Like their counterparts at larger companies, managers at small and medium-sized businesses (SMBs) are waking up to the fact that data-driven decision-making is crucial for growth and success.
However, many SMBs lack the means to employ highly skilled data analytics professionals to collect, investigate and analyze the dizzying amount of data that is available to businesses these days. The go-to solution has been to outsource this vital data science function to third-party data analytics firms and freelancers instead.
According to a Gartner report commissioned by one such data analytics firm, LatentView Analytics, some 70% of marketers expect the majority of their marketing decisions to be powered by data next year.
“A notable share of the analytics budget — more than technology and nearly as much as internal talent — goes to outside experts,” notes the report. “The majority of mature data-driven marketers expect external sourcing to grow over the next two years, and 30% of them expect to decrease their internal team size, taking more advantage of the efficiency, scale and expertise of service providers.”
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Given the importance of data analytics to businesses’ success, it is a concern that such a vital function is almost routinely outsourced. However, when you consider the costs involved and the shortage of specialist skills required, it has been a logical solution. At least, until recently.
The misconception that shapes today’s data analytics market is that big data is the domain of enterprises and SMBs simply lack the means to manipulate and analyze complex data competently. These misconceptions are now being challenged by emerging self-service analytics solutions, and the question now is whether SMBs can afford not to to take advantage of these new solutions and move data analytics in-house.
Data has become the lifeblood of any effective business, regardless of its size. Deloitte recently published a report titled “The Analytics Advantage” which was the result of an extensive survey that the consulting firm conducted.
One of the many insights in the Deloitte report is that senior executives in the companies it surveyed have realized that “good data can yield good decisions, if captured, analyzed, communicated, and acted upon in a timely and efficient fashion.” This is as relevant to SMBs as it is to large enterprises.
According to one anonymous executive quoted in the report, “Basically, analytics is about making good business decisions. Just giving reports with numbers doesn’t help. We must provide information in a way that best suits our decision-makers.”
Smaller companies, however, are generally not as focused on performance metrics and methodical tracking as the big guys are. They usually have fewer employees, less cash flow, smaller inventory and less diverse product lines, which means that managers often take pride in knowing everything themselves. The challenge for SMBs as it relates to data analytics, then, is as much about changing mindsets and culture as it is about acquiring the skills and technologies required.
In his introduction to the Deloitte report, leading analytics thought leader and academic Thomas H. Davenport notes that “From observations over many years, analytical progress is undeniable: the demand for analytics is much greater, resources are more available, and executive understanding has increased.”
It certainly seems that SMBs are increasingly aware of the need to actively take advantage of data analytics to compete effectively. But how can they do so in a commercially feasible manner? And what stands in the way of SMBs cultivating the capability to conduct data analytics internally?
A combination of more powerful desktop PCs and self-service data science tools represent a directional shift for SMBs. Thanks to solutions like Alteryx, Databox and IBM Watson Analytics, it is increasingly possible for virtually any employee to be a data scientist, pulling relevant data sets, analyzing them with advanced visualization tools and making informed real-time decisions.
As Amir Orad, the CEO of business intelligence platform Sisense, notes, “Traditionally, the main obstacle for self-service analytics was data preparation. Modern analytics technology can simplify this process to the extent that today’s business users can cover the full scope of data analysis – preparation, reporting, and visualization – independently, without dedicated IT or DBA resources.”
The need to balance the costs of hiring a data specialist and benefits of analytics represents a real challenge, which is why so many SMBs believe outsourcing is the answer.
“This route will usually be preferable, because no one understands the business as well as its current executives and employees,” says Sisense’s Orad. “They know which KPIs matter and how to translate data into meaningful results from a business perspective.”
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Cloud-based SaaS data solutions fill the need for powerful infrastructure required for some data analytics processes, along with the need to maintain that infrastructure. Modern self-service data analytics solutions offer SMB teams the capability to collate large quantities of data from multiple sources and analyze it all using easy drag-and-drop interfaces.
These solutions democratize complex data analytics and remove this critical function from the sole domain of large enterprises. An immediate benefit to bringing data analytics in-house is being able to dramatically reduce the latency traditionally associated with complex business intelligence activities.
Reducing this latency means that businesses are able to act on insights derived from data, often within minutes of information being collected. Management can capitalize on positive trends before anyone else does and circumvent negative ones before they cause any damage. Reducing lag times effectively makes for faster decision-making, using actionable business intelligence, as informed by snapshots of the business ecosystem any point in time.
As the cost and infrastructure barriers to access to high impact data analytics solutions for SMBs crumble, these businesses are beginning to realize that their assumptions about access to these important business functions are no longer valid. The need to outsource data analytics is quickly becoming a thing of the past for SMB leaders who are interested in handling their own data.
What this means is that SMBs can now make better business decisions that are informed by large, complex datasets and respond more effectively and swiftly to changing marketplace dynamics in real-time. That sounds like a powerful competitive edge.
Ramon Ray, Editor & Technology Evangelist, Smallbiztechnology.com
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