Predictive analytics in manufacturing:
top use cases and adoption tips

Predictive analytics in manufacturing: top use cases and adoption tips

The role of predictive analytics in manufacturing

Predictive AI-driven analytics gives you valuable insights from the complex and diverse data you collect to recognize future development opportunities and notice potential disruptions before they affect production. The AI-empowered solutions we provide enable you to find dependencies that are difficult to detect with traditional analytics.

the estimated value of the manufacturing predictive analytics market by 2026

Allied Market Research

Asia-Pacific region to show the highest CAGR between 2018-2026

Allied Market Research

Top 7 use cases of predictive analytics in manufacturing

Demand forecasting

    Demand forecasting relies heavily on historical data on supply levels, material costs, purchasing trends, consumer buying habits, and delivery conditions. Demand forecasting will help you to:

    • Calculate the number of products to manufacture
    • Forecast possible sales and deliveries
    • Determine out-of-stock items 
    • Identify trendy products in a given period
    • Allocate resources
    • Plan budgets

    Predictive analytics services we offer

    Our artificial intelligence experts provide comprehensive assistance to companies that want to implement AI-enabled predictive analytics solutions for manufacturing or want to improve an existing one. Our extensive services range from analyzing business needs to selecting the best strategy and technology to implement the solution.


    We develop ready-to-implement MVP and enterprise AI-enabled predictive analytics tools to help our clients make data-driven decisions quickly, solve business problems and gain an edge over the competition. Itransition services include requirement identification, data management, AI model development as well as customization, integration, and further support.

    Ready to leverage predictive analytics capabilities?

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    Client spotlight: our success stories

    BI for incident management

    Incident analytics

    around the globe

    We helped a risk management and security company create a universal BI solution that processes and visualizes different types of incident reports around the globe. The solution increased the satisfaction of existing customers and attracted a new major corporate client.

    Risk management for a nuclear plant


    risk assessment

    Itransition developed a cross-platform risk assessment and management system for a nuclear power plant. By detecting risky events in a timely fashion, the solution enabled experts to prevent their escalation and significant impact on the enterprise manufacturing operations.

    Our service delivery pipeline


    Problem definition

    Identifying business needs and user expectations

    Assessing customer’s technical environment

    Defining the solution’s functional and non-functional requirements


    Data analysis

    Conducting exploratory analysis of available data sources, both customer-owned and from public databases



    Designing the solution’s architecture

    Defining the implementation strategy and optimal technology stack

    Setting the project’s timeline and budget



    Data preprocessing, including data cleaning, annotation, and transformation

    Defining the solution’s evaluation criteria

    Developing the solution in-line with the defined implementation strategy


    Integration and deployment

    Integrating the solution into the customer’s infrastructure

    Launching the solution into operation


    Support and maintenance

    Further retraining of the predictive analytics solution using user feedback and new data from the production environment

    Top 5 predictive analytics platforms for manufacturing

    Key features
    • Customizable dashboards
    • Easy sourcing and data transformation with Power Query
    • Extracting insights from large datasets
    • Navigation pane
    • Re-using datasets across different reports and dashboards
    • Integration with other Microsoft Products
    • Excel integration
    • Low costs
    • Constant updates and innovations
    • Clear learning curve
    • Advanced data cleansing options are limited
    • Limited information sharing
    • Big data analysis is challenging for beginners

    Free trial

    for two months

    Power BI Pro

    $9.99 per user/month

    Power BI Premium

    $20 per user/month

    Power BI Premium

    $4,995 per capacity/month

    Benefits of predictive analytics in manufacturing

    1 Reduced costs

    Predictive analytics optimizes manufacturing processes, identifies quality failures in advance, and enables faster remedial action to minimize consequences. Advanced analytics and condition monitoring can help businesses minimize downtime and lost productivity by alerting them to potential equipment problems.

    2 Spotted inefficiencies

    Predictive analytics sifts through vast amounts of historical and real-time data much faster and more accurately than humans do. As a result, AI-enabled quality analytics can spot recurring errors and predict potential anomalies or equipment failures to help a manufacturing organization avoid production line halts by scheduling timely repairs and equipment replacements.

    3 Streamlined growth

    The maximized usage of available resources improves product quality, strengthening the company’s competitive advantage. Predictive software solutions identify actionable ways to optimize product development strategy, efficiently manage operations, make informed decisions, and maintain growth.

    4 Increased revenue

    AI-enabled analytics uses data to predict critical future results and revenue based on market conditions and current sales. Companies incorporating predictive analytics can reap significant value by reducing production costs, identifying emerging opportunities, and quickly responding to changing trends.

    5 Enhanced performance

    Predictive analytics can help you streamline various production processes, from inventory management to sales and marketing operations. AI-driven predictive analytics also enables organizations to optimize workforce management, improving employee engagement and motivation and, thus, boosting their performance.

    6 Real-time insights

    Predictive analytics allows you to obtain and compare data from historical production activities with actual production activities. It gives manufacturers a comprehensive source of real-time recommendations and alerts to improve operations, enabling company personnel to make data-driven decisions.

    Learn how to get more out of your data with Itransition

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    Adoption barriers and how to overcome them




    Collecting the right data



    Collecting and using inaccurate or incomplete information will lead to poor results that are not useful for end users and managers. To prevent this problem, you can establish robust data collection targeted for a particular purpose and streamline quality assurance procedures. If you have just started implementing predictive analytics, the first step is to define a period and collect as much data as possible. Then, analyze all the collected data and select the data sets applicable to your use cases.


    Lack of a clear strategy for using predictive analytics



    Many organizations want to put predictive analytics to work but aren't 100% sure how to use it. Before choosing a solution, clearly define your company's goals and objectives, and determine the estimation metrics. Analyze your business's needs and specific pain points to identify the most relevant use cases for a future solution.


    Lack of in-house expertise



    Predictive analytics can be complex for inexperienced employees. You might need help selecting, installing, customizing, and maintaining the solution. A professional technological partner can help you seamlessly integrate predictive analytics tools with applications used in your firm, such as an ERP platform, and organize training to enable your employees to adjust to predictive analytics quickly.

    Predictive analytics drives the future of manufacturing

    Predictive analytics helps manufacturers to reduce maintenance costs and improve operational efficiency and product quality. In addition, it enables leveraging the existing data by integrating and visualizing it to predict trends and act on opportunities before they manifest. If you want to select and apply predictive analytics in your manufacturing business successfully, Itransition experts are ready to help.