Three Reasons Why Midmarket Companies Need to Embrace Big Data … or Get Left Behind

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By Joanna Schloss, Dell Software

On the surface, big data and the midmarket seem an unlikely match. After all, the industry hype would have you believe that the key word in the phrase “big data” is big, with the term generally understood as a reference to datasets so large and complex that they cannot be managed within the confines of traditional IT systems.

Against this backdrop, it would be perfectly understandable if most midmarket organizations adopted the mindset that big data is a big company problem. It would be equally understandable if those same midmarket organizations were of the opinion that the many opportunities for operational improvement that come from better analysis of data and information are likewise reserved for those in the enterprise.

Understandable, but completely wrong.

For in the world that exists outside of the big data hype-cycle – the one in which real-world companies live and do business – midmarket organizations are fast debunking the myth that big data is the sole domain of big companies. On the contrary, many midmarket organizations are aggressively embracing big data projects. (In fact, a recent survey from Competitive Edge Research reports indicates that more than 40 percent of midmarket companies are already in flight with an existing big data project.) What that means is that if your midmarket company isn’t one of them, then you’re falling behind, and perhaps more quickly and in more ways than you might think.

Data Analysis as Table Stakes

The time is now for midmarket organizations to realize the potential that data-driven management holds. Your tendency might be to think of data analysis as something that puts (or would put) your business on the cutting edge. You might think of analytics as a way of differentiating yourself from your key competitors. But the reality is that the window to be among the first to embrace the benefits of data analysis is rapidly closing. If we’re not already there, then we’re just around the corner from the day when the use of data analytics will become a business necessity. As more mid-sized companies embrace the need for data-driven management, data analysis as a competitive differentiator will soon give way to data analysis as a standard operating practice – one required to remain viable and competitive in just about any marketplace.

But it’s not just the fact that some of your competitors are embracing big data initiatives that should concern you. Rather, it’s the benefits that they’re reaping – and more importantly, that you’re not reaping – that pose the biggest threat to your business. By being proactive with their efforts to better analyze data and information, chances are your competitors are making smarter, faster decisions then you are, identifying new business opportunities more quickly than you are, and improving the quality of their products more consistently than you are. It doesn’t take a data scientist to figure out that this is a problem, one your business needs to address quickly in order to avoid being outmoded by the competition. In the modern data-driven economy, every organization, regardless of size, scope or vertical, needs to be leveraging data to make better business decisions.

Here are three tips midmarket organizations can follow to get started down that path:

  1. Forget big data -I know what you’re thinking: We just got done discussing how aggressively your competitors in the midmarket are embracing big data initiatives, and now you’re telling me to forget big data? In a manner of speaking, yes. “Big” is a relative term. Being an enterprise organization with large, complex data sets is not a prerequisite to benefiting from a data-driven mindset. When organizations of any size focus on improving the quality of their business processes by becoming more analytical and data-driven, the potential benefits are limitless. So rather than fixating on “big” data, instead focus better leveraging your organization’s data and information in order to make smarter, more informed decisions. Adopting this new mindset is your first step on the path to big data success, and your data doesn’t have to be large, nor does it have to be complex, in order for you to take it.
  2. Build executive support by starting with a business question - One of the key differences between midmarket organizations and their larger, enterprise counterparts is the proximity of top-level executives to any and all company projects. If you’re going to get access to the right data, as well as to the budget and employee resources you’ll need to succeed with a data analysis project, you’re going to need the support of your company’s top executives. The way to get it is to ensure that your project is driven by a specific business question, one to which finding an answer would clearly benefit the company. Remember, big data is a business challenge first, and a technology challenge second. Don’t concern yourself with putting the right technologies into place until you’ve clearly outlined the question you’re trying to answer with those technologies, and until you’ve gotten your top-level stakeholders to agree on the importance of finding that answer to that question.
  3.  Drive collaboration between IT and lines of business -When it comes to the critical role collaboration between IT and line of business plays in the success or failure of big data initiatives, the midmarket is no exception. In aforementioned Competitive Edge survey, strong collaboration between IT and line of business was the most often cited prerequisite of midmarket project success. Strong collaboration ensures that objectives are clear, proper governance is maintained, and the right data is made available to the right people at the right time. Success usually follows quickly. 

When all is said and done, the most important thing to understand about “big data” is that the key word isn’t big, it’s data.

With the right approach, any organization can benefit from better analysis of data. Many midmarket companies have already figured this out. It’s time for yours to follow suit.     

About the author

Joanna Schloss, Business Intelligence and Analytics Evangelist, Dell Software, is a subject matter expert in the Dell Center of Excellence specializing in data and information management. Her areas of expertise include big data analytics, business intelligence, business analytics, and data warehousing.