Business Challenges to Using Data Analytics

Over the past several months I’ve been introduced to various business analytic tools for working with big data. The introduction to these tools, including SAS and Tableau, was provided in a business analytics course offered as part of the MBA program at Radford University. At first, I was intimidated at the thought of learning SAS, Tableau, and SQL. I am most comfortable using my ‘tried-and-true’ Excel methods to analyze data and the thought of learning the foundations of coding and new tools was overwhelming. However, throughout this course I found that learning the basics of SQL, SAS, and Tableau to be valuable for me professionally. I’ve also realized that these tools are extremely valuable for organizations.

Using these tools to work with large data sets to reveal relationships, trends, and patterns is essentially telling a story. Business analytic tools that help tell the story about a company’s past and help leaders make decisions about a company’s future is valuable for all businesses in all industries. Numerous articles and extensive research has been completed outlining the benefits of business analytics. Many articles have been written featuring Fortune 500 companies and their successes from using data analytics in product marketing, employee recruitment and retention, gaining efficiencies in internal processes, and more. However, based on other studies and from my work experiences with smaller businesses and organizations, many are only minimally using data analytics. Why is that? I feel certain that almost all organizations are accumulating and storing data so why isn’t that data being analyzed, reported to the organization’s decision makers, and used to make decisions and organizational changes? Businesses are confronted with various obstacles that prevents the effective analysis and use of the data they maintain.

A Cultural Change

Perhaps one of the biggest obstacles is an organization’s culture. The adoption of data analytics to drive business decisions often requires a cultural change. Traditionally, departments operate in silos by creating their own spreadsheets and databases to maintain information. Information is not centralized and is not shared across the organization. Even organizations with a robust ERP system may have data that is centralized, but not shared across departments to allow for relationships among the data to be identified and analyzed. Additionally, I’ve observed how many employees in organizations are resistant to change. Even small operational or process changes can be met with skepticism and with the response of “But, that’s how we’ve always done it.” Employees are most comfortable performing their job duties in the same manner as they have done for the past 5, 10, 15, or 20 plus years even though technology has changed significantly. Similarly, embracing data analytics to drive decisions instead of acting on instinct is a significant change that can be met with resistance. This type of cultural change of data sharing, data analysis to reveal trends, and using data to make business decisions requires leaders at the top of the organization to promote and champion a business analytics initiative.

Data Analytic Tools

Organizations working toward implementing a data analytics approach must consider which data management tools they will use. SAS and Tableau are two powerful data analysis tools that we covered in the business analytics foundations course at Radford University. These tools are used by many organizations who have embraced the power of data analytics and have hired data analysts whose primarily job responsibility is to analyze data. These programs allow for large data sets, data from multiple tables to be joined together in a single table, the creation of dashboards and visuals to report results, and much more. However, businesses in the early stages of adopting a data analytics approach often use Excel as their primary data management tool. Data from a company’s ERP system is exported to Excel and analyzed through the use of pivot tables and vlookups. Graphs and other visual illustrations of data trends and patterns can be generated through Excel. However, as companies begin seeing the benefits of business analytics, they may find it necessary to invest in more robust data management tools.

Recruiting Data Analysts

Another obstacle almost all companies face is the hiring and retaining of employees with knowledge and experience of data analytics. This is a challenge shared by companies who have embraced data analytics as well as those who are just beginning the transition. Data analysts not only need to have the technical skills necessary to work with large data sets potentially from various systems in a variety of forms, but they must be able to work with individuals throughout the organization to understand business operations and business needs in order to provide data in a valuable way. Data analysts must be knowledgeable of business challenges, industry issues, organizational procedures, and so forth. Having this knowledge enables them to understand the relationships in the data so that a meaningful story can be told. For businesses with defined data analyst positions, department managers may need to be trained on the basics of business analytics to more effectively communicate requests to the data analyst and understand the results reported to them. 

Data Integrity

You’ve probably heard the phrase “garbage in, garbage out”. Well this is true as it relates to data analytics. Today, businesses are capturing and storing all types of data including financial, customer, human resource, transactional, and more. However, this data can only provide meaningful information for decision making if the data is accurate. Data captured through manual input is subject to error. And the likelihood of inaccurate data increases if there are not clear procedures for data technicians to follow when keying data into the company’s ERP system. I’ve been on project teams in which new pieces of data needed to be captured in the company’s system for reporting requirements. If the system didn’t provide a specific field for this information, other existing data entry fields were repurposed. As a result, the name of the field may not correlate with the data entered. This can be misleading for data technicians and data analysts. Procedure manuals should be reviewed and updated frequently as needed to provide a guide for accurate data entry and an understanding of the data elements being stored.

Financial Costs

Some business leaders may be concerned that the financial investment in business analytics, including data management software and the hiring of data analysts, is too costly. However, others argue that it is too costly not to make this investment. With technology today, data is everywhere. Not only do businesses have their own data, but often have access to market and industry research, data from social media sites, and more. Using data to understand the company’s past and current performance, trends, and patterns as well the trends and patterns in the industry or market can help drive decisions about a company’s future. This creates a competitive advantage for businesses.

Although there are a number of obstacles and challenges organizations face in implementing a data analytics approach to conducting business, I believe it is more critical than ever for businesses to acknowledge these challenges and work to overcome them. The importance of business analytics will continue to grow and I believe that more mid-size and small organizations will begin adopting business analytic strategies in some capacity in the future. It’s necessary. With organizations operating in an increasingly competitive and fast-paced environment with customers who are more informed than ever, data analytics provides the competitive edge businesses need.