The term “prescriptive analytics” denotes the use of many different disciplines such as AI, mathematics, analytics, or simulations to advise the user whether to act, and what course of action to take. In that sense, prescriptive analytics offers an advisory function regarding the future, rather than simply “predicting” what is about to happen. This newer branch of business analytics informs and guides decision logic through the skillful use of analytics. While this form of analytics is still not as widely adopted as predictive analytics, it was predicted that by 2021, the prescriptive analytics software market will touch $2.1 billion.
What Exactly the Heck are Prescriptive Analytics? even suggests that prescriptive analytics is not just one specific type of analytics but an inclusive Data Science activity, which combines the goals of descriptive, predictive, and prescriptive analytics to aid decision-management. All Aboard the Prescriptive Analytics Express states that the true test of prescriptive analytics will begin with the optimization of manufacturing or supply chain systems.
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Prescriptive: The Maturity Model of Business Analytics
In Gartner’s analytics maturity model, “prescriptive analytics” lies at the highest level of human comprehension. Not only does this form of analytics offer choices to the business decision-maker, but it also helps in making an optimized choice.
According to Prescriptive Analytics Takes Analytics Maturity Model to a New Level, a Gartner Report has indicated that only three percent of surveyed businesses are utilizing prescriptive analytics, whereas about 30 percent are actively using predictive analytics tools. The best part of this inclusive analytics discipline is that it can begin with something as basic as Excel, and then graduate with enterprise-grade, predictive-analytics software comprising complex business rules, models, and ML algorithms. While Excel models may succeed in demonstrating future outcomes of specific trends, more sophisticated tools may be needed to advise (prescriptive) which option is most suitable among a range of options.
As prescriptive analytics helps businesses discover unknown sources of value, this type of analytics is intrinsically value-driven. A company called River Logic, an SaaS solution provider, has built its reputation on prescriptive analytics and offers optimizations of business value chains. The Surge of Prescriptive Analytics traces the growth of prescriptive analytics through vendors like River Logic.
Widespread Adoption of Prescriptive Analytics is Still Pending
Data-enabled decision-making has already helped businesses earn huge rewards in the forms of optimized costs, higher profits, better supply chains, and improved customer service.
The easy availability of huge volumes of data and relatively cheap storage technologies have made it possible for businesses of all sizes to take advantage of analytics platforms to operate their businesses on superior, technologically-backed decisions.
A suitable technology was needed to harness the power of big data, and now prescriptive analytics has removed that limitation. Prescriptive Analytics Use Cases suggests that descriptive, predictive, and prescriptive analytics each have distinct business goals to fulfill, and used together, they deliver the best solutions to business problems.
While the strength of descriptive analytics is in analyzing past events, that of predictive analytics is using the past trends and patterns to make future forecasts, and finally, the strength of prescriptive analytics is the comparison of available options and recommendation of the best option.
Doron Cohen, CEO of Powerlinx, and Chairman of Dun & Bradstreet Israel, remarked: “Prescriptive analytics can take processes that were once expensive, arduous, and difficult, and complete them in a cost-effective and effortless manner.” Thus, businesses have to realize which processes may be streamlined through the use of prescriptive analytics to hasten widespread adoption of this technology. Although much of the supposed benefits of prescriptive analytics are still locked in modeled “use cases,” these should soon result in widely publicized case studies.
Use Case 1: Predictive Analytics in Healthcare
While the global healthcare industry is undergoing a value-assessed transformation, what better time for this industry to embrace advanced data analytics? In a value-based business model, the consumers are highly demanding, and they are always searching for quality at the best price. In such a climate, the healthcare industry has an obligation to deliver the best possible outcomes for patients and customers.
Prescriptive Analytics: The Cure for a Transforming Healthcare Industry explains how prescriptive analytics can play a big role in transforming the global healthcare industry. The “real-time” and “evidence-driven” nature of healthcare decisions has a lot to gain from this analytics science.
Healthcare is one field where physicians and other medical practitioners often rely on their intuition and past experience while making decisions about patient care. With the arrival of prescriptive analytics, will the experienced medical practitioners be willing to set aside their intuitive insights when confronted with solid, data-backed decisions or recommendations? Prescriptive Analytics Beats Simple Prediction for Improving Healthcare describes the far-reaching impact of prescriptive analytics on the healthcare business.
An infographic from River Logic showcases useful prescriptive analytics use cases in healthcare in 10 Use Cases for Prescriptive Analytics in Healthcare
Use Case 2: Predictive Analytics in Sales & Marketing
With the avalanche of customer data pouring in through diverse digital touchpoints, it is important that sales and marketing departments, especially in retail, take advantage of the intelligence hidden in those data. Predictive analytics and big data helped these customer-focused functions to a point, but now prescriptive analytics will take customer-centric, business activities a notch higher.
Prescriptive Analytics Use Cases for Sales and Marketing includes a solution for retail planning. This platform offers a modeling technique for designing marketing mixes. The platform has also been used to optimize product mixes. The diverse applications used prescriptive analytics to target and promote products, to forecast demands, and to optimize trade campaigns.
Use Case 3: Predictive Analytics in Big Data Analytics
Prescriptive analytics has been defined as the future of big data, but what does that really mean?
Big data analytics, in most cases, begin with descriptive analysis of past data, then moves toward predictions based on trends and patterns. Now business analysis can optimize recommended outcomes and actions with the help of prescriptive analytics. The sheer volume of big data makes it easy for data scientists to rationalize recommended “actions” and their corresponding “outcomes,” which was not possible in the pre-prescriptive analytics era. So, now the business users are not only informed, but also guided and navigated about their future course of action. The Future of Big Data? Three Use Cases of Prescriptive Analytics offers examples.
The prescriptive analytics expert is like a surgeon offering a range of treatment choices with possible outcomes, and then the business user, like the patient, is free to make a wholly “informed and guided” decision. Although the ultimate goals of prescriptive analytics are to mitigate future risks and capture opportunities, few business owners currently have that amount of data to make the best use of prescriptive analytics. The future of business analytics lies in mass adoption of prescriptive analytics in all enterprise big data projects.
Use Case 4: Predictive Analytics in Risk Management
Use Prescriptive Analytics to Reduce the Risk of Decisions suggests the next wave of business analytics will center on guided decision-making, as business leaders move away from the “law of averages” by using prescriptive analytics. This type of advanced business analytics can reduce the risk of particular decisions. This implies not only groundbreaking technologies and tools, but also a change in the mindsets of decision-makers.
Business operators and users will develop new skills and new approaches to decision-making. The individuals who relied on speed and past experience will learn to depend on analytics-guided decisions. The above article describes how prescriptive analytics could have averted the flooding of Red River in North Dakota and Minnesota. Prescriptive analytics refines the science of predictions by lowering risks.
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