In today’s business landscape, optimization is the key to success. Business process management (BPM) has emerged as a powerful tool to help businesses optimize their processes. There are two main types of BPM: predictive and prescriptive, based on predictive analytics and prescriptive analytics, respectively. Predictive BPM uses historical data and analytics to predict future outcomes, while prescriptive BPM provides recommendations on how to improve business processes.
Predictive and prescriptive BPM are valuable tools for businesses looking to save time, money, and resources while maximizing profits. By analyzing data, businesses can anticipate problems, take proactive measures to address them, and optimize their processes for greater efficiency and profitability. In turn, this can support businesses’ digital transformation efforts. In this blog, we will delve into the depths of predictive and prescriptive BPM, their advantages and disadvantages, and how they can be used together to optimize business processes.
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Predictive BPM is a type of BPM that uses predictive analytics based on past data to forecast outcomes. In fact, a Forbes report revealed that 86 percent of businesses using predictive analytics achieved significant revenue growth.
Therefore, BPM and analytics go hand in hand, allowing businesses to anticipate problems and take proactive measures to address them. For example, predictive BPM can be used to predict customer demand. By analyzing historical data on customer behavior, businesses can predict how much of a particular product will be needed in the future and plan accordingly. This can help businesses avoid stock shortages or overstocking, which can result in financial losses.
Another way predictive BPM can be used is to forecast sales. By analyzing historical sales data, businesses can predict how much revenue they will generate in the future. This can help businesses adjust their pricing strategy, marketing campaigns, and production processes to maximize profits.
Predictive BPM can also be used to predict equipment failures. By analyzing data on equipment performance, businesses can anticipate when a particular piece of equipment will need maintenance or repair. This can help businesses avoid costly breakdowns, minimize downtime and prepare for digital transformation.
Prescriptive BPM combines BPM and analytics with the help of machine learning to suggest the best course of action to optimize a business process. This type of BPM extends beyond predicting outcomes and instead provides recommendations on how to improve business processes based on prescriptive analytics. This is why prescriptive analytics is often referred to as the “future of data analytics”.
Take for instance, using analytics, a prescriptive BPM can be used to suggest the best pricing strategy. By analyzing data on customer behavior, competitor pricing, and market trends, prescriptive BPM can recommend the best price for a particular product or service.
Another way prescriptive BPM can be used is to recommend the best supplier. By analyzing data on supplier performance, delivery times, and prices, BPM and analytics can be combined to prescribe the best supplier for a particular product or service.
Prescriptive BPM can also be used to recommend the most efficient route for deliveries. By analyzing data on traffic patterns, road conditions, and delivery schedules, prescriptive BPM can recommend the most efficient route for deliveries. This can help businesses save time and resources on transportation.
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| Predictive BPM | Prescriptive BPM |
Definition | Uses historical data and analytics to predict future outcomes | Uses data analytics and machine learning to suggest the best course of action to optimize a business |
Purpose | Anticipate problems and take proactive measures to address them | Improve business processes by providing recommendations on how to optimize the process |
Benefits | Helps businesses anticipate problems and take proactive measures | Provides specific recommendations for optimizing the process, leading to greater efficiency and profitability |
Challenges | Limited to historical data and may not be accurate in predicting future outcomes | Requires high-quality data and expertise in machine learning and data analytics |
Examples | Predicting customer demand, forecasting sales, predicting equipment failures | Suggesting the best pricing strategy, recommending the best supplier, recommending the most efficient route for deliveries |
Best use cases | Situations where historical data is abundant and can be used to predict future outcomes | Situations where data analytics and machine learning can be used to provide specific recommendations for optimizing the process |
Predictive and prescriptive BPM have different advantages and disadvantages. By using predictive analytics for BPM, businesses can anticipate problems and take proactive measures to resolve them as soon as possible. It can help businesses avoid stock shortages, overstocking, and equipment breakdowns. However, predictive BPM is limited in that it only predicts outcomes and does not provide recommendations on how to improve business processes.
On the other hand, prescriptive BPM provides recommendations on how to improve business processes. It can suggest the best pricing strategy, supplier, or delivery route. However, prescriptive BPM is limited in that it requires a large amount of data to work effectively. It may also require significant investments in technology and personnel to implement.
Despite their differences, predictive analytics and prescriptive analytics can be used together to optimize business processes and develop a digital transformation strategy.
Predictive BPM can be used to anticipate problems and provide input for prescriptive BPM. Prescriptive BPM can then provide recommendations on how to improve business processes based on predictive data. Predictive analytics and prescriptive analytics can also be leveraged in BPM practices to navigate the infrastructure, insight and resources required for digital transformation. Together, these two types of BPM can help businesses save time, money, and resources while maximizing profits.
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In conclusion, predictive and prescriptive BPM are essential tools for businesses looking to optimize their processes and maximize profits. Predictive BPM helps businesses anticipate problems and take proactive measures to address them, while prescriptive BPM provides recommendations on how to improve business processes. While each type of BPM has its own advantages and disadvantages, they can be used together to optimize business processes.
The key to growth in today’s business landscape is optimization. BPM and analytics can help businesses achieve that goal. By analyzing data, businesses can make informed decisions, improve their processes, and save time, money, and resources. It is important for businesses to identify and analyze the differences between predictive and prescriptive BPM and to determine which type is best for their needs. Moreover, shifting perspectives from predictive vs prescriptive BPM to utilizing a combination of both can mean superior outcomes. With the right BPM strategy in place, businesses can achieve greater efficiency, profitability, and success.
