How Small Companies Can Use Big Data To Grow And Improve

Jennifer Horowitz

Small businesses can cost-effectively analyze large data sets to improve their marketing and product quality and accelerate customer relationships. Leaders from every business sector must learn how to grasp its changes for the future as Big Data becomes the key basis of competition.

Big Data is for organizations of any size, with data management having developed into an important skill to competitively differentiate today’s market leaders from those that are no longer influential. Signals and Systems’ mid-2014 report found that the Big Data market is expected to total $76 billion by 2020, an increase of 17%.

Technically, Big Data refers to technologies and initiatives that are too massive for traditional skills, technologies, and infrastructure efficiently address.

More than 70 years ago, in 1941, the first attempt to quantify the volume of data growth known as the “information explosion” was used, according to the Oxford English Dictionary.

Big Data was initially a unique resource only for large corporations and statisticians. With the growth in the Internet, smartphones, wireless networks, sensors, social media, and other digital technologies, small businesses and companies of all sizes are now able to leverage this trend.

As Big Data grows, MSPs can even connect to SMBs in offering their services as they look for new opportunities. Markets and Markets predicts that third-party MSPs cut recurring in-house costs by 30-40% and can add as much as a 60% improvement in efficiency. Small businesses face a big problem today with finding data storage, due to the increased growth and data volume of devices.

MSPs can expand their cloud services as SMBs look for bigger and better data storage alternatives. This means new growth and partnerships for MSPs that choose to expand their suite of services.

In addition to expanding storage options, MSPs can look to analytics performance and database management. By helping small businesses better evaluate their data, SMBs can provide a streamlined recovery and backup system to ensure data is not cluttered on a user’s mobile device.

Big Data leaders and laggards

A.T. Kearney, a global management consultancy firm, and Carnegie Mellon University investigated the corporate use of Big Data in its first-ever Leadership Excellence in Analytic Practices (LEAP) July/August 2014 study. They divided companies into four categories: leaders, explorers, followers, and laggards. Here’s what the leaders were doing with Big Data.

An inclusive atmosphere: This begins with a hands-on, dynamic policy of executive sponsorship and mindshare about Big Data. This fosters team-building, cross-functional collaboration, and company-wide confidence in data-driven methodologies.

The need for speed: Leaders used approaches that focused on rapid experimentation, mobilization, and deployment. This was primarily through pilot programs and proof-of-concept modeling.

Forward-thinking: These policies bred innovation, growth, and better operational efficiency. While Big Data was used for reporting on past efforts, leaders focused on future endeavors. They evaluated risks. They studied costs and benefits and balanced the tradeoffs between them. Then they charted a course.

Building on Big Data

According to the IBM Institute for Business, 26% of companies see returns from Big Data after 6 months. 63% see returns after one year. 40% reported that they use Big Data to solve their operational challenges.

The world will become more and more reliant on data-driven metrics in the years to come, and businesses need to recognize that fact. Using the power of analytics can shift a company into high gear, while failing to do so could leave them stuck in neutral.

Want more strategies to help your business tap the power of analytics? See Top Five Big Data Challenges For CIOs.


Jennifer Horowitz

About Jennifer Horowitz

Jennifer Horowitz is a management consultant and journalist with over 15 years of experience working in the technology, financial, hospitality, real estate, healthcare, manufacturing, not for profit, and retail sectors. She specializes in the field of analytics, offering management consulting serving global clients from midsize to large-scale organizations. Within the field of analytics, she helps higher-level organizations define their metrics strategies, create concepts, define problems, conduct analysis, problem solve, and execute.