To generate better business decisions, you need more and better data, right? Not necessarily. According to SmartData Collective, a successful analytics program requires much more than “big data” — it also requires communication, shared priorities and a decision-making culture within the organization.

Different types of specialists have different roles in making analytics work for an organization, from data scientists to professionals focused on operational analytics or business intelligence. But the largest and perhaps most important group, according to SmartData Collective, comprises all the nonspecialists who must use the analytics tools integrated into their business processes and responsibilities. This group also includes key decision-makers: They need to use data to guide business decisions, but they are not data scientists themselves.

On a technical level, an analytics platform must serve as a means for integrating, processing, tracking and analyzing complex enterprise data from a wide variety of sources. But when it comes to decision-making, it’s helpful to think of analytics as a tool for improving communication.

For example, managers often need to use data to communicate trends to other stakeholders and to analyze scenarios to generate effective business decisions and streamline daily operations. That means they need the tools to quickly and easily transform enterprise data into compelling and actionable reports — without intervention from the technical staff.

In the trenches, a primary challenge for analytics and “big data” initiatives is to improve communication and understanding, according to SmartData Collective. It’s a challenge to refine vast technological resources and put them in the hands of nonspecialists, who need tools that work easily and quickly to create transparency, uncover opportunities and communicate ideas. One easy place to start is to mine the data contained in your company's expense reports. By doing so, you can uncover the true cost of sales, determine which division is spending wisely in comparison to its revenue, even identify which departments or locations stay in compliance with expense policies.

We’d like to hear from you. What are some interesting ways that you’re seeing nontechnical businesspeople use analytics to communicate? Please share your experiences below in the comments section!

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