In this age of Big Data, don’t let your small business data go to waste

There has been a good deal of press about Big Data, including a number of recent articles about related tools for small business. The basic idea is that companies can cost-effectively tap disparate sources of data and combine them in new ways to improve decision-making and performance.

Is there hype here? Of course, but that doesn’t mean it’s all sizzle and no steak. In fact, that steak might just be the lunch that savvy companies are snatching from the jaws of their less alert competitors. So, what’s a small business to do? Regardless the size of your datasets—big or small—there is more pressure than ever to use data-driven tools. Here are some specifics that may deserve your attention.

1. Use your current data and analysis tools to identify and implement improvements. Most small (and large) businesses collect data that isn’t used much if at all. Even if it doesn’t qualify as Big Data, put it to work!

How long is your sales cycle and where are the rough spots? What are the characteristics of your best customers? If you don’t know the answers, it’s likely that you are missing something important. Some analysis doesn’t even require a computer, as in this terrific example from my colleague Laurie Breitner.

Do you have a way to contact customers with information that is relevant to them, or to ask them to share their opinions? If not, see item 2 below.

Do your inventory, maintenance, or production systems allow you to spot inefficiencies or intermittent problems? Are you using the data in each to find points at which difficulties occur routinely and unnecessarily? For example, perhaps one or two machines breakdown disproportionately or one vehicle in your fleet is particularly trouble prone? These costly problems can be hard to spot over short periods; analyze data over time to identify opportunities for profit improvement.

2. Explore innovative data-driven tools to help you attract new customers and reach out to existing customers more effectively. Add new tools to more selectively contact, cultivate, and survey customers or potential customers.

This NYTimes.com article profiles businesses that combine free tools such as Google Analytics with specialized tools built into software they use to improve their sales operations. It also points out the value of new generation of loyalty programs, as does this article.

Don’t overlook opportunities to combine existing data in new ways that enable more powerful insights. For example, do your sales, customer service and manufacturing systems store customer information in different formats that don’t match up? What could you learn if they did?

3. Scan for potentially disruptive technologies that could change the dynamics of your industry and weaken your advantages. Build awareness of Big Data and data mining into routine scanning of your competitive landscape and market trends.

The rise of Amazon and the decline of independent booksellers is a cautionary example. As Viktor Mayer-Schöenberger and Kenneth Cukier describe in Big Data: A Revolution That Will Transform How We Live, Work, and Think, Amazon’s successful replacement of person-to-person recommendations with a recommendation engine allowed the Internet retailer to cost-effectively match what had long been held to be the sole purview of independent booksellers—personalized recommendations. Small business owners, beware. This example calls into question the competitive advantage of the personal touch—always thought to be one element that big business could not hope to match except in luxury markets. (Here’s a BookTV discussion with the authors of Big Data.)

4. Be alert to new opportunities to build tools for existing customers or new markets. Big Data can create opportunities—some involve helping your customers have a better experience and others may repurpose data or analyze it differently to build entirely new businesses.

Mayer-Schöenberger and Cukier (pages126-131) suggest three categories: organizations that own data, organizations able to carry out complex analyses on the data, and organizations with a “big-data mindset” that enables them to spot opportunities before others do. One company that fits into the latter two categories is Innovation Accelerator, which is developing novel tools to explore existing databases for overlooked solutions to intractable R&D problems (Full disclosure: I am founder Anthony McCaffrey’s NSF I-Corps business mentor).

5. Don’t be wowed or intimidated by Big Data. There is no substitute for good judgment and business acumen. For example: before you can identify your best customers, you need to define “best.”

As Shevtank Shah, Andrew Horne, and Jaime Capellá point out in their Harvard Business Review “Idea Watch” article (April 2012, pages 23-25), “For all the breathless promises about the return on investment in Big Data…companies face a challenge. Investment in analytics can be useless, even harmful, unless employees can incorporate that data into complex decision making.” They go on to say that “Informed skeptics” are needed to provide balance. Bryan Burkhart’s April 4April 11 and April 16 NYTimes.com “You’re the Boss” blog posts describe how one company used both in its decisions regarding a data-driven initiative (be sure to read all three or you will miss the point).

Are you convinced that data should be a bigger part of your tool kit? If your team typically relies on intuition or rules of thumb to make decisions, start slowly and be patient. Taking greater advantage of data-driven tools will require changing decision-making habits, which takes time and training. You may want to pick one of the first four categories to get started. Find some low hanging fruit to generate quick wins and build employee enthusiasm.

How is Big Data changing your small business? Do you see mostly opportunities or threats on the horizon? I’d love to hear your thoughts.

Additional articles:

“3 Steps To Incorporate Big Data Into Your Small Business” viewed May 13, 2013.

“Unlocking the Big Data Goldmine for SMBs” viewed May 13, 2013.

“Why ‘lean’ data beats big data” viewed May 13, 2013.

Thanks to Laurie Breitner for her help with this post.

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Karen Utgoff, principal of Karen Lauter Utgoff Consulting, is a market-oriented business strategist based in Amherst, MA. Learn more at http://www.utgoff.com.

© Karen Lauter Utgoff Consulting 2013. All rights reserved.

3 comments

  1. Trish says:

    Great post. Here's the updated link to the article referenced here with "It also points out the value of new generation of loyalty programs, as does this article. http://www.inc.com/victor-ho/why-small-data-may-b

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