Over the past several years, the emergence of big data as the primary driver of efficiency and growth in multiple industries have created a boom in the data science industry that’s still going strong. That shouldn’t be a surprise, as the phenomenal success of data-driven businesses like Amazon, Google, and Facebook has given every business organization on Earth good cause to investigate the ways that data collection and analysis could supercharge their bottom line.

On the whole, the trend has been positive. It’s created a whole new kind of products and services and helped countless businesses remain competitive in challenging business environments. At the same time, however, the mad rush to incorporate data into every business process has seen some failures, too. According to recent research on the subject, only 2% of businesses making significant investments into sales and marketing analytics say that their efforts are having a broad and positive impact.

That disconnect between the potential of big data and the actual results, it’s generating for businesses is one that bears some scrutiny by business leaders charged with creating a data strategy for their company. Since it’s very easy to find countless sources of information regarding why big data is a must for today’s businesses, here are the four reasons why businesses should take a more measured approach toward making big data the centerpiece of their strategic plans.

With Big Data Comes Big Responsibility


The first and most pressing reason that businesses should think very carefully about how they plan to ramp up data collection and analysis is the fact that collecting and storing vast amounts of data cost money and create significant liability issues. All one need do is to look at what’s happening to Google and Facebook within the EU now that strict new data privacy laws have gone into effect. Those developments should serve as a cautionary tale for any business leader considering a move toward big data. While the aforementioned companies are able to absorb the costs associated with data protection lapses, it would be a death blow for most others. The bottom line is, a simple cost/benefit analysis may reveal that for some companies, big data’s just not worth the risk.

Integrating Big Data Requires Cultural Upheaval

For established companies, making major changes to business processes and the underlying culture that supports them is not a task to be undertaken lightly. It’s the kind of thing that requires time, effort, and most of all, employee buy-in. Getting it wrong could upset the balance of the whole the organization, but it’s still a prerequisite for almost every company to be successful at integrating big data into their decision making processes. The reason is that most of the benefits derived from big data come from its use as the underpinnings of evidence-based management. For companies filled with managers that spent whole careers relying on intuition and instinct, learning to manage through data analysis isn’t always a natural fit – but if they can’t make the transition, big data investments will go to waste.

It’s Difficult to Assemble a Skilled Data Team


These days, with every company looking for experts in the field of data science, it’s no small task to find and recruit the right people to run a fledgling analytics operation. That leaves today’s business with two choices: resign themselves to paying some exorbitant salaries to lure experienced data scientists onto their team, or turn to lower-skilled staff and finance their continuing education. While that second option is more feasible today with accredited institutions like JCU Online providing comprehensive big data training to learners all over the world, it also means introducing a significant wait time into the business’s big data plans. Even then, with the market being as competitive as it is, there’s not even a guarantee that your newly-minted analytics staff will stay around long enough to guarantee an ROI.

In Big Data, Failure is an Option

For most companies, strategic decisions are all about calculating the odds that a given investment or risk will pay off in better outcomes for the business. That’s one of the major reasons companies are so keen to explore the possibilities of big data; they’re lured by stories of unlocked potential and untapped resources. What many don’t realize, however, is that big data is also known for another outcome: failure. In fact, Gartner analysts estimate that as many as 85% of big data projects fail to meet their objectives, which all but guarantees that any business with a big data operation will suffer a high degree of negative outcomes. If the benefits of the successes can overcome that astronomical failure rate, big data is worth the risk. If not, it could be a better option to invest in other strategies.

Choose Wisely


The pitfalls of big data listed here aren’t the end-all-be-all of the subject. Some simple research can highlight how valuable a successful big data investment can be to a business, given the right circumstances. The point is, there’s plenty of reasons for businesses to tread carefully when deciding whether or not to go big on big data. If there’s a real and justified business use case for it that’s identified in clear terms beforehand, big data can revolutionize a business. If not, it can end up a costly drain on the bottom line – and one that could have been avoided at that.