Only 18 percent of small businesses and just more than half (57 percent) of mid-size companies use business intelligence and analytics solutions, according to market research firm The SMB Group.
What about the others?
Many smaller businesses are reluctant to invest in leading-edge technologies. Limited capital or the lack of the right staffperson might prompt even the most forward-thinking companies to avoid innovations or postpone such a move until they reach a certain revenue or profit goal.
It’s an erroneous notion among small business owners and decision-makers that big data is too complex or something only big companies can afford to try out. Even the name – the “big” in big data – can seem off-putting. But it’s not as tough to dive into big data as small companies might think and the payoff can be significant.
Advances in user interfaces, automation and cognitive computing are removing the barriers to adoption of big-data tools and they are now at costs that small businesses can afford. How does free sound?
Can you imagine the impact when a small-business owner is able to sort through volumes of internal and external data about his or her business and then lets any employee, in any role, to make insightful decisions and engage customers more effectively?
What if I told you that you don’t have to imagine, that tapping into critical data that could change the way your company operates for the better was as simple as a web search and costs you nothing?
Today, any employee can use analytics to make data-driven decisions that directly address his or her business problems without having to worry about the underlying technology or needing an in-house data scientist with specialty skills in analytics.
Solutions are now available (including Watson Analytics developed by my company, IBM) that are designed not only for data scientists and analysts but for every business professional who uses data.
There are extremely powerful tools that can help knowledge workers find insightful perspectives and answer a whole host of questions they might have about their area of business using natural language, just like using a search engine, but far more meaningful.
This means smaller businesses can take advantage of their speed and customer proximity and, combined with new data insights, really be game changes.
It’s been estimated that with the rapid spread of mobile devices and the “Internet of Things,” the world is generating more than 2.5 billion gigabytes of data every single day. These vast sets of data are an organization’s most precious natural resource – whether that data is structured in databases or is the kind of information that comes from blog posts, customer-support chat sessions or even social networks like Twitter.
When analytics is applied to big data, an organization can change the way it makes decisions. Business processes improve, customer engagement becomes more personalized and new markets can be created as needs emerge.
A good example of this is Tacoma, Wash.-based Point Defiance Zoo & Aquarium, a client of IBM. On a daily basis, millions of data records are generated about visitors exhibit preferences, along with significant consumer feedback generated on social channels, such as Facebook.
The zoo used big-data analytics to uncover patterns and trends in its data to help drive its ticket sales and enhance visitor experiences. As a result, Point Defiance Zoo’s online ticket sales grew more than 700 percent in one year.
This is just one example of an organization's using its data to drive decisions and dramatically increasing revenue – even thought it has fewer than 100 people and no data scientists on its payroll.
Small business owners can test out big-data analytics and see the benefits for themselves. The following steps are ways that managers can get started and reap the benefits:
1. Identify your challenges.
Understand the opportunity that big data and analytics can present for your company. Set some goals whether to save on costs, increase the return on investment, growth and expansion.
2 Get to know your data.
Start by looking at the data your organization is creating and understanding where it’s coming from, including from social networks, business activities and software applications for sales or marketing. Knowing what you have to work with is a critical step.
3. Identify the information that's most useful.
Based on the data that your organization is already generating, figure out which types will have the most impact on your business.
Consider these questions: Would mining customer sentiment on social networks help to improve product development and customer service? Can you use sales and marketing data to improve growth and revenue?
Focus on your customers. Historically, the main focus of IT has been on automating and driving cost savings in the back-end systems of record.
Today, the focus is increasingly shifting to systems of engagement. When diving into your data, think about how to drive top-line revenue growth by using data to find new customers and partners and deliver real-time value to them in unique and unexpected ways.
Choosing the right technology tailored for your organization’s needs will be crucial to your company’s big-data analytics success. There are free versions of powerful solutions available today that provide a good representation of features so you can receive a taste of what they can do. These features will often provide enough benefit to make a difference immediately.
5. Consider using the cloud.
The rise of the cloud is having a dramatic impact, making big-data analytics technologies within reach for small businesses and startups. By putting analytics in the cloud there’s minimal cost and infrastructure requirements. You can drive down costs and relay the resulting savings to product development and customer service while extracting critical insights for your business.
6. Tap the power of peers.
Communities like StartupNation or Midsize Insider are ideal forums for investigating new solutions and posing questions. They are also a great way to identify local IT services companies that have a level of expertise in analytics technologies and can work with you to apply them to your particular business need.