What are the 3 areas of analytics that can contribute to decision making?
Data analytics answers pressing questions and unlocks insights to deliver efficiencies. The right analytics allow decision-makers to identify trends and make better-quality decisions. They can make better strategies and understand the implications of each course of action better. The speed of decision-making also improves.
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But not all analytics lead to better decision-making. Here are the four most effective types of data analytics that empower businesses. 1. Descriptive AnalyticsDescriptive analytics identify patterns in raw data to clarify the current state of the matter under analysis. Companies use descriptive analytics to track
Descriptive analytics describes what happened or will happen. Consider a seasonal surge in sales of a video game console. Descriptive analytics attribute the underlying reasons to school vacations. Such insights allow the company to plan for higher inventory during the following holidays. Enterprises applying predictive analytics remain proactive, and can seize opportunities fast. Businesses apply descriptive analytics by:
2. Diagnostic AnalyticsDiagnostic analytics takes insights to the next level by deciphering “why it happened.” It identifies correlations among variables to unearth causal relationships and coexisting trends. Diagnostic analytics gets to the root of the issue or the underlying cause of an outcome. It identifies connections between data and detects activity patterns to unlock business opportunities. For example, descriptive analytics identified a spike in sales of video game consoles. Diagnostic analytics digs deeper. The analyst identifies the console users’ age group as between eight and eighteen years of age and the buyers’ age group as between 35 and 55 years. Digging deeper, the analytics identifies the main reason customers buy the console as gifts for their children. The business could then launch a marketing campaign centred on gifting to boost sales further. Likewise, diagnostic analytics could identify the reason for machinery breakdown as improper usage. The improper use may be complex operating switches and poor user manuals. Business managers applying data analytics could go back to the drawing board and redesign the user console. Businesses apply diagnostic analytics by:
3. Predictive AnalyticsDescriptive analysis describes “what it is,” and diagnostic analytics reveals “how it happened.” Predictive analytics delves into the future and shows “what will happen.” It correlates historical data with industry trends to predict what will happen next. For instance, diagnostic analytics establish parents gift game consoles to children during holidays. Predictive analytics plots a trend that expects similar spikes during the next holiday season. Predictive analytics is invaluable in strategy formulation. It identifies if a trend will continue and, if so, the pace and intensity of the trajectory. Enterprises who apply predictive analytics remain ready to take the right decision at every opportunity. Predictive analytics depends on statistical modelling. The accuracy of predictions depends on high-quality, thorough data. Businesses get started with predictive analytics through the following steps:
4. Prescriptive AnalyticsPrescriptive analytics guides decision-makers on what to do next. This analytics considers all factors connected to a scenario and suggests takeaways. For instance, a marketer could run an A/B test with two ads. One ad could target parents and other children in the video console example above. The test data guide marketers to focus their efforts on parents who make the purchase or children who want the product. To conduct prescriptive analytics,
These different types of data analytics are not mutually exclusive. Enterprises often use all these analytic types in tandem to get a complete picture and make informed decisions. Today’s businesses miss out big time if they make decisions without analytical insights. Data analytics, used the right way, improves organisational learning and performance outcomes. Lack of critical insights leads to loss of opportunities or inability to understand the red flag that stands in the way of obvious choices. Check “Seven Ways AI and Analytics Solve Supply Chain Disruption“ Andre RodriguesAs a software and IT solutions advisor, Andre leads a team of technology consultants for implementing Account-based Marketing strategies to IT customers. In his 30 years of working experience, across the region, Andre has helped numerous clients improve existing business systems and IT infrastructure. This experience has helped Andre secure a unique knowledge and understanding of the challenges faced by these sectors. What are the 3 common categories of data analytics?Three key types of analytics businesses use are descriptive analytics, what has happened in a business; predictive analytics, what could happen; and prescriptive analytics, what should happen.
What analytics are used to help make decisions?Prescriptive analytics and artificial intelligence are currently being used by the majority of big data-driven businesses to improve decision-making.
What is the role of analytics in decisionData analytics, if used properly, provides a competitive advantage over other companies in the industry by enabling organizations to identify new opportunities and leverage their insights to make strategic decisions. Data analytics programs are evolving as the digital transformation of companies progresses.
What are the 3 types of analytics and what kind of questions does each type can answer?Descriptive analytics tells what happened in your business in the past week, month or year, presenting it as numbers and visuals in reports and dashboards. Diagnostic analytics gives the reason why something happened. Predictive analytics determines the potential outcomes of present and past actions and trends.
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