and think about all possible solutions. Brainstorm even the most far-fetched possibilities and never leave out the option of doing absolutely nothing. That may be the most beneficial choice of all.

If you were trying to increase sales from social media, as in the example above, a few of your options might be: using social media advertising, having a social media only promotion, or converting fans to email subscribers and offering deals through that method.

3. Identify Metrics

Once you have a clear view of the problem and a set of possible solutions, now it's time to bring in the data. For each of the options you listed in Step 2, identify the most suitable metrics that will best inform your choice.

For example, if we are tracking product line performance, we can use past sales of each product line, current sales of competing products against our own, and possible future trends of our market.

On the other hand, if we are trying to generate more leads, we can track the number of clickthroughs and their sources, overall traffic to our landing page, and number of signups.

If we're trying to close more online sales, we might instead look into the path buyers took to reach to the sales page, the type of items they selected, the number of processed orders, and the number of abandoned carts.

You don't need to go digging into numbers and start creating a bunch of reports and charts just yet. This is simply an exercise to help you tell what numbers might create the clearest story and help you make the most informed decision.

4. Create Visualizations

Now that you know which metrics matter, it's time to put your data to work. One of the best ways to do this, particularly when making choices, is to create visualizations. When you can see everything at glance, differences and trends become much easier to spot, like this simple coffee comparison chart from illustrator Sky Nash. This is also why Google Trends presents their data in graphs and maps, rather than a list of numbers.

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Google Goals is another stellar way to create visualizations. By setting up a series of pages, each with its own specific goal (like clickthrough, sign-up, add-to-cart, or even video play), you can easily generate visual representations that highlight what's working at each step, along with what's not.

Generating a genuine "all in one" view can be difficult, especially if your data is spread across several tools and needs to include both online and offline data.

One solution is a tool like Cyfe. Cyfe pulls together information from a host of sources--like onsite traffic and performance, social media, email, specific marketing campaigns, as well as sales and revenue--into customizable dashboards. Cyfe's customer support dashboard, for example, includes incoming customer queries, cases created and resolved, average response time, and statistics on individual and channel performance.

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On the other hand, if you only need to focus on online data, another useful tool is SumAll. Like Cyfe, SumAll gathers data from numerous online platforms and gives you options to display your data based on the specific goals you set.

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Armed with this simple process, you can make any almost any decision using data. As long as you remember to manage the data and filter what you want, instead of trying to analyze every single number, you'll be on your way to better choices in no time.