AI & Forecasting: How does it work?

AI & Forecasting: How does it work?

Over the past few months, we've witnessed the emergence of exciting new applications that have transformed Artificial Intelligence (AI) from a futuristic concept into a practical and accessible technology for everyday use. While individuals are just beginning to embrace AI, it's businesses that stand to reap the most significant benefits by incorporating these powerful tools. In this blog post, we'll take a deep dive into the far-reaching impact of machine learning, a central component of AI, and explore how it empowers businesses to navigate their operations with greater foresight.

Understanding the Magic of Machine Learning

Machine learning operates by creating a process to "train" intricate models using data and code. These training processes draw from both internal organizational data and external market insights. The raw data is meticulously processed to align with the specifications of a machine learning model. As this process unfolds, the data can be categorized into two main groups: features and targets. Features encompass various data points ingested by a machine learning model, ranging from historical sales data to marketing expenditures. Conversely, targets encapsulate the specific data points that a machine learning model aims to predict, such as a forecast of sales for the next 365 days. The choice of which data points become part of the feature sets and which become part of the target sets is highly dependent on the specific problem that the machine learning model is addressing.

The Power of a Well-Trained Machine Learning Model

A well-trained machine learning model possesses the ability to identify intricate relationships, patterns, and anomalies within a wide array of datasets. For instance, it can capture the nuanced behaviors of consumers and predict fluctuations in sales throughout the year. Moreover, the model can generate predictions of future data for the company based on insights derived from historical patterns. These predictions equip analysts with the tools to create more accurate, efficient, and adaptable sales forecasts.

Data Scientists: The Architects of Insights

Data Scientists are the architects who harness a diverse range of data sources and swiftly respond to shifts in the business landscape. Consider the intricate patterns woven by consumer behaviors; these patterns serve as the threads that train machine learning models, enabling them to anticipate the ebb and flow of sales throughout the year. What's truly remarkable is their innate ability to seamlessly adapt to unforeseen variables, ensuring precision and relevance even in the face of the unexpected. These robust models empower analysts to quickly adapt to changes in demand, such as those caused by major weather events, enabling them to create more pertinent predictions. Additionally, predictions can be tailored specifically to individual customers, sales channels, or product lines, providing companies with the ability to make more intricate forecasts of their future.

The Role of Generative AI

Generative AI automates manual tasks, such as data entry, allowing analysts to work more efficiently. In the realm of forecasting, it eliminates the potential for human error that could skew the results of a forecast. With the assistance of AI, companies can redirect their efforts toward higher-level analysis and planning. A noteworthy case study at Microsoft Tokyo, initiated in 2018, found that while human-generated forecasts exhibited a variance of 1.8%, AI-generated forecasts had a variance of just 1.6%. These AI-generated forecasts were not only more accurate but also more efficient. What's more, they were created by a team of just two employees, compared to the 60 individuals required for the workforce-generated forecasts. As AI continues to advance, its effectiveness in delivering results has only improved.

Embracing AI for the Future

In today's rapidly evolving business landscape, the adoption of AI and machine learning is no longer optional—it's essential for staying relevant and adaptable. AI empowers analysts to make smarter decisions, navigate unexpected shifts, and enhance overall efficiency. Today, the key to success lies in establishing a solution that ensures effective AI utilization. This is where the DataMetrics BI Platform comes into play. Tailored to your company's unique needs, it leverages machine learning to boost sales forecast accuracy. Discover how our AI and machine learning initiatives can keep your business on the cutting edge of technology, elevating your decision-making capabilities along the way.

Lastly, we would like to highlight that this blog post was a collaborative effort between our intern, Ben Haggerty, during his internship, and two of our senior managers.

Collaborative Article
Collaborative Article

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