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Data Is Waste. Only Information Matters.

byMarcus Rabe|Nov. 28, 2023

If you run across the number 82, what does it mean? By itself, not much. It’s just a data point. But when you surround it with context, that data point is now valuable information that you can use to make smart business decisions. Let’s say your company sold 82 more high-end consulting packages this year vs. last year. OK, that sounds like a good thing. But we’re still missing some context. How many packages do you sell in a normal year? If it’s 40, then your additional 82 could indicate a transformational amount of revenue. If your sales last year were closer to 1,000, and you set a goal to sell an additional 100 this year, then your 82 additional sales is more of a warning than a celebration. What started as a fairly meaningless metric (82 additional sales) became more valuable with each piece of context added.

Understanding the distinction between data and actionable information is essential. While one depends on the other, they are not the same. In order for data to do more than just take up space on a server, it needs to be analyzed and presented as information, which can then be turned into actionable insights. That’s where the business value lies.

Small Business Data Challenges

You’ve probably heard from many sources that data is incredibly valuable. In fact, a recent article in The Economist described data as the world's most valuable resource. It’s been called the planet’s new crude oil (a more apt comparison, perhaps, since oil is a raw material that becomes much more valuable after refinement). No matter how much it’s praised, though, the reality for many small businesses is that the data is there, but the resources to capture the value within it are not.

If your business has been around for a while, you might be sitting on a decade’s worth of data. You know it’s there, and you want to use it, but you lack the time, budget, or resources to turn it into valuable information. Or, it’s even closer at hand but still frustratingly out of reach — let’s say you have the resources to extract some value from it, but you lack the in-house expertise to know where to even start. Meanwhile, you’re watching the competition seemingly use their analytics results to soar past you.

To make things more complicated, embarking on a new data initiative with your company can create more problems than it solves, if it’s not carefully planned and communicated. Employees can get rightfully anxious about their job security when managers start talking about collecting data for analysis. Care must be taken to reassure members of your team about their job security, and people can get downright resentful if they’re suddenly tasked with new and unfamiliar technical duties on top of their current workload. Without an in-house IT department, it’s hard to assess the quality and availability of your data. If your team uses many disparate platforms to manage their work, data is spread across platforms, which makes it that much harder to know what you’re actually working with.

Advice For Small Business Owners

Because there are so many moving parts, it’s crucial to take a structured approach to data analysis. To begin, you need to start at the end.

Many small businesses – and even large ones – make a mistake by putting new tech tools front and center and working from there. Their business objective seems to be, “Everyone else is using a chatbot, so we need to do that, too.”

Instead, the first and most important step is to define the business problem at hand. Before you even look at one piece of raw data, ask yourself: What do I want this initiative to accomplish? How will I know that I’ve succeeded? Setting measurable goals when answering these questions is critical to measuring success at the end of the project.

From there, you can start working backwards to find the tactics and tools, along with the correct data to analyze, so that everything works together toward solving your problem. (By taking this approach, you may find that despite chatbots being trendy, they won’t help you at all.)

When you’re choosing tools, try to choose as few as possible. One of the most frustrating challenges for any business is having many different platforms that don’t speak to one another. Using multiple tools can lead to wastefully redundant data entry, and a lack of normalization between data on different platforms can skew your results.

One more word of advice: it’s important to include your employees from the very start. They may take on many roles, but up until now none of those likely required any IT knowledge. This doesn’t necessarily mean allowing your staff to have input on every decision, but it’s essential that you don’t keep them in the dark. No one likes surprises, especially ones that involve their jobs and new tech.

One good way to ensure buy-in is to take baby steps. Trying too many new things all at once can be overwhelming, and your staff could just reject the idea wholesale. Instead, take a slow-but-steady approach of continuous improvement.

Choosing the Right Partner

Adding data analysis to your workload can feel insurmountable when you’re already overworked, especially if collecting and analyzing data isn’t part of your company’s core competency. One way to ease that stress is to allow a trusted partner to take on all the heavy lifting. An outside company that can serve as your one-stop shop can be a lifesaver, allowing you to focus on the aspects of your business that might otherwise get pushed to the back burner. It’s also a lot easier on your mental load than trying to manage 10 freelancers to handle one project each.

As your data science partners, ISC will work alongside you to help you make sense of your business data. We’re experts at managing projects, choosing smart tools, and showing you how you can use your results to effectively solve your business problems. Drop us a line to learn more.

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If you have a problem that can be solved with data, we can help. Our problem-solving approach works across company sizes and industries. Contact us to set up a free consultation.

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