Understanding Business Analytics – Using Data to Drive Insights and Decisions
Data provides businesses with an objective view that helps them make strategic business decisions more effectively and expand operations and sales. Being able to use it wisely is crucial in today’s business climate.
Business analytics professionals, also referred to as data analysts, can examine this data and interpret how it can enhance department processes or aid future financial projections.
1. Analyze All Data
An important step to taking the leap into data analytics requires understanding your organization’s end goals. Understanding your organization’s end goals before engaging in business analytics will enable you to choose appropriate methods and questions to ask.
If a company wants to increase productivity by streamlining commercial operations, predictive analytics could help their sales teams identify underperforming retail locations so they can proactively reach out and offer training or coaching for these stores. It could also trigger workflow in salesforce that sends an email congratulating employees on meeting quotas or outlining strategies that have improved performance.
Business analysts are tasked with identifying business issues and making recommendations backed up by statistical models and data visualization tools. Their job requires translating complex information into formats easily digestible by executives – an essential skill when creating a culture of data-driven decision-making within organizations. Professional certification such as Maryland Smith’s OMSBA program’s ECBA can assist individuals in honing these skills.
2. Analyze Data from Different Sources
Business analytics is the practice of turning raw data into actionable intelligence that can be utilized for organizational change. The process utilizes data mining, forecasting and visualization techniques to detect trends and make predictions about the future; businesses then utilize these findings to devise plans aimed at increasing sales and profits.
Studies indicate that companies typically collect data from over 400 different sources. It’s essential that companies prioritize key data points that will have an impact on their bottom line in order to avoid spending unnecessary time and resources analyzing unnecessary sources of data.
Once you have identified your most valuable data sources, the next step should be analyzing them. First, your data needs to be cleaned by eliminating irrelevant records and redundancies; next step should be categorizing and organizing this cleaned data into logical groups; finally apply a governance model and data source architecture so decision-makers have access to insights whenever they require them.
3. Analyze Data in Different Formats
Business analytics utilizes a set of skills and tools to develop insights that support and drive business decisions. This discipline involves data collection and interpretation as well as statistical analysis, predictive modeling, data mining and forecasting to uncover opportunities for improvement while making more informed business decisions that improve efficiency, revenue and profit.
Employing the appropriate technology can assist companies with business analytics to reach their strategic objectives. One bioscience firm used predictive analytics to understand why its cash collections and claims denials were poor, ultimately helping it clear millions in outstanding accounts receivables and improve operational efficiency.
Before undertaking any business analytics project, it’s crucial to set clear business objectives and set measurable goals. This will enable you to select the appropriate data for analysis while supporting and aligning with your overall business strategy and making it easier to communicate the results to stakeholders.
4. Analyze Data in Real Time
Business analytics enables organizations to make more rapid and accurate decisions more rapidly and accurately. Data-driven decision making involves gathering, analyzing and interpreting key performance indicators (KPIs) and trends so businesses can act based on those insights and facts.
Data mining techniques allow users to sift through large datasets in search of hidden truths and patterns that aren’t immediately apparent, using machine learning and statistical analysis. Predictive analytics enables business analysts to create models which predict future outcomes; business intelligence solutions which use these techniques may even allow business users to configure what-if scenarios without needing sophisticated software programming skills.
An effective business analytics solution can help businesses become more cost-competitive, streamline decision making processes to increase revenues and lower risk, increase revenues and lower risks, as well as get everyone onboard with how analytics can be utilized to reach overarching strategic goals. Leaders must ensure everyone in their company understands this value of analytics to maximize effectiveness of utilization within an organization.