5 Toxic Mindsets to Avoid if You Want to Leverage Big Data
Whether your business is in health care or home financing, marketing or manufacturing, insurance or investment banking, big data is playing a huge role in your industry. If you want to leverage big data, there are a few toxic attitudes that could kill your endeavors. Here are the worst mindsets to approach big data with, and how to correct these attitudes within your organization to experience success with big data.
1. Our Company is Already too Far Behind With Big Data
You can catch up. You just have to get started.
Do you think you’re too far behind your competitors to catch up? Then, why even bother? The answer is multi-fold. First, remember the story of the tortoise and the hair — the tortoise wins the race because, though slow, he keeps at it. Your business can still see success with big data — but won’t stand much of a chance if you never get started.
Secondly, those who watch and learn from past failures and successes can delve in with a better understanding of best practices. Find out what you can about your competitors big data initiatives. What worked? What didn’t? What have they learned? You can use these answers to create a plan for success, without having to endure the pitfalls of those who went before you.
Lastly, big data isn’t going away. Avoiding the issue only puts your company even further behind. The sooner you begin a big data initiative, the sooner you’ll catch up. Data integration and data analytics tools come with some learning curves, but the challenge pays off with huge a ROI.
2. Big Data is too Expensive
This is simply a myth — with cloud service providers and a wide range of open source analytics tools, big data initiatives do not have to come with huge price tags. When it comes to hiring big data talent, there are numerous contractors and other sources to get plans off the ground and running smoothly on the cheap. The idea that even small businesses can’t afford big data is nonsense.
3. Big Data is Only for the High-Tech Companies
Big data is used in education, environmental science, farming, and casinos. Naturally, there’s a way to utilize it in your industry too.
Do you think big data is restricted to the high-tech companies in Silicone Valley? Think again. Big data is huge on the East Coast, where schools are graduating big data talent as fast as they can play “Pomp and Circumstance.” Big data initiatives are underway on Wall Street, in the Windy City, and even in unsuspecting areas of the Midwest and Pacific Northwest. Farmers use big data to find more efficient ways to grow crops and manage livestock. Manufacturing facilities use big data for everything from finding safer ways to use robotics to using less expensive packaging. Energy companies, travel agencies, the service industries, and logistics specialists (known for their slowness in adopting new technologies) all use big data.
4. We Have Plenty of Data Already
Another bad attitude involves thinking your existing data is all you need. Streams of data are constantly evolving, and all new sources of data provide a new way of analyzing, understanding, and improving methods above what is currently understood. For example, could you improve your customer experience by offering data on current weather conditions at your facility? Manufacturers use incident report data to make it safer for humans and robots to work together on assembly lines. Airlines use historical flight data to determine whether it’s safer to cancel flights. There are always new sources of data available and new ways to use the data that comes in.
5. We Need All the Data We Can Get
On the opposite end of the spectrum are companies who think that lots and lots of data equal better data. This is not necessarily true. Gather data with the idea of solving particular problems. For instance, if your operational costs are high according to industry standards, what data could help you lower costs? Is your customer base dwindling? What data could help you identify why and correct the problem? Always gather and analyze data with a particular goal. This prevents data overload, which leads to inefficiency — the exact opposite of what big data is supposed to do for you.
Start by taking advantage of the resources available to you. Study what big data has done for businesses like yours, and establish a clear set of goals to accomplish with your big data initiative. Then develop solid, consistent, straightforward plans to get from here to there.