Data analytics is a generalized term that can be a catch-all for more specific applications including business intelligence platforms, data governance, forensic data analysis, advanced statistical modeling and more.
“Data analytics can empower business leaders to make better decisions, not by replacing intuition or business expertise, but rather by augmenting or supplementing it,” says Jonathan Poeder, Director of Data Analytics at Clark Schaefer Hackett.
Companies face challenges when developing an analytics program. But businesses that do not integrate data analytics into their decision-making process are in danger of being at a competitive disadvantage within their industries.
Smart Business spoke with Poeder about data analytics programs and what companies need to understand before attempting to implement one.
Why is data analytics important?
Analytics involves shaping data structures into a useful format and applying mathematical techniques to extract meaningful information — to find the signal in the noise.
Storage technologies have become more robust, which means companies can cost-effectively track petabytes of information if needed. Extracting data that can inform decision-making on a specific problem is very challenging and can become a barrier that prevents many companies from attempting to develop analytics capabilities. Business leaders see the value of that information, however, so there’s a strong incentive to pursue methodologies and techniques to identify reliable, data-driven insights.
How common is it that a company is effectively capturing and analyzing data?
Data analytics, for some smaller businesses, might mean using Excel spreadsheets or utilizing a simple business intelligence platform. Companies can use these tools and grow, but often struggle to transition to something more robust that requires sophisticated expertise to develop and operate.
Larger businesses tend to have a higher level of sophistication, but they still face challenges. For instance, a business might have a rich database under a third-party platform through which they manage products and services. However, staff often lacks the training or know-how to utilize the full potential of the data.
Code customization that would shape data to enable targeted advanced data analytics is a skill set frequently lacking in organizations. The business is then constrained by what the platform will provide. Regardless of a company’s size, if leadership does not understand and support the value analytics brings to a business, it will stunt the company’s growth potential.
What do companies misunderstand when it comes to data analytics?
Data analytics can seem esoteric. Business owners and executives want data to be more relatable, easier to understand and easier to transform into something meaningful. But it’s a deep and complicated field. The difference between perception and reality can create a disconnect between data analytics experts and the C-suite.
Executives might not understand the level of work that goes into extracting useful data from a database. They also might not understand some of the implications of various findings, or struggle to manage the analyst in ways that allow the analyst to provide data of maximum value to the organization. These are just a few of the reasons that organizations struggle with implementing a data analytics program.
Who can help a company that wants to better utilize, or implement, data analytics?
It can be challenging and expensive to get a data analytics program in place and operating effectively — from leadership to infrastructure to talent. Just hiring an analyst won’t cut it. There is a lot more to building the infrastructure, getting the right data, and implementing a data analytics program than just hiring a data scientist. For these companies, the best strategy is to start with an external consultant. Talk to an organization with data analytics expertise to see what options exist to leverage data analytics assets to gain efficiencies and grow.
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