Deciding how to invest your company's resources is complicated, especially when you're not sure what factors to rely on: revenue, customer reviews, team feedback, or even just a gut feeling.

An emerging field of business development, data analytics, solves this problem by providing insightful data patterns and clear stories that help key stakeholders make these big decisions.

At Growth Acceleration Partners (GAP), we leverage our expertise in the development of analytics solutions to tell our clients the story of what happened, why it happened, and what will happen. With the right data analytics strategy in place, your organization can not only begin to track historical data, but also make fact-based, real-time decisions on how to invest company resources with the end goal of improving your bottom line.

Over the next several months, we are rolling out a series of articles dedicated to this rapidly developing sector. In this article, we begin with a primer on the theory and terminology of data analytics.

Defining data analytics

Because it is a new business component, many companies define data analytics differently. Some companies think simply collecting data is data analytics and others may imagine it's the visual representation of data. While these are vital pieces, they only comprise a portion of data analytics.

With our experience across a wide range of sectors, we define data analytics in this way:

Companies and organizations collect data associated with customers, business processes, market economics, social media, practical experience, and more. The data should measure both internal and external data, which is often publically available. The collection of this data is often known as "big data".

Analytics, then, refers to the insights gleaned from processing the collected data. These insights should turn into actions that optimize marketing campaigns, improve operational efficiency, and respond more quickly to emerging market trends in order to maintain a competitive edge - all with the ultimate goal of increasing business revenue and boosting business performance.

Why we need to analyze big data

Data analytics is defined by using facts to understand what's happening and how to appropriately invest resources, such as money, staff, time, and products. When put to use correctly and systematically, big data helps - or even dictates - how companies invest their resources.

But why do we need to analyze the data; can't we find this information in other ways?

In some instances, data may bear out something that we already see happening. More commonly, data can indicate things that are happening that we may not even see yet. By strategically analyzing big data, the organization will begin to understand where problems lie, how prominent they are, and why they are happening.

Data analytics makes it quicker and easier to see and understand what's happening - often in near-real time. The quicker you recognize a problem, the faster you can react to solve it; saving valuable company resources.

An example from our clients

This story shows how analyzing big data, not simply collecting it, is the lynchpin of success.

Square Root, a Software as a Service company, creates technology solutions that power data-driven action planning for leading automotive and retail enterprises. Square Root engaged GAP to assist in the development of CoEFFICIENT, their Store Relationship Management platform. CoEFFICIENT combines data analytics and machine learning to align organizations, increase transparency, and action improvement plans.

One of Square Root's automotive clients needed a solution to help them align sales penetration data. They had struggled with not only having inconsistent data across multiple systems, locations, and roles, but also not understanding how to take action on that data. The CoEFFICIENT platform allowed the client to have a single source of truth, and analyzed the data to help all areas of the business - from corporate, through the field, and into dealerships - understand current performance and identify opportunities to improve sales penetration targets. As a result, the client was able to hit their target for the year.

I hope part 1 of this 2 part article has shed some light on a few of the benefits your team will experience with the right data analytics strategy in place. With your company's newfound ability to foresee issues before they occur, you'll find that your operations will be much more streamlined and success rates will climb.

Check back soon for part 2 and find out how you can better invest your resources. We'll even touch on a full breakdown of the key elements in data analytics that we use to build the exact data system your organization needs to thrive.

About the Author

Joyce Durst, co-founder of Austin-based Growth Acceleration Partners (GAP), is driven to help software companies achieve rapid growth through business-focused applications. Joyce has launched startups and led teams at enterprise companies by applying her passion and business knowledge to efficiently create software that solves business problems. Active in the community with Special Olympics and the Women Presidents Organization, she enjoys helping other women in technology to achieve their dreams.