What is Prescriptive Analytics? Functioning, Tools

  • Post last modified:19 May 2023
  • Reading time:16 mins read
  • Post category:Business Analytics
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What is Prescriptive Analytics?

Prescriptive analytics is a branch of data analytics that uses mathematical and computational algorithms to provide recommendations on the best course of action to take in a given situation. It is a type of advanced analytics that goes beyond descriptive and predictive analytics, which simply describe past events and predict future outcomes, respectively.

By using the optimisation technique, prescriptive analytics determines the finest substitute to minimise or maximise some equitable finance, marketing and many other areas. For example, if we have to find the best way of shipping goods from a factory to a destination, to minimise costs, we will use prescriptive analytics.

Data, which is available in abundance, can be streamlined for growth and expansion in technology as well as business. When data is analysed successfully, it can become the answer to one of the most important questions: how can businesses acquire more customers and gain business insight?

The key to this problem lies in being able to source, link, understand and analyse data. All companies need to address their data challenges to support their decision-making capabilities or may risk themselves in falling behind in this highly competitive landscape. Today, businesses are collecting, storing, analysing and interpreting more data as compared to the previous years, and this trend is continuing at an alarming rate to gain momentum.

According to many leading professors and researchers, this is the era of a Big Data revolution. In any case, it is not the amount of information that is progressive. Rather, the revolution has got something to do with the volume, variety and velocity of data.

Since a lot has been written on Big Data, we will focus on analytics, which will help companies transform the finance function by offering forward-looking insights and help them devise a solution appropriate for the optimal course of action, improve the ability to communicate and collaborate with other companies at a lower cost of ownership.

These transformative characteristics will lead to better performance improvements in business sectors. Prescriptive analytics go beyond predictions, workforce optimisations and decision options. It is usually used to analyse complex data to analyse huge complex data to forecast outcomes, offer decision options and show alternative business impact.

This method also consists of many scientific and mathematical methods used for understanding how alternative learning investments impact the bottom line. Moreover, this analytics can also help enterprises to take decisions on how to take advantage of a future scenario or reduce a risk in the future course of time and represent the implication of each decision option.

In real life, prescriptive analytics can automatically and continuously process new data to improve forecast accuracy and offer better decision options. For instance, prescriptive analytics can be utilised to profit healthcare key arranging. By utilising data analytics, one can harness operational information which includes population statistic patterns, financial information, and population health patterns, to a more exact arrangement and contribute future capital, such as, equipment usage and new facilities.

Functioning of Prescriptive Analytics

Utilising prescriptive analytics is a complex and time-taking process that investigates all viewpoints to sustain the decision-making process, including:

  • Identifying and breaking down every single potential choice.

  • Defining potential connections and associations between each of these choices with each other.

  • Identifying variables that could affect each of these choices (positively or negatively).

Prescriptive analytics handle processes for each of these viewpoints and maps out (at least one) potential results for each of the choices— bringing about a customised model. Elements sustaining the model, including information volume and quality, could affect the exactness of the model (as they would in descriptive and predictive analytics).

Prescriptive analytics utilises procedures like optimisation, game theory, simulation, and decision-analysis techniques. A procedure as opposed to a defined event, prescriptive analytics can constantly and consequently prepare new information to enhance predictive precision and give better decision choices.

Commercial Operations and Viability

Most organisations have concentrated intensely on finding the correct cost levels and working model to adequately empower them to develop. Prescriptive analytics add another measurement to operational and business adequacy by giving directors a chance to foresee what structures, messages and targets will yield ideal outcomes given the organisation’s remarkable parameters, and after that choose which way will give the biggest returns. There are numerous other business applications of prescriptive analytics, such as:

  • Optimising spend and rate of profitability (ROI) through exact customer profiling

  • Providing important data for brand planning and go-to-market procedures

  • Maximising campaign productivity, sales force arrangement and promotional activities

  • Predicting and proactively overseeing market events

  • Providing significant data for territory examination, customer deals and medical data

A one-estimate fits-all business model is no longer reasonable; the eventual fate of a focused sales model is focused on customised messaging.

Research and Innovation

Research and advancement are frequently speculating games, however, prescriptive analytics can be a noteworthy differentiator for any organisation occupied with Research and Development exercises in a competitive industry including:

  • Demonstrating, anticipating and enhancing results from item utility

  • Understanding sickness (or different zones of intrigue) patterns/ movement

  • Establishing ideal trial conditions through focused patient cohorts

  • Increasing customer adherence to the item and diminishing compliance

  • Understanding necessities for customised drug and different advancements

  • Determining and setting up focused items and interventions

  • Determining and setting up an ideal trial conditions through focused patient cohorts

Business Development

Understanding what new items are required, what differentiating components will make one item sell better than the other, or which markets are demanding which items are key zones for prescriptive analytics including:

  • Identifying and settling on choices about circumstances/rising ranges of unmet need ‰‰ Predicting the potential advantage

  • Proactively following industry trends and actualising techniques to get an advantage ‰‰ Exploiting data analytics to distinguish particular buyer populations and regions that ought to be focused on

  • Leveraging data analytics to distinguish key advancements for item improvement that will produce the biggest return for the investment

  • Identifying likely purchasers to cut business improvement costs altogether, and imagine a scenario where situations for items, markets and purchasers could be an unmistakable differentiator for developing organisations

Consumer Excellence

Prescriptive analytics can be utilised to improve purchaser excellence in a huge number of ways including:

  • Predicting what purchasers will need and settling on key choices that address those necessities.

