Data rules the world these days. But now that it’s handily surpassed just about every other quantifiable thing on Earth in terms of usefulness and monetary value, a single burning question remains: Just what, precisely, do we do with all of it?
Don’t be scared off by the name ” big data is every bit as useful for smaller companies as for globe-spanning corporations. As it turns out, it’s not really about how much you have, but rather how you use it. If you collect and rely on data, but you’re wondering how to make it more useful and actionable, here are a few places you can get started.
Start With a Problem That Actually Needs Solving
You don’t need to pore over a data point just because it exists. Some data just isn’t going to yield anything useful ” so you need to pick your battles. What problems are you actually trying to solve?
Perhaps the best source of this kind of structured data is the information that changes hands during customer transactions. With a little effort, you can uncover patterns you didn’t know existed, such as seasonal fluctuations and spending habits.
Operationalize Your Results
Supposing you started with a problem that needed solving and then figured out a way to collect data related to that problem, you then need a realistic picture of what each of your in-house operations will actually do with it. It sounds simple, but it can get quite complicated.
For example, if you do business in a sensitive industry like government contracting or health care, there are laws and guidelines in place to protect your clients and their information. Failing to safeguard this data will cost you money in both fines and lost reputation.
The short version is that not all departments need all your data, all at once. Consider how the data you process on a daily basis realistically has an impact on your customer service teams, your product research teams, your mobile sales teams and everything else that goes on under your roof.
Thinking through the ways in which they interact with data and with each other can yield some exciting opportunities.
Leveraging Cloud Systems
Data must be mobile ” there’s no way around it. We’re getting better and better at doing business on our own terms, and that means we’re as likely to carry out important functions from the comfort of a home office as from a building downtown. Even if you’re using big data already, you severely limit its usefulness if you can’t access it from wherever life takes you.
It’s simple: You need to be able to make business decisions from anywhere. That’s where the cloud comes in. The cloud isn’t any one thing, in fact ” it’s a technique where the software you use to interact with data is stored on each of your devices, and where changes made on one device are instantly reflected on all your others.
It’s critical for any operation which relies on teams out in the field, but it can grant mobility and newfound freedom even to relatively compact businesses.
Productivity and Automation
Finally, it’s worth thinking for a moment about how big data can positively influence your productivity and offer new ways to automate some of the repeatable and predictable processes you rely on daily.
Granted, we’re not ready to phase humans out of the equation quite yet. As business leaders always have, you need to balance the expertise of trained professionals with the convenience of cold information. So what does this all look like?
Frankly, it means having people around who can look at numbers and derive something human from them. Data science isn’t a science without data ” but it’s also not a science without human beings. Automation and machine learning let us do really convenient things like auto-tag transactions of a certain type on a balance sheet or produce forecasts for the upcoming quarter, but what are these things if not human behavior?
At the end of the day, it all comes back to people ” both their patterns and their surprises. It might sound cold, but it’s not ” big data really can help us understand each other better, whether it’s in the pursuit of more effective treatments for common illnesses or helping us produce more products more efficiently.
