Data analytics is a vast field and one that covers many areas. In the world of business, analytics is used to forecast trends and predict demand or challenges. Today, businesses have access to huge amounts of data about their customer's interests, preferences and behaviors. Prescriptive analytics is one way of putting that data to use to make better business decisions. Business analytics has three parts, including descriptive, predictive and prescriptive analytics.
Descriptive analytics refers to a form of analysis that describes a business' performance to date. For example, looking at past website traffic or sales performance would be considered descriptive.
Predictive analytics takes that data and uses it to project future performance. Historic data can be parsed using machine learning algorithms to attempt to predict future trends.
Prescriptive analytics is more about predicting outcomes based on different types of variables. Instead of predicting an outcome, using prescriptive techniques means an analyst can tweak different variables to see how they affect the outcome of a scenario.
A Prescriptive Analytics Definition
Gartner describes prescriptive analytics as answering the question of "What can we do to make X happen?" It does this by using complex tools, such as neural networks, machine learning and heuristics. Prescriptive analytics uses machine learning and artificial intelligence, along with business rules, to describe what should happen.
“Based on the results of predictive analytics, prescriptive analytics aims to understand what variables can be manipulated to achieve the desired outcome and how,” wrote Forbes Council Member and writer, Carlos MelendezIt takes the data, or what we know, and processes it to provide recommendations for the best steps to take to improve future outcomes.
The Adoption of Prescriptive Analytics
While the use of predictive analytics is commonplace in business, prescriptive analytics is not as widely adopted. The practice is not new, however, and has attracted interest and detailed reports from organizations, such as Forrester, even in 2017.
In 2019, Gartner predicted the prescriptive analytics software market would reach $1.88 billion by 2022, showing a Compound Annual Growth Rate (CAGR) of 20.6%. It's unclear how much of an impact the pandemic had on this sector.
Why Use Prescriptive Analytics?
The main benefit of this kind of analysis is that it helps managers optimize the efficiency of their operations. Prescriptive analytics can form the basis of other business intelligence tools. It offers the option to view real-time business information and long-term projections about business operations.
Prescriptive analytics also helps businesses make impartial decisions. AI processes data quickly and more accurately than a human could. This means human biases and emotion won't creep into decisions.
Jobs in Prescriptive Analytics
Prescriptive analytics is used in many jobs, both in business and in STEM. For example, an Operations Research Analyst may use prescriptive analytics as a part of their job. The Bureau of Labor Statistics lists the median pay for an Operations Research Analyst as $86,200 per year. This job field is expected to grow by 25% between 2020 and 2030.
Analysts have several tools at their disposal, including descriptive, predictive and prescriptive analytics. Each of these techniques requires different tools and methods and is applied in different situations. While many areas of prescriptive analytics require specialist tools, a lot can be done with common systems that are taught as part of MBA courses.
TechTarget notes that as data collection methods become more readily available and analytics technology improves, the adoption of prescriptive analytics techniques is likely to grow substantially.
Many businesses started using Excel with plugins for analytics, TechTarget goes on to explain. These tools are suitable for most use cases. If a business discovers they have more advanced or sophisticated needs, they can turn to more powerful and specialist software.
Real World Prescriptive Analytics Use Cases
Prescriptive analytics is something that can be used by businesses of all sizes and in a variety of industries. For example, Stitch, an analytics tool, is promoted as being useful for both the transportation and finance industries. Stitch explains that prescriptive analytics can be used in transportation to "Minimize energy usage through better route planning and solving logistical issues, such as incorrect shipping locations."
Meanwhile, in the finance industry, firms can, according to Talend, build algorithms that churn through historical trading data and measure the risks of trades. This allows them to make data-driven business decisions.
Marketing and Sales Analytics
Most businesses today have to deal with many challenges and limtations, including budgets, scheduling, purchasing issues and potential clashes, in terms of what promotions to run at any given time.
Prescriptive analytics can be employed to help businesses optimize different functions, including:
A marketing model could, for example, take into consideration the cost of the products, baseline demand, various product substitutions, training costs and income generated. This can give extensive insights into the profit potential available for various promotions.
It’s no wonder organizations are interested in prescriptive analytics. Better and faster decision making is a place we’d all like to get to. Companies looking for the best possible business outcomes should be taking a serious look into how prescriptive analytics can help.