Predictive and prescriptive analytics are the two most significant parts of a successful data strategy. When predictive analytics help with finding plausible outcomes, prescriptive analytics comes up with better options to consider in terms of those outcomes.
Fremont, CA: Like any other industry of this decade, the warehouse industry has also recognized the potential of modern technologies, including AI anddata analytics. Using many of these technological tools, it is possible to attain a significant amount of valuable data. Data that are powerful enough to help in significant business growth and improved productivity. Thus, it is essential to implement a successful data strategy.
That being said, a successful warehouse data strategy will require a combination of predictive and prescriptive analytics. This can help businesses, even the small ones, to stay ahead in their competition. Even though the tasks carried out by each technology are different, it is important to leverage both the predictive and prescriptive analysis for developing a strategy rather than relying on one.
Predictive analytics is the technology where businesses can come up with outcomes or future consequences of a decision or an action. Statistics, historical figures, mined data, and recent up-to-date data are acquired to provide such information. Predictive analytics helps in advanced forecasts and can predict statistical models which can foresee future issues and outcomes. This way a better supply chain planning and management is possible. Using automated demand sensing, a predictive analytics solution can alert or notify of certain common issues like a potential obstacle in the supply chain, troubles on inventory levels, and model stock to avoid out-of-stock scenarios and also improve customer service. In addition, labor structures, fulfillment costs, and budgets can be calculated and analyzed to see whether they will impact future profit margins.
On the other hand, prescriptive analysis utilizes technologies like AI and ML to get a deeper perspective of future scenarios or an outcome. In warehousing, this technology helps to automate the entire process of analytics and reduces the risk of human errors. Prescriptive analysis ensures a better workflow, improved financial planning, and inventory management.
By utilizing these two technologies, the warehouse industry can save itself from possible future threats or disruptions. Since it is imperative to have a smooth supply chain, it is crucial to understand these potential obstacles and take necessary actions to avoid them. As data analytics and AI continue to grow, this industry will be able to use these technologies more effectively and thereby expand their capabilities and advance to a greater level within years.