Data science and information analytics is a crucial component to nearly every industry and business model. In order to succeed, business professionals will need necessary knowledge in data science to make business decisions and solve problems.
Murray State University offers a fully online Master of Science in Information Systems (MSIS) with a concentration in Business Analytics degree. This program is designed to help business professionals become experts in information systems, business analytics tools and data science.
Here are three ways technology leaders with expertise in these areas can use data science to solve complex problems and improve business outcomes:
- Identifying Internal and External Problems to Remediate
Inefficiencies in resource and time management can negatively impact a business’ bottom line, productivity and growth potential. Market volatility and disruptions can be difficult to navigate successfully, and failing to weather these disruptions can harm customer relationships, lessen market share and limit opportunities for market expansion.
Identifying problems and their root causes is necessary for addressing such challenges. Data-driven analytics tools can be essential for identifying both internal and external issues rapidly and accurately.
Technology leaders can use today’s analytics tools to collect and analyze massive amounts of data. Then, advanced machine learning and automation technologies can detect nuanced patterns in that data, offering insight into the root causes of a targeted problem. This is known as descriptive analytics (helping business users understand what has happened) and diagnostic analytics (illuminating why something has happened).
Data scientists and other analytics professionals can use tools like data visualization to represent the insights these types of data analytics offer in simple ways. These comprehendible representations of data can help business leaders understand and address problems and make decisions.
An article from Big Data Zone notes that an important benefit of modern data science is the ability of advanced analytics to comb through big data in real time. This allows analytics software to offer “real-time reporting” (RTR) on market conditions, customer interactions and internal processes. With RTR, business users can identify and address problems as they happen, avoiding costly inefficiencies, missed opportunities and harm to customer relationships.
- Prescribing Solutions to Complex Problems
Importantly, today’s data and business analytics tools can offer business users more than merely descriptive and diagnostic analysis. Technologies like deep learning allow analytics software to explore and predict outcomes of various courses of action and prescribe solutions with the most likelihood of success.
These types of analytics are known as predictive analytics and prescriptive analytics. They can help business leaders make data-informed decisions to solve existing problems.
These types of analytics also facilitate Existent Data Interpretation (EDI). According to Big Data Zone, “The purpose of EDI is to construct predictive models that will help organizations avoid problematic customer(s) relations incidents, for example, that could be avoided.”
By predicting issues that may arise, EDI empowers business leaders to be proactive in their decision-making, sidestepping potential issues and retooling efforts to minimize future problems.
- Discovering Opportunities for Securing Competitive Advantages
Harvard Business School notes that “Through learning how to recognize trends, test hypotheses, and draw conclusions from population samples, you can build an analytical framework that can be applied in your everyday decision-making and help your organization thrive.” Consumer fads, innovations and trends shift at lightning speeds. Businesses must do more than react to these changes to stay relevant.
Successful businesses keep ahead of the curve, anticipate trends and actively drive innovation. Analytics tools like EDI help businesses do this by analyzing data on consumers, competitors, changing market conditions, supply chain logistics and other factors to predict likely trends.
Predictive and prescriptive analytics allow business users to improve functions like product development and marketing. As business.com puts it, “Big data and marketing research are a match made in statistical heaven.”
Through uncovering real-time patterns in consumer and market data and offering evidence-based predictions on future patterns, data analytics helps decision-makers discover potential opportunities. This ability to focus efforts on pre-empting product development according to consumer preferences and needs is integral to securing competitive advantages in crowded markets.
In the past, the unpredictability of consumer trends and behavior made anticipatory strategy and investment in innovation a challenging gamble. But harnessing the potential of data science and analytics tools can make predictive innovation a reality, even a necessity, for modern businesses.
Identifying problems, addressing past and potential issues and discovering future opportunities are three “simple” ways data science can improve business outcomes. With expertise in business analytics and information systems, technology leaders can use data science to enhance efficiency and productivity across business processes in virtually limitless ways.