“If a technological feat is possible, man will do it. Almost as if it’s wired
into the core of our being.” (Motoko Kusanagi, Ghost in the Shell)
When introduced to the market, complex technological innovations like data analytics programs tend to be expensive. In the technology adoption life cycle, “innovators” are the first to buy into tech, mainly because of their intense interest in the field in which the innovation was developed. They don’t mind the expense since they often peg it as the price of the prestige of being the first to have it. Next come the “early adopters,” who get wind of what the innovators are doing, see the value in the tech, and follow suit to maintain their status as trendsetters.
Large enterprises tend to fall under the “early majority,” a category composed of parties that are receptive to new ideas, but let the innovators and early adopters bear the brunt of the risk of the tech failing to catch on. But as more entities adopt the innovation, the more its price goes down, making it possible for the “late majority” to afford.
With regard to data analytics solutions in particular, the tech is ripe for adoption by the late majority. Major corporations have benefited from it for quite some time now, and the price has gone down far enough for small- and medium-sized businesses (SMBs) to take advantage of it as well. But more than just being something that’s merely nice to have, data analytics is fast becoming a business necessity.
What is data analytics?
According to Investopedia, data analytics is the “science of analyzing raw data in order to make conclusions about that information.” These conclusions are arrived at via automated processes and are delivered in a form that’s fit for human consumption.
What makes data analytics valuable?
In a nutshell, processing speed. Prior to using data analytics programs, humans had to do the processing by hand, on spreadsheets, or other software. Human data processors tend to take time and run the risk of producing conclusions that are outdated or inaccurate by the time these are submitted. With data analytics programs, firms get to act upon data more quickly than they ever had before.
Manufacturers use data analytics to identify production bottlenecks and optimize machine output. eCommerce websites use it to determine the best products to display to customers, and online gaming companies use it to time challenges and rewards to maximize the time that the majority of its players play their games.
Doesn’t data analytics require a lot of computing power and storage?
Yes, but with computing and storage resources readily (and affordably) available in the cloud, setting up data analytics solutions is feasible even for SMBs.
I’m still not convinced. Why do I need it for my small business again?
Here’s the thing: there’s data to be gathered everywhere. You can attach sensors to track anything from the heat a machine produces to foot traffic in shops. Every customer interaction produces data, so if you have thousands of customers, then you have a gold mine of market insights — but only if you’re actually able to extract it in a timely fashion.
Imagine two rival manufacturers, but one invests in new machines to produce output faster and with greater quality. It’s the same way with data analytics, but with actionable insights rather than physical goods. It increases your awareness of opportunities and threats, allowing you to know when to pivot and when to push the pedal toward growth.
If you’re dreaming about growing your business, then let data lead the way. Companies in Kansas City partner with Umbrella so that they can leverage new tech such as data analytics. To learn more about how we can help you use IT to your advantage, download our eBook today.