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Top talent is scarce, and hanging on to the best employees once they've been hired can be a challenge. Any human resources manager would agree, but it's a particular pain point for those seeking to fill roles in the world of data analytics. 

Even if your company manages to land an exemplary tech graduate from a top school, it still doesn't mean he or she will bring success to a data analytics project. 

A lack of necessary business expertise means that even top tech graduates don't always bring results where data analytics projects are concerned. In addition to facing a scarcity of talent, this is another unpleasant truth business leaders are surprised to discover -- and typically, they only have the realization after an analytics project is spiraling downhill.



Why Analytics Projects Have a High Risk of Failure

Many company leaders view an analytics project as a variation of an IT project; this attitude is likely to be the first step toward dooming the endeavor.

Regardless of what Software as a Service (SaaS) vendors might tell you during their sales pitch, analytics software is complicated by its very nature. It's imperative that you have the right talent to implement and manipulate it. Even if you've hired the most talented IT team member with vast tech knowledge in software development, if he or she lacks business experience, your analysis project may be doomed to fail. 

Smart tech grads simply don't guarantee success. Business acumen is also an important part of the mix.

There is far more to analytics than merely applying algorithms to data. Analytics is an ever-evolving strategy, and data analytics software must be continuously manipulated by savvy data scientists in order to extract the most useful insights. 

Of course those results will only have a useful impact on business decisions when the questions being asked of the data were directly focused on a company's goals and operations. Naturally, this means that keen business insight and broad experience with analytics projects are necessary requirements of a successful data scientist. 

It's a given that in addition to intellectual curiosity, someone leading a big data analysis project would have a solid background in statistics, math, modeling, analytics, and of course, computer science and applications. But the best data scientists also have the ability to pinpoint issues and spy opportunities that are of particular relevance to a given business or industry. 

In reality, most companies simply don't have in-house talent who possess such a wide swath of skills, thus leaving the unwieldy task of data analysis to one of the IT professionals or business analysts on staff -- which most often thwarts a project's success. 

What is the Answer?

Though there's an inherent risk in leaving data analysis in the hands of an IT professional lacking business experience, there also exists possibility for a project's failure when an in-house data scientist works with analytics software that arrives through a SaaS product. This is because data scientists should ideally have intimate knowledge of the analytics software with which they're working, and the knowledge to constantly manipulate it and derive continuously repeatable and valuable insights.

A viable alternative to those shaky scenarios is for businesses to engage with Solution as a Service (SolaaS), a groundbreaking, single vendor approach. The SolaaS model offers a single vendor solution that marries quality data analytics software with a team of the industry's top data scientists who have complete understanding of the software. 

These analysts (the deployment team) work closely with the software development team behind the software, and if questions or issues arise, they are quickly addressed. More importantly when a new idea emerges it is quickly implemented. 

SolaaS brings to the table experienced data scientists with storied business backgrounds, who have worked on many data analysis projects across different industries, giving them sharp business acumen and familiarity with business tactics and needs. This combination of business knowledge and analytics experience, plus a deep understanding of the analysis software yield actionable insights that guide businesses toward more valuable results and targeted, data-driven decision making. 

Once insights are gathered, the data scientists' backgrounds allow them to communicate their results in a meaningful way to the stakeholders. 

Summary

Hiring the best tech grads will not guarantee businesses success with their data analysis projects -- in fact, many ultimately fail. With SolaaS, businesses are granted a team of experienced data scientists, and won't have to rely on recent tech grads picking up business knowledge and experience on the job. This groundbreaking approach brings to a company's doorstep highly trained data scientists with intimate knowledge of the software and proven acuity in business.