5 Top Prescriptive Analytics Solutions Impacting the Manufacturing Sector

We analyzed 132 prescriptive analytics startups. eTrack, Daitum, Germanedge, CodeData & FourDotOne develop 5 top solutions you should watch out for. Learn more in our Global Startup Heat Map!

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups working on innovative solutions for the manufacturing sector. As there is a large number of startups working on a wide variety of solutions, we want to share our insights with you. This time, you will discover 5 promising prescriptive analytics startups.

Heat Map: 5 Top Prescriptive Analytics Startups

Using our StartUs Insights Discovery Platform, covering 1.379.000+ startups & scaleups globally, we looked at innovation in the field of advanced manufacturing. For this research, we identified 132 relevant solutions and picked 5 to showcase below. These companies were chosen based on a data-driven startup scouting approach, taking into account factors such as location, founding year, and relevance of technology, among others. Depending on your specific criteria, the top picks might look entirely different.

The Global Startup Heat Map below highlights 5 startups & scaleups developing innovative solutions for prescriptive analytics. Moreover, the Heat Map reveals regions that observe a high startup activity and illustrates the geographic distribution of all 132 companies we analyzed for this specific topic.


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Which startups develop the other 127 solutions?


eTrack – Prescriptive Maintenance (RxM)

Predictive maintenance systems combine the Internet of Things (IoT) sensors and artificial intelligence (AI) to predict machine failures. This helps manufacturers to keep spare parts ready and reduce downtime. However, this doesn’t inform manufacturers about actions that would potentially lengthen the lifetime of their machines. To meet this need, startups are integrating prescriptive maintenance in predictive maintenance (PdM) solutions.

eTrack is a US-based startup that develops a platform for prescriptive maintenance. The startup’s solution combines predictive and prescriptive analytics to eliminate downtime due to machine failure. The platform monitors component failures, overheating, hydraulic failures, temperature leaks, and other faults in heavy machinery. It also provides operational insights to improve business intelligence for operators and managers.

Daitum – Operations Optimization

Optimization of factory operations enables improvements in productivity by improving the efficiency of resources and time management. Manufacturing units also need to deal with complex and uncertain situations, such as demand fluctuations and resource scarcity. Startups are working on prescriptive analytics solutions that combine mathematical and machine learning (ML) algorithms to mitigate various risks. Prescriptive analytics solutions have an immediate impact on manufacturing baseline and increase return on investment (RoI).

Australian startup Daitum offers decision analytics for operations optimization. The startup’s software-as-a-service (SaaS) optimization platform provides a rich library of prescriptive analytics and solution techniques. The platform enables non-technical users to solve complex problems in an Excel environment. For manufacturing, it ensures that all materials, equipment, and human resources are available at the right time and place. Daitum’s solution also helps managers with capacity planning, maintenance planning, and capital expenditures (CAPEX) decisions.

Germanedge – Advanced Planning & Scheduling (APS)

Traditional manufacturing methods allocate materials and production capacity to plan and schedule production. However, this isn’t sufficient to meet sudden changes in demand or resource availability. Startups are working on prescriptive analytics based advanced manufacturing solutions for APS. In addition to responding to resource constraints, these solutions enable manufacturers to make-to-order, as well as efficiently produce multiple products in the same facility.

Germanedge is a German startup that develops RxM software solutions for Industry 4.0. The startup’s digital platform provides a holistic view of the entire production process. Germanedge offers advanced planning & scheduling for supply chain, production, laboratory, and data management. The platform provides transparency in logistics and other operations of manufacturing companies. For instance, the RxM software enables full automation of supply chain processes in real-time, such as material procurement.

CodeData – Real-Time Asset Performance

Prescriptive analytics integrates predictive maintenance and operational data modeling to increase the efficiency of asset management decision-making. Startups are developing prescriptive analytics solutions that derive information from different business information systems. Moreover, these provide real-time recommendations that improve asset performance in manufacturing.

The US-based startup CodeData develops an applied machine learning platform for real-time asset performance recommendations. MAKORO uses AI to offer predictive insights and speed up decision making in manufacturing. The integrated platform boosts, as well as connects, plant performance, maintenance efficiency, and workforce productivity. The data-driven solution enables deep domain industrial applications by helping businesses leverage the power of analytics.

FourDotOne – Asset Behavior Monitoring

As a consequence of advances in asset performance solutions, there is considerable growth in condition-based monitoring (CBM) applications. These solutions use equipment data to allow manufacturers to interpret past behavior to predict future outcomes. Building on that, startups offer systems that provide timely and actionable suggestions to reduce machinery and equipment downtime and mitigate the risk of damage.

FourDotOne is a Turkish startup that provides solutions for modeling and forecasting the behavior of manufacturing systems and processes. The startup’s solution employs machine learning and data analytics to continuously monitor equipment health. On problem identification, the automated systems immediately implement the required actions. Further, the solution is available as an upgrade for existing predictive maintenance systems and increases production performance.

What About The Other 127 Solutions?

While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence and enable you to achieve your goals faster. The 5 prescriptive analytics startups showcased above are promising examples out of the 132 we analyzed for this article. To identify the most relevant solutions based on your specific criteria, get in touch.

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