get in touch

SAP implementation services: 11% reduction in costs and increased revenues

SAP implementation services for oil and gas industry

SAP implementation services: 11% reduction in costs and increased revenues

By integrating SAP S/4HANA, our team has modernized outdated enterprise management systems and the client’s operational processes, as well as streamlined purchasing, inventory management, transportation, financials, and analytics.

#ERP

#Enterprise

#DataManagement

Client*

An industrial corporation which specializes in oil and gas investigation, extraction, refining, and transportation.

*We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

Project in numbers

duration

33 months

team

31 specialists

The team involved in the project

industry

Enterprise

solution

SAP S/4HANA integration

technologies

SAP S/4HANA, SAP GUI, SAP HANA

21 x SAP consultants

1 x Project manager

1 x Project architect

2 x ABAP developers

hire the team

Challenge

The client‘s business was rapidly expanding and faced difficulties with the legacy software. As a SAP implementation partner, our team had to address these issues so that the software could meet the growing demands of the enterprise.

Objectives

Rebuild legacy software

Foster visibility and control over the value chain

Solution & functionality

Our team proposed deploying an SAP business suite to automate logistics, finance, HR management, reporting, and more. Utilizing SAP Activate, we managed to integrate best practices and methodologies for smooth S/4HANA implementation.

Financial accounting module (FI)

Our team deployed a finance module to manage transactions within the client’s businesses, covering general ledger and asset management, as well as accounts payable and receivable, financial reports, and bank accounting. All financial activities, income, and expenditures are carefully recorded in the module, so they stay compliant with global accounting standards.

Funds management module (FM)

Using this module, the client can utilize budget resources efficiently. The module enables controlling revenue and expenditures, tracking funds according to financial constraints, and preventing budget excesses, while simultaneously allowing managers to change releases, supplements, returns, and transfers.

Sales and distribution module (SD)

The module houses customer and sales data, encompassing every facet of the sales cycle. Additionally, utilizing it with Materials Management (MM) and Financial Accounting (FI) modules helps to facilitate sales transactions, oversee orders, devise pricing tactics, and evaluate sales efficacy.

Controlling module (CO)

As the module documents the essential data, stakeholders are enabled with efficient decision-making, supervision, and enhancement of all corporate operations. Additionally, the module compares actual data with the initial plan so that it can be adjusted for a short-term or a long-term period.

Human resources module (HCM)

The last not least important module was integrated to oversee and bolster the client’s workforce — staff administration, organizational oversight, time management, payroll processing, perks, and self-service functionalities for employees, so that human resources are applied to their full potential.

Business intelligence module (BI)

We designed this module for efficient data analysis and reporting, giving the client the possibility to get data from SAP and non-SAP platforms, then convert them into valuable insights. Functionality allows a range of possibilities, like data storage, modeling, creating reports and dashboards, as well as setting key performance indicators (KPIs).

Materials management module (MM)

The module helps to oversee procurement, stock, and warehouse operations along the supply value chain. This implementation ensures timely availability of materials, optimizes inventory levels, and streamlines procurement procedures.

Results and business value

With SAP S/4hana implementation, we replaced the obsolete system with cost-effective solutions that enabled the client to diversify workflows, regain data integrity, visibility and controllability over business processes.

Benefits for client

With SAP S/4HANA implementation, our team transformed the client’s operational processes, covered project administration, inventory, sales, distribution, and financial management. We improved the client’s operational workflows, facilitating smooth data transmission and interaction among various divisions, thereby enhancing coordination and teamwork throughout the organization.

14%

increase in total revenue

11%

reduction in production cost

Related cases

see all case studies

We appreciate your interest in Timspark

    IIoT platform for a manufacturing company: 20-30% boost in productivity

    IoT PLATFORM

    IIoT Platform for a Manufacturing Company: 20-30% Boost in Productivity

    The client turned to Timspark for IoT application development from scratch. Our team was supposed to build a smart web platform that would contribute to the whole production management ecosystem in one of the client’s factories, optimize its working processes, and improve productivity.
    #IoT
    #Manufacturing
    #WebDevelopment

    Client*

    The client is a large manufacturing enterprise in the EU, producing machine equipment for numerous partners worldwide.
    *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

    Project in numbers

    duration
    2020 — ongoing
    team
    10 specialists

    The team involved in the project

    industry
    Manufacturing
    solution
    Industrial IoT platform
    technologies
    C#, ASP. NET MVC, .NET Core 3, .Net 5, Web API, JavaScript, JQuery, TypeScript, Azure

    4 x Full-stack developers

    2 x QA engineers

    1 x UI/UX designer

    1 x Project manager

    1 x Solution architect

    1 x DevOps engineer

    hire the team

    Challenge

    Create an IoT monitoring platform that would manage all processes at the enterprise by gathering, analyzing, storing, and processing data.