  • Segmenting purchasers and recognising and focusing on custom-fitted messages to them.

  • Staying on top of competition and deciding (e.g., marketing, branding) about items that will prompt more desirable items and higher sales.

Corporate Accounts

Corporate account functions can immensely use prescriptive analytics to improve their capacity to settle on choices that help drive internal excellence and outer strategy.

Internal Excellence

The following points describe the internal excellence as follows:

  • Viability and direction for non-item related activities; what choices ought to be made and what is the effect.

  • Viability and direction for item related activities; what choices ought to be made and what is the effect.

External-Facing Key Direction

The following points describe the external-facing key direction as follows:

  • Utilising important data to demonstrate item esteem and build up a market valuation

  • Utilising examination to build up a target on coupon strategy

  • Recognising ideal price point alternatives and the effect of those choices on the income model for the item

  • Better understanding of the whole price cycle from rundown cost to repayment (counting all rebates and refunds) to inform the ideal pricing system

  • Utilising an important competitor data to build up estimation and get market access

Supply Chain

Prescriptive analytics can likewise furnish, supply chain capacities with an upper hand through the capacity to predict and make decisions in a few basic areas including:

  • Forecasting future demand and pricing (e.g., supplies, material, fuel and different components affecting cost to guarantee proper supply)

  • Utilising prescriptive analytics to illuminate stock levels, schedule plants, route trucks and different components in the supply chain cycle

  • Modifying supplier threat by mining unstructured information regarding value-based information

  • Better understanding historical demand examples and product course through supply chain channels, anticipating future examples and settling on choices on future state procedures

Governance, Risk and Compliance

Governance, risk and compliance are elements of expanding significance crosswise over practically every industry. Prescriptive analytics can help associations accomplish consistence through the capacity to anticipate upcoming dangers and settle on the proper mitigation choices.

Governance, risk and compliance are functions of increasing importance across almost every industry. Prescriptive analytics can help organisations achieve compliance through the ability to expect forthcoming risks and make proper mitigation decisions. Utilisation of prescriptive analytics in the region of governance, hazard and compliance incorporates:

  • Improving internal review effectiveness
  • Notifying third-party arrangement and management
  • Classifying patterns related with outlandish spend (e.g., total spend working on this issue of pharma)
  • Applying very much learned compliance controls

Difference Between Descriptive, Predictive and Prescriptive Analytics

Descriptive AnalyticsPredictive AnalyticsPrescriptive Analytics
Descriptive analytics is the process to look data statistically that what happened in the past. It is the process that focuses on predicting previous data and scenarios.Prescriptive analytics will provide a prediction or a forecast of what future trends in the business may look like.
It determines the details of past data. It tries to forecast on the basis of previous data and scenarios.Prescriptive analytics can automatically process new data to improve forecast accuracy.
It helps to make display performance and trends by chasing KPIs. It helps to make prediction for future.It helps to make decisions based on facts.
It is performed before diagnostic and predictive analysis to explain and précis the past data. It is performed by the business analysis.It is performed by expert opinions.

Tools Used for Prescriptive Analytics

As more data is created the tools which are used to store that data, structure, analysis and visualizations are considered as more essential for business purpose. There are several prescriptive analytics platforms tools in the market.

Some of the common prescriptive analytics tools are as follows:

  • Sisene: It is a most influential tool that provides users to create attractive, collaborative reports based on data. The features of this tool are user-friendly. Basically it is helpful for those who need a holistic view of data.

  • Rapidminer: This tool provides user an open source analytics platform that delivers AI and prescriptive analytics to businesses. In centralised platform, the graphical interface supports its users with all stages of predictive analysis.

  • Looker: The looker tool is based on browser platform that works from the database. It is mostly used for the purpose of choosing, designing and visualizations, also delivers a range of charts and graphs for the visualizations to users. This tool is generally used by the group of organisations.

  • Alteryx: It is a self-service platform that delivers several kinds of products for business needs. Alteryx also has a spontaneous drag-and-drop UI, which makes it enormously user-friendly.

Article Reference
  • Capehart, B. L., & Brambley, M. R. (2021). Automated Diagnostics and Analytics for Buildings 1st Edition, Kindle Edition

  • Foote, K. D. (2021, December 22). A Brief History of Analytics. DATAVERSITY. Retrieved March 31, 2023, from https://www.dataversity.net/brief-history-analytics/

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