For a company's analytics software to successfully deliver actionable insights, a combination of complex software and ever-changing data feeds need to be continuously updated and controlled. Data must be properly wrangled, the right questions asked, and insights extracted in an ongoing cycle. Businesses trying to benefit from analytics software without help are faced with a mighty, but avoidable, challenge. Analytics software is inherently complex, and operating it yourself can be a time-consuming and costly endeavor. Even after facing the decidedly unglamorous struggle of initial data wrangling and optimizing your software for proper analysis, a new burden unfolds. Unless you regularly use it, you're likely to forget some of the new software's most intricate and seemingly endless details. If you've been tasked with tackling your company's data analysis, and you want it to succeed, it's best not to go it alone. Do You Want Software or Do You Want Results? When it's properly set up, analytics software gives businesses an invaluable look at their customers' unbiased sentiments and actions; these unsolicited thoughts have the potential to be a company's best type of feedback. These compelling insights inform future business decisions and guide a company toward further success. But a software package is only as valuable as its utilization. Because detailed knowledge of the software is necessary, even the industry's most powerful software packages will be worth little to a business that is unsure how to leverage its strengths into helpful insights. At the end of the day, what you're shopping for isn't merely software, it is the results. This is where many businesses misfire. They think they simply need the best possible software. But the software is more than just a list of capabilities – it needs to work to your benefit. On a basic level, yes, this means getting it set up correctly, but it's just as important to target the right kinds of data and ask the best questions to gather useful insights, and finally, present the analysis in such a way that your company derives the most value from the information. Don't Be the Guinea Pig Teams at many companies don't realize that employing data analytics software is not simply about targeting the right kinds of data and analysis at the beginning of the software's implementation. Analytics is also an ongoing science – endless, in fact. New data will always arise, as will new questions and ways to present it. Your analytics must be constantly updated and fine-tuned to continue delivering valuable insights. The knowledge garnered from data analysis brings enormous value to a company; it's best to avoid giving novice users opportunity to experiment on your business data with new, complex software. What's the Answer? You don't want to take risks with analytics software utilization. The best way to guarantee its efficacy is through Solution as a Service (SolaaS). The SolaaS model combines some of the industry's highest-performing data analytics software products with a team of highly trained data scientists through a single vendor, building a seamless, synergetic relationship. Unlike a systems integrator model, where the systems integrator may not own the software it's using, with SolaaS there is no disconnect between the development team and the implementation team. In fact, SolaaS offers a tight integration between the people building the software and the data scientists who are working with it. As questions arise from either team, they can easily communicate with each other, best harnessing the software's power for your company's benefit. SolaaS benefits corporations in any industry. For example, if you need to analyze call center transcripts and social media data, or dive into a customer service survey's open-ended questions, the SolaaS model offers a team of experts familiar with your vertical who can best target and analyze your trove of data. Because these data scientists have worked on many projects in various industries, they are accustomed to seeing different scenarios and business tactics. Summary When your company employs data analytics software, having an inexperienced in-house team experimenting with its utilization could prove time-consuming and costly. It's critical you derive insights by combining a single vendor's robust software with professional data scientists via Solution as a Service (SolaaS).