4 Ways to Get Insights from Your Data
By Lauren Elmore, published in Innovation Enterprise.
Almost every executive has bought into the importance of data. Data can tell you an incredible number of things, from where your customers live and hang out, to their biggest issues with your product or service. Businesses are collecting more data than ever before. What leaders often fail to realize, however, is that front-end data collection is just the beginning.
Data is only valuable if it can be turned into insights, and this piece of the puzzle is often forgotten. It’s no surprise, then, that despite huge investments in data collection, executives frequently fail to see results from the massive amounts of data they collect.
With technology advancing at an increasingly fast rate, business leaders are going to have even more data to manage before they know it — so it’s important to understand how to make the most of that information.
Data and the IIoT
Everyone has heard of the Internet of Things, and most people think of things like smart doorbells and internet-connected voice assistants.
But there’s also the Industrial Internet of Things that applies sensors to devices, machinery, and vehicles to create more intelligent business outcomes. That could mean everything from smart rat traps that text you once the trap has been activated to machinery sensors that keep miners safe and improve productivity. As you might imagine, all that front-end data collection requires a back-end operation to process it.
If you’ve started to integrate data collection and analytics into your business, you’re on the right track — but you’re not at the finish line yet. Here are four strategies to maximize your data efforts and avoid the many common pitfalls:
1. Educate yourself
In order to avoid data pitfalls, you need to have a basic understanding of the language of your data. What do certain results mean, and how did you come to this conclusion? When it comes to translating data into insights, plenty of businesses have found that an initial assumption they made at the very beginning of the process turned out to be wrong. If you must make assumptions, be sure to verify them as soon as possible.
2. Partner with experts
The most common reason executives fail to derive much value from their data is that they don’t know what to do with it or don’t have the time to mine for insights. Working with an expert in your industry is a valuable way to get the insights you need without having to learn an entirely new field, such as data science.
3. Maintain consistency
Monitoring your data is extremely important, and nothing taints a data set faster than repeated discrepancies. Whether they occur weekly or seasonally, ignoring discrepancies can only make your data more difficult to reconcile. Keep a keen eye on what’s going into your data, especially early on in the collection process, and it will save you headaches down the road.
4. Don’t confuse correlation with causation
Data-driven insights can have a significant impact on business outcomes. That being said, when there’s a lot on the line, it’s easy to jump to conclusions that appear to make sense. Unfortunately, this behavior will cause you to overlook other important factors. Keep an open mind, and remember that correlation doesn’t necessarily mean causation.
Data is incredibly powerful, and thanks to its current and future abundance, it’s changing the way companies do business. As more and more organizations start to rely on data, their competitors will need to do the same to avoid becoming obsolete — so it’s understandable that many business leaders are collecting data at top speed.
What they need to realize, however, is that data itself won’t transform their company overnight. It takes time to collect enough data to inform decision-making, and simply collecting the data isn’t enough to produce insights. Instead, it’s cleaning and analyzing data that extracts the value. As more businesses become adept at this process, they will move to the front of their fields while competitors that are slower to evolve fall further behind.