Big Data Success: 10 Tips for SMEs
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The last couple of years have seen Big Data filter down from the enterprise into the land of small and mid-sized enterprises (SMEs). In fact, recent research from Quinstreet Enterprise (the owner of this site) shows that midsize companies currently have more Big Data deployments than their larger competitors. Similarly, research from Dell found that smaller companies are actively involved in Big Data projects.
“Big Data is a hot phrase these days, but the key for SMEs is that they should be using data in new ways that are appropriate for their business, whether it's ‘big' or not,” said Chad Carson, former Microsoft and Yahoo executive and now the co-founder and vice president Product at Pepperdata, a company whose software optimizes the popular Big Data software framework Hadoop. “There's a ton of untapped potential for most businesses in acquiring and using data about their customers and suppliers, and sometimes their products themselves.”
Like everything else, there is a right and wrong way to go about it. Here are 10 pointers for SMEs to bear in mind when considering or implementing Big Data.
Do Not Dismiss Big Data
Few businesses these days are in a position where they can smugly claim they understand their market, can assert total dominance within it, and are not operating in an area where they have to deal with price undercutting or a whole new band of startups offering a better/faster/cheaper way of doing business. As this has become the norm in most segments, Laurie McCabe, an analyst with SMB Group, stressed that even small businesses should consider Big Data, as it is all about using your data in a smarter way.
“Small businesses should possess the ability to get their arms around data and be able to put it into action for successful business outcomes,” said McCabe. “There are blind spots in every business; Big Data analytics can help you known them and so make better decisions.”
Know When You Need Big Data
Some businesses might balk at the idea of Big Data adoption due to concerns about the size of their company. But Jim Bell, Head of Marketing, TIBCO Jaspersoft, believes the decision is less about the size of the company and more about Big Data's place in overall strategy.
“Small or mid-sized companies that rely on machine-generated data, customer sentiment or mass personalization to drive competitive advantage should apply Big Data solutions,” said Bell. “Larger companies that compete on less data-driven competitive advantage quality might not have as much of a need for it.”
Start Simple
OK, most businesses can recognize they need to be able to make more informed choices. But they are faced with a mountain of unknowns – not just the sheer volume of the data itself, but more basic questions like where the data is located, who in the company needs it, and what they are missing in terms of technology to begin to make it actionable.
That’s where it can go off the rails for SMEs. They find out about dozens of possible Big Data and analytics tools they could use and lose interest fast due to the hefty price tag, the number of personnel needed to implement it or the length of time it will take to deploy the systems.
McCabe’s advice, therefore, is to keep it really simple. Even baby steps can make a difference.
“Some firms might already have plenty of data available in a QuickBooks Online application, for example,” she said. “It has a trending tool that comes with the product where you can benchmark your own operation against similar businesses.”
Look for Embedded Analytics Opportunities
Another easy way to get started is by using Google Analytics on your website, said McCabe, or other analytics applications that may already be embedded within the tools you have. Increasingly, analytics is moving from an additional tool you purchase to one that is included within well-known software packages like QuickBooks and Microsoft Office.
Consider the Cloud
Starting simple might get you a better handle on who is visiting your website, how sales trends are changing, or how you measure up compared to similar businesses. But it only goes so far. If you need to graduate up into more sophisticated Big Data analytics, perhaps the cloud is the next place to go. You don’t need to buy any software or hardware and only have to pay for what you use.
“If you get to the point where you want to know such matters as what customers are saying about you on social media, the cloud is an option,” said McCabe. “There are plenty of good cloud-based tools, so why install them yourself?”
Don’t Lose Big Data Ground
If an SME holds off on implementing Big Data, perhaps due to seeing no immediate necessity, that decision could come back to bite them, Carson believes. “One of their competitors is going to, and if they don't, they'll lose ground relative to the competition as well as losing out on the business gains from using all of their data,” he said.
Buy, Don't Build
For someone who is clearly a Hadoop advocate and who works at a Hadoop-centric company, Carson has surprising advice for small businesses: Don’t use Hadoop. Instead of trying to build your Big Data system, he suggested taking advantage of one of the many software-as-a-service options on the market. In particular, look for apps designed for a specific vertical market.
“Vendors have spent years developing vertical-specific online services and tools to help their customers make the most of their data, which means they're ready to use and already designed to help specific kinds of businesses,” said Carson.
Define Big Data Use Case
One way to reduce the investment in time, money or personnel (even if using a cloud provider), said Bell, is to apply Big Data to specific use cases. That can keep costs way down as you focus your efforts in one area or one initiative rather than trying to store and analyze everything. “This can be much more affordable than gathering a bunch of data and then trying to find trends and take action,” said Bell.
Look to Big Data Leaders
Ray Kingman, CEO of Semcasting, advised companies to follow Big Data leaders rather than working it all out on their own.
“Big consumer-facing retailers, financial services organizations and some technology-driven businesses are embracing the analytic side and establishing some baseline performance and ROI expectations,” said Kingman. “These companies are defining better tools sets, taking the rocket science out of the analytics and turning it into business capability rather than a set of tools.”
Leaders are also finding ways to tap into any and all Big Data sources internally and externally. Therefore, it makes sense to let them do the heavy lifting and then use their approaches to investigate ways to derive useful intelligence from the data and tie it back to various business models.
“At that point, Big Data tools will be available beyond the lab and will finds their way into the workflow of product development, marketing and the sales processes of the mid-market,” said Kingman. “I suspect it is likely that the Big Data collection phase will shortly become commoditized, and it is possible that portions of the analytics could follow and become (at least in part) off-the-shelf products.”
Know When to Take It to Next Level
But there may come a point where the price tag for cloud services, or the degree of customization you require, means that a highly focused or cloud-only approach becomes too restrictive.
“SMBs should keep using more and more applications/services that are tailored for their business (and their supporting departments, like HR and IT). Then start exploring other, more custom, uses of their data,” said Carson. “At that point it might be time to start thinking about building their own Hadoop cluster and hiring people to apply it to improve their business even further.”
Drew Robb is a freelance writer specializing in technology and engineering. Currently living in Florida, he is originally from Scotland, where he received a degree in geology and geography from the University of Strathclyde. He is the author of Server Disk Management in a Windows Environment (CRC Press).
Drew Robb is a writer who has been writing about IT, engineering, and other topics. Originating from Scotland, he currently resides in Florida. Highly skilled in rapid prototyping innovative and reliable systems. He has been an editor and professional writer full-time for more than 20 years. He works as a freelancer at Enterprise Apps Today, CIO Insight and other IT publications. He is also an editor-in chief of an international engineering journal. He enjoys solving data problems and learning abstractions that will allow for better infrastructure.
