Who are the key innovators in demand forecasting applications in the technology industry?

The technology industry continues to be a hotbed of innovation, driven by the rapid emergence and widespread adoption of transformative technologies such as artificial intelligence (AI), the Internet of Things (IoT) and robotics, such as: Technology is becoming more important. Big data analytics, predictive analytics, data visualization, machine learning, and more. Demand forecasting applications are of great importance in various industries due to the need for accurate demand forecasting, increased data availability, advances in machine learning algorithms, and the potential to optimize supply chain operations, inventory management, and decision-making processes. increasing sex. In the last three years alone, more than 3.6 million patents have been filed and granted for him in the tech industry, according to GlobalData’s report on “Innovation in Artificial Intelligence: Demand Forecasting Applications.”

However, not all innovations are the same, nor do they follow a constant upward trend. Instead, their evolution takes the form of an sigmoidal curve that reflects a typical life cycle from early emergence to accelerated introduction and finally to reaching stable maturity.

Identifying specific innovations, especially those in the emerging and accelerating stages, is essential to understanding the current level of adoption and the expected future trajectory and impact.

Over 300 innovations shape the tech industry

GlobalData’s Technology Foresights uses an innovation strength model built on over 2.5 million patents to plot the S-curve of the tech industry, with more than 300 areas of innovation shaping the industry’s future.

Within emerging The innovation stage, finite element simulations, ML-enabled blockchain networks, and generative generative networks (GANs) are disruptive technologies that are in the early stages of application and should be followed closely. Demand forecasting applications, intelligent embedded systems, and deep reinforcement learning are some of them. To accelerate An area of innovation where adoption is steadily increasing.in mature Innovative areas are wearable physiological monitors and smart lighting, which are now well established in the industry.

Artificial intelligence innovation S-curve in the tech industry

Demand forecasting applications are a key innovation area for artificial intelligence

Demand forecasting applications include software programs and systems designed to forecast customer demand for products and services. These applications employ various data sources, statistical analyses, and algorithms to generate accurate forecasts. The purpose of demand forecasting is to help companies anticipate customer requirements and effectively strategize their operations.

GlobalData’s analysis also reveals the companies at the forefront of each innovation area and assesses the potential scope and impact of patent activity across different applications and geographies. According to GlobalData, there are more than 310 companies involved in developing and adapting demand forecasting applications, ranging from technology vendors, established technology companies and start-ups.

major players Demand forecasting application – disruptive innovation in technology industry

‘Application Diversity’ measures the number of different applications identified for each relevant patent and broadly divides companies into ‘niche’ or ‘diverse’ innovators.

“Geographic coverage” refers to the number of different countries in which each relevant patent is registered, reflecting the breadth of intended geographic application, ranging from “global” to “local” .

Number of patents related to demand forecasting applications

Source: GlobalData Patent Analytics

IBM is a leading patent applicant for demand forecasting applications. The Company’s patents are directed to a method, computer program product, and system for providing cognitive guidance services to a group of excursion participants using the initial route planned by enrollment of the participants and environmental information along the initial route. Related. During the excursion, the participants’ real-time sensory data and environmental changes are collected and relayed to the cognitive guidance engine, where real-time multi-objective optimization is modeled and performed.

Participants will be regrouped according to the purpose of the excursion, depending on their level of interest and the circumstances of the environment at a particular stage of the excursion. The participants are formed into subgroups for each objective, and each subgroup selects a new route from the set of optimal solutions. During the excursion, the cognitive guidance engine iteratively optimizes the route according to the real-time sensory data it receives and the purpose of the excursion.

Other prominent patent applicants in this area include Microsoft and Fanuc.

In terms of geographic deployment, Illumina leads the pack, followed by Turck duetec and ELMOS Semiconductor. In terms of application diversity, Amdocs takes the top spot, followed by Talkdesk and Aptiv.

Demand forecasting applications enable businesses to make informed decisions, optimize resource allocation, and effectively meet customer demand. By providing accurate forecasts, these applications help organizations streamline operations, minimize risk, and improve overall business performance.

To better understand how artificial intelligence is transforming the tech industry, visit GlobalData’s latest Thematic Research Report on Artificial Intelligence (AI) – Thematic Intelligence.