Companies that sell third-generation reporting products and many cloud solutions providers have expanded into the domain of big data and analytics, making these technologies more affordable and accessible to small companies. Unfortunately, many small companies don’t know how to make the best use of these resources, or know how to change their operations so analytics can help their bottom line. Read about two small companies that have succeeded with big data.
SEE: 7 tools to help your company get started with big data
Two big data success stories
Outdoor venues like the Point Defiance Zoo & Aquarium in Tacoma, Washington, rely on attendance to keep the doors open, and attendance is highly dependent on weather. The zoo’s management worked with IBM and BrightStar Partners, an analytics firm, to come up with a better way of predicting outdoor zoo attendance for the purposes of budgeting and staffing. Historical attendance records for the zoo were parsed and then analyzed against years of detailed local climate data collected by the National Weather Service. This ultimately led to new insights that helped the zoo anticipate with surprising precision how many customers would show up on a given weekend. The analytics helped with staffing, predicting attendance, and launching promotions.
In Tucson, Arizona, Brian Janezic was used to going through cleaning supplies and vending machine items to determine what to order for his two self-service car wash locations. He installed sensors and collected IoT (Internet of Things) data from his drums of chemicals, which enabled him to automate the monitoring of chemical consumption and the triggering of reorder points. This saved him time and more efficiently managed costs of operation.
SEE: How Chatham Financial optimized its big data for better insights
Guidelines for small businesses with big data projects
Since most analytics end up coming from data sources that small businesses are already familiar with, the keys to success depend on identifying a tightly defined business case that is calculated to bring specific results and on not making the initial project scope too big. Also, small businesses should look to augment corporate knowledge obtained from their internal systems and offline documentation with big data insights.
In addition, small companies can avoid expensive capital investments in hardware and software, since they can check out the offerings of cloud-based big data crunchers and analytics providers.
In the cloud market, there are pay-for-use and pay-by-subscription providers that help businesses get their non-digitalized data into digital form so it can be used in analytics. Other providers collect the data and combine it with publicly available information to help the small business owner better understand the market and their customers in order to make smarter business decisions. These providers can supply the small business owner with the reporting and query tools and dashboards so they can ask their own questions of the data. Other providers, like Google Analytics, offer free web traffic monitoring tools, metrics, and traffic sources, and share data about website visitors.
Ultimately, your business case and project will dictate the types of analytics tools you will use. The tools should meet these four vetting criteria:
- the cost should be reasonable (preferably, you pay only for what you use);
- the tools should be easy and intuitive to use, with very short learning curves;
- the data that you provide to the process, along with any data provided by your vendor, should be data that you trust; and
- the solutions must enable you to meet your goals.
Using these guidelines, small businesses can have successful big data projects, and better yet, help level the playing field in today’s highly competitive marketplace.