Is ‘Big’ Data only for ‘Big’ Companies?
Is ‘big data’ only for ‘big’ companies? What about the small and medium enterprise organizations? SME’s, are they ready to embrace Big Data revolution? This was the question posted by one of our readers in the previous blog.
So much of big data discussion is focused on ‘big’ in volume which has SME ignoring Big Data and prevented SME to embark on the potential opportunity Big Data will provide to the organization. SME should look at Big data more than just a buzz word or an enterprise and global trend. Rather Big data should be used as a strategic technique to identify trends, patterns, enabling decision making process and to gain a competitive advantage in the market.
The concept of Big Data is to basically combine data from various sources where they are in their ‘silo’, combined together to make it work effectively work for the productivity and efficiency of business on their business decisions and directions.
How Big is Big?
First, let us help to address, how big of a data is suitable and required for SME?
With the volume, velocity and variety of information readily available across the globe, gathering, processing, analyzing and making meaningful decisions are the real questions that we should be focusing on.
SME can start with just a small dataset from the current CRM tool, Emails marking, Social media marketing, posts made on social media (ratings, text, image and video), data search engines (e.g: google), credit card payment systems, Phone calls, mobile applications for texting, transfer of images, videos and etc plays vital parts in the variety of data used by Big Data. The insights from the above can provide a good starting point and a much-needed business insight.
Instead of organization investing in an investment heavy enterprise wide big data solution, organizations can use current data and identify the correlation and regression between marketing campaigns, social media marketing, seasonal trends which contribute to sales, for example.
Organizations could also focus on the digital footprints as opportunities that potential customers leave behind in their search platforms or social media platforms, for enabled decision making.
Tools, techniques and algorithms used for large enterprise corporate organizations are no different to SME.
Various scholars identify ‘big data’ as the “next big thing in innovation”; “the fourth paradigm of science”; “the next frontier for innovation, competition, and productivity”; “the next management revolution”; and that “big data is bringing a revolution in science and technology”.
With cloud technology readily available, the cost required for initial investment on the tools are much cost justifiable and tools readily available. SME can also choose to adopt open source Hadoop for storage, processing and computing the structured and unstructured Big Data. Thus the technology with an affordable cost is available for SME.
Big or small challenges for SMEs
Challenges that SME could face would be from the skills of big data analytics that SME might lack.
Having a good understanding on Big Data for SME, the question to be answered is, Can SME embark on Big Data ?
Yes they can! As long as the organization can answer below questions,
- Can the organization extract this data ?
- Can the organization make sense of this data?
- Can the organization use it for improvement of service ?
- Can the organization convert the analysis to profit?
Oxford Economics Survey (2013) identified technology and innovation as the key strategic drivers for the growth of SME and for SME to adopt Big Data. Being able to analyze and predict market and customer behavior with Big Data is a new paradigm shift for SMEs. When it is implemented correctly, it can yield increased flexibility, productivity, responsiveness, anticipation and ability to meet customer need through capturing blind spots and making better decisions.
As a conclusion, with correct approach and by asking the right questions, Big Data can yield significant improvements. SMEs can implement Big Data for in-depth data analysis to point out correlations, risks, opportunities as well as for predictive maintenance, demand forecasting, process optimization, predictive inventory planning, market segmentation, analyzing and predicting market and customer behavior and so on.