3 ways to find value in your unstructured data

Big data is crashing through the business world like a tidal wave, doubling in size every two years. While some companies are successfully riding the wave, others are either hesitant to get their toes wet, or they’re drowning in their attempts to do so.

The sheer size of the data boom is daunting, and the most common issue plaguing enterprises is that they only have the ability to immediately analyze 20 percent of the data they generate. This easy-to-evaluate information is known as “structured” data — consistent, well-formatted, tagged metrics that are typically derived by technology (IoT sensors, inventory reports, sales numbers, and machine outputs).

The other 80% is “unstructured” data. Insights from this information cannot be immediately gleaned upon first glance. Commonly created by humans, this data comes in all shapes and sizes via sources like emails, customer reviews, and comments on social media sites.

While structured data explains what is happening or going to happen, unstructured data explains why something is happening or will happen in the future. There’s a world of opportunity in unstructured data, and the enterprises that go the extra mile in analyzing it will gain a huge advantage over their competitors.

Unearthing the Insights of Unstructured Data

Imagine that your company has several retail locations, and your sales are dropping at each one. To find the source of the issue — the “why” — you hire a team of consultants to come in, crunch your numbers, analyze your unstructured data, and come back with a list of recommendations. This process can take many months, and by the time you’re prepared to tackle the issue, you’ve already lost tons of revenue and face an even bigger uphill battle.

This doesn’t have to be the case anymore. With the right approach, companies can now easily build their own strategies around unstructured data and quickly learn the “why” behind their performances in a matter of days.

When it comes to user feedback, for example, there are several new tools on the market that allow businesses to analyze how customers feel about their brands or products in real time. This technology can also comb through social media archives to analyze a company’s track record of customer feedback, providing a holistic past- and present-day view into this unstructured data. And further, the tools can use location proximity features to report all of this information on a per-store basis, allowing decision makers to know exactly where the problem exists, why it’s happening, and where they need to go to fix it.

Ultimately, building an analytics strategy around unstructured data puts actionable information into the hands of business leaders in a timely fashion, enabling quick, informed decisions, thus providing a competitive edge.

Here are three things to keep in mind when building your strategy:

1. Start with a specific question

From day one, you need to know what you’re looking for and why it’s valuable to your business. For example, don’t just ask your IT department to analyze product reviews. Instead, specifically ask about the ratio of positive reviews to negative reviews (or about the most unpopular product features).

Giving specific directions about the insights you want will help your technical team find the best solutions.

2. Expect pushback from your IT group

Due to the way traditional IT groups are structured, there’s a good chance you won’t have the right skill sets in-house to address the new way you want to handle unstructured data. That’s where the pushback will come from, and you’ll need a strategy to address that.

An industry expert consultancy can help with the initial strategy and early adoption phases, and eventually you can retrain or restructure your IT group to address the change. It’s unlikely that the transition will be smooth and seamless, so prepare yourself and try to make it as easy as possible.

3. Keep your entire enterprise in mind

Siloed data is one of the biggest data-related problems modern enterprises face, and business units often make the mistake of building their strategies independent of the rest of their enterprises. Instead, create a well-rounded data strategy that allows and encourages all business units to share and capitalize on each other’s efforts.