Various organizations define Big Data differently. Some use “petabytes of data” as a benchmark to isolate big data from other normalized and structured data sets that exist within an organization. However, this measure quickly boxes big data analytics into the large enterprise market segment. Small and mid-market businesses certainly do not have this extent of data but Big Data still relevant for them. In fact Big Data solutions are more relevant for Small and Mid-Market businesses. However, it will take some creativity on the part of solution providers to make Big Data accessible, easy to use and comprehend for segment that constitutes 97 percent of global businesses.
Cloud computing started as an enterprise play, however, it was quickly discovered that SMBs will be the more relevant target segment with a faster path to adoption. Similarly, as Virtualization market started getting fully penetrated within the enterprises, vendors shifted their focus to the SMBs with some very creative solutions. As far as big data is concerned SMBs are starting to show interest and even adoption. However, there is a stark difference in approaches between mid-market businesses and small businesses. While mid-market businesses are experimenting with bespoke solutions, small businesses are gravitating towards a multi-tenant, aggregated and federated big data solution that has a mix of publicly available data and their own internal data.
It is expected that in year 2016, global SMBs would spend US$1.6 Billion on big data solutions exhibiting a growth rate that is faster than what was exhibited by cloud computing solutions. Cumulatively between now and end of 2016, SMBs itself would have shelled out US$3.9 billion on big data solutions. This spending includes hardware, software and services.
So why are many big data solution providers ignoring SMBs? Simply put, because of perceived complexity and inability to create bite-sized messaging that directly address SMBs pain-points. But they should not forget that business intelligence has now become one of the fastest solutions to be adopted by SMBs. If done right, Big data address three key pain points of SMBs: Increase sales, Efficient operations, Improve Customer service.
Promise of Superior Decision Making
Let us take Techaisle’s recent global mid-market businesses’ Big Data Adoption & Trends study which clearly shows that the promise of superior data-driven decision making is motivating 43 percent of global mid-market businesses to either invest in or investigate Big Data technology. Out of these, 18 percent of mid-market businesses are actively investing in big data related projects. The possibilities of analyzing a variety of data sources, producing action-driven business insights is too big to ignore for these businesses.
Similar to cloud, the attitude towards Big Data is transitioning from “Over-Hype” to “Must-Have” technology with the size of business. Even within the businesses that consider big data to be over-hyped, 29 percent think that it will be an important part of their business decision making process in the future.
Extracting Business Perspectives
Business intelligence by itself has provided enough business insights, however, mid-market businesses are now looking for extracting business perspectives to drive superior decisions and ultimately achieve superior results. Extracting business perspectives has become important as they rethink their marketing strategies because mobility, social media, and other transactional services have increased the number avenues for connections with their customers and partners.
CRM solutions had first established the analytics for analyzing customer data. However, the data was mostly two-way transactional data. This changed when customers began visiting business websites to explore, browse and perhaps make purchases thus leaving behind a trail of information. IT vendors and mid-market businesses figured out the need to analyze the data and combine it with transactional information.
However, everything changed with the onset of social media, blogs, forums, wikis and opinion platforms where the identification of false positives and negatives became difficult and knowledge about the customer and resulting segmentation became an inaccurate undertaking.
Big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights whether be for generating sales, improving products or detecting fraud.
It is therefore not surprising that global mid-market businesses are turning towards big data analytics to analyze social media data, web data, customer and sales data along with click-stream machine generated data and even communications data in the form of emails, chat, voicemails.
Leap of Faith or Solution Readiness
Analyzing data from diverse sources leads a mid-market business to naturally consider linking structured and unstructured data. This also drives them to evaluate and select the technology that can be used for simplified implementation. Simplified implementation is important because mid-market businesses do not yet have in-house capabilities to analyze unstructured data and those that have them consider the capabilities at best rudimentary.
Big data therefore is a major leap of faith for mid-market businesses resulting in treating big data analytics projects usually as separate to the existing analytics within the business. More aggressive adopters are planning to use big data analytics along with other analytics in a coordinated manner so that one does not become an inhibitor for the other.
In recent years technology and technology options have evolved extremely rapidly for an average business to understand, evaluate, purchase and implement. The complexity gets further exacerbated with lack of experience, lack of skilled manpower and innate difficulty in identifying external consultants that would be the most right fit for their business objectives and budget availability.
In spite of challenges, the study shows that there have been some successes when business units, IT & data analysts exhibit extraordinary alignment. Our study shows that mid-market businesses typically started their big data journey in one of four ways. Highest success rates for project implementation and generating new insights have been achieved when IT and data analysts work with external consultants from project inceptions.
SMBs as the Path to Big Data Simplicity
The global SMB spend on big-data related deployments will cross US$1.0 billion in 2013 which is a 32 percent increase from 2012. SMBs are still experimenting to see if big data analytics can provide newer insights into their operations and better knowledge about their customers. It is still very early days for small and mid-market businesses to fully embrace big data but they are planting the seeds in terms of re-architecting their IT infrastructure to plan for the future. But we believe that SMBs may very well race ahead of enterprises with their deployments as technology becomes simpler and consultants become experienced.
