Small Business and Big Data
Living Entrepreneurship

Small Business and Big Tech

On a stormy day in September, I board the Cranberry Cove Ferry in Southwest Harbor, Maine. As the boat heaves in the fog and rain, the captain’s mate swipes my VISA card through a small device plugged into his iPhone. With one swipe and two taps, he takes my fare via Square, and then sends a return passage receipt to my phone. In those few seconds, our transaction takes place among a pitching deck in the Gulf of Maine and data servers across America.

Technology fuels small businesses such as the Cranberry Cove Ferry, even when it’s as invisible as the shoreline in a storm. Square’s service is possible only as a sequence of complex data across networks. As everything becomes connected to everything else, petabytes of data circulate in the cloud of networks and storage, interacting with millions of mobile devices and creating value in ways familiar (paying a fare) and utterly new (smart utility grids that manage power use down to the level of a dishwasher).

Big data is a shorthand term for three layered technologies: Database infrastructure, analysis software, and business-facing applications. In practice, here’s how they work for a small business using point-of-sale service such as Square or PayPal:

Infrastructure: These are the Web servers and secure storage devices that keep financial data for both business and customer. Infrastructure contains data such as the location of the store (or boat!), the items purchased, and whether a customer’s bank account or credit limit can cover the transaction. All this information is transported across networks (including cell networks), managed moment by moment to maximize efficiency.

Analysis: Data analysis software answers specific questions such as “Is this credit card active?” and, “Is this a repeat customer, and does he like special offers?”

Business-facing applications: From many transactions, this software allows the merchant to ask important marketing questions: “What is my average transaction?” “What is the price point at which a discount increases net revenue?” “What is the ideal ratio of new-to-repeat customers, given my sales patterns for one month?”

Big data makes this kind of analysis available to any size business—Square’s fees are 2.75 percent of a transaction or $275 a month, much cheaper than buying servers and IT staff to run it.

Enabling Entrepreneurs

For entrepreneurs, both the familiar and new uses of big data add value in two broadly defined categories:

Enabling technology: Startups save money and run their businesses using big-data, cloud-based applications such as Google Apps, Microsoft Office Web, and Zoho. Intuit is planning a business version of its Mint money-management service. And, services such as Google Analytics enable the best use of an entrepreneur’s website. These technologies are useful to entrepreneurs no matter what their business is.

Value-creating technology: Entrepreneurs are exploiting the capabilities of big data to create new businesses altogether. The big ideas appear in growing companies such as security startup Bromium and software-as-a-service pioneer Salesforce. Technology at these companies is paramount as a convenient product such as Salesforce requires huge data manipulation to appear simple in use.

Babson Associate Professor Salvatore Parise focuses on big data’s capability to combine social data with market and transactional data. He suggests a new wave of applications that unlock the hidden world of social data for existing businesses, creating new value. For example, “Banks could discover that a very socially active person with modest deposits is actually worth more than a wealthy but introverted depositor, because the data show the social person driving more business to the bank via her network.” A cloud-based service combining these different data sets would turn conventional wisdom on its head, creating huge value to businesses where none existed before.

The categories aren’t exclusive of each other: entrepreneurs will see abundant overlap as they use Web analytics, social data, and customer input to develop and test a new product. They might collaborate with global suppliers using free cloud-based applications, or prototype a product while soliciting input from future customers. All the generation of data, from customer purchases to Facebook-based likes, can disappear momentarily into the cloud, only to emerge from that fog with compelling new clarity.

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