Cloud computing started as an enterprise play, however, it was quickly discovered that SMBs will be the more relevant target segment with a faster path to adoption. Similarly, as Virtualization market started getting fully penetrated within the enterprises, vendors shifted their focus to the SMBs with some very creative solutions. As far as big data is concerned SMBs are starting to show interest and even adoption. However, there is a stark difference in approaches between mid-market businesses and small businesses. While mid-market businesses are experimenting with bespoke solutions, small businesses are gravitating towards a multi-tenant, aggregated and federated big data solution that has a mix of publicly available data and their own internal data.
It is expected that in year 2016, global SMBs would spend US$1.6 Billion on big data solutions exhibiting a growth rate that is faster than what was exhibited by cloud computing solutions. Cumulatively between now and end of 2016, SMBs itself would have shelled out US$3.9 billion on big data solutions. This spending includes hardware, software and services.
So why are many big data solution providers ignoring SMBs? Simply put, because of perceived complexity and inability to create bite-sized messaging that directly address SMBs pain-points. But they should not forget that business intelligence has now become one of the fastest solutions to be adopted by SMBs. If done right, Big data address three key pain points of SMBs: Increase sales, Efficient operations, Improve Customer service.
Promise of Superior Decision Making
Let us take Techaisle’s recent global mid-market businesses’ Big Data Adoption & Trends study which clearly shows that the promise of superior data-driven decision making is motivating 43 percent of global mid-market businesses to either invest in or investigate Big Data technology. Out of these, 18 percent of mid-market businesses are actively investing in big data related projects. The possibilities of analyzing a variety of data sources, producing action-driven business insights is too big to ignore for these businesses.
Similar to cloud, the attitude towards Big Data is transitioning from “Over-Hype” to “Must-Have” technology with the size of business. Even within the businesses that consider big data to be over-hyped, 29 percent think that it will be an important part of their business decision making process in the future.
Extracting Business Perspectives
Business intelligence by itself has provided enough business insights, however, mid-market businesses are now looking for extracting business perspectives to drive superior decisions and ultimately achieve superior results. Extracting business perspectives has become important as they rethink their marketing strategies because mobility, social media, and other transactional services have increased the number avenues for connections with their customers and partners.
CRM solutions had first established the analytics for analyzing customer data. However, the data was mostly two-way transactional data. This changed when customers began visiting business websites to explore, browse and perhaps make purchases thus leaving behind a trail of information. IT vendors and mid-market businesses figured out the need to analyze the data and combine it with transactional information.
However, everything changed with the onset of social media, blogs, forums, wikis and opinion platforms where the identification of false positives and negatives became difficult and knowledge about the customer and resulting segmentation became an inaccurate undertaking.
Big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights whether be for generating sales, improving products or detecting fraud.
It is therefore not surprising that global mid-market businesses are turning towards big data analytics to analyze social media data, web data, customer and sales data along with click-stream machine generated data and even communications data in the form of emails, chat, voicemails.
Leap of Faith or Solution Readiness
Analyzing data from diverse sources leads a mid-market business to naturally consider linking structured and unstructured data. This also drives them to evaluate and select the technology that can be used for simplified implementation. Simplified implementation is important because mid-market businesses do not yet have in-house capabilities to analyze unstructured data and those that have them consider the capabilities at best rudimentary.
Big data therefore is a major leap of faith for mid-market businesses resulting in treating big data analytics projects usually as separate to the existing analytics within the business. More aggressive adopters are planning to use big data analytics along with other analytics in a coordinated manner so that one does not become an inhibitor for the other.
In recent years technology and technology options have evolved extremely rapidly for an average business to understand, evaluate, purchase and implement. The complexity gets further exacerbated with lack of experience, lack of skilled manpower and innate difficulty in identifying external consultants that would be the most right fit for their business objectives and budget availability.
In spite of challenges, the study shows that there have been some successes when business units, IT & data analysts exhibit extraordinary alignment. Our study shows that mid-market businesses typically started their big data journey in one of four ways. Highest success rates for project implementation and generating new insights have been achieved when IT and data analysts work with external consultants from project inceptions.
SMBs as the Path to Big Data Simplicity
The global SMB spend on big-data related deployments will cross US$1.0 billion in 2013 which is a 32 percent increase from 2012. SMBs are still experimenting to see if big data analytics can provide newer insights into their operations and better knowledge about their customers. It is still very early days for small and mid-market businesses to fully embrace big data but they are planting the seeds in terms of re-architecting their IT infrastructure to plan for the future. But we believe that SMBs may very well race ahead of enterprises with their deployments as technology becomes simpler and consultants become experienced.