    Related objectives

    Build a smart factory application
    Implement ML algorithms
    Increase the client’s production efficiency

    Solution & functionality

    The team built an IoT monitoring platform with several operational modules that help oversee processes and operations within the client’s enterprise.

    Predictive maintenance module

    Every piece of equipment is equipped with various sensors. They continuously monitor and transmit real-time data regarding the machinery’s temperature and vibration levels. The application sends notifications to operators on any unusual temperature rise, preventing automatic shutdowns. Afterwards, algorithms scrutinize the maintenance history and suggest an out-of-schedule maintenance check.

    Environmental control module

    Sensors identify diverse factors that influence the well-being and security of the factory workforce. Among them are humidity, temperature, and noise intensity. Additionally, the application supervises air quality and emission levels in industrial spaces. If these standards go over the limit, the system alerts operators and provides algorithms to address the issue.

    Manufacturing effectiveness module

    The platform gathers data from sensors for every production division and machine and analyzes their OEE (overall equipment effectiveness). Users can see what critical factors influence OEE levels, detect potential issues, and resolve them. What is crucial is that the application collects performance metrics over a specified timeframe and helps operators see how key indicators progress.

    Quality assurance module

    With the IIoT platform, users can monitor the quantity and quality of components produced during one shift or any specified period. Also, they can have access to comprehensive details about each item, like production line, the count of rejected pieces, statistics, and more. Leveraging this information, system operators can spot production trends and the reasons behind elevated scrap rates and implement suitable measures to enhance the quality performance metrics.

    Results and business value

    Timspark has leveraged IoT for manufacturing and delivered a web application that monitors all the production processes, thus enhancing efficiency and mitigating risks. Also, our team provided maintenance and support services for the IIot platform they built. The client is eager to introduce new features and scale IoT for enterprise by applying it to other facilities.

    Higher productivity

    Streamlined processes and management

    Related cases

    see all case studies

    We appreciate your interest in Timspark

      How to Use Computer Vision in Agriculture for Detecting Diseased Banana Leaves

      Computer Vision in Agriculture

      How to Use Computer Vision in Agriculture for Detecting Diseased Banana Leaves

      Our team developed a computer vision software that checks banana seedling leaves for damage all on its own. We also use advanced analytics to help our client reduce crop loss probability.

      #AI

      #WebDevelopment

      #ComputerVision

      Client*

      Top banana seeding supplier in the world

      *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

      Project in numbers

      duration

      4 months

      team

      5 specialists

      The team involved in the project

      industry

      Agriculture

      solution

      Computer vision software for plant disease detection

      technologies

      Python, Pandas, Numpy, Pytorch, Streamlit, Opencv

      1 x Lead Data Scientist

      1 x Data Scientist

      1 x Data Engineer

      1 x Project Manager

      1 x QA

      HIRE THE TEAM

      Challenge

      The client was concerned about the possibility of using computer vision in agriculture to detect plant disease and prevent crop loss automatically. On the tech side of things, our team faced a scarcity of data available to train AI-based computer vision solutions.

      Solution & functionality

      We came up with a solution to place cameras in the greenhouse, putting them up high and to the side. These cameras take periodic snapshots of banana seedlings. The client can adjust the frequency of these snapshots.

      Deep learning for object detection and classification

      Timspark made a computer vision software module that grabs pictures of the leaves spotted by the camera. These pictures later get sent to the deep learning classifier model, which has a closer look at images and tells if a banana leaf is healthy or damaged. It can even figure out what kind of damage it is.

      Plant condition reports and analytics

      Our computer vision software checks out the uploaded pictures and generates a PDF report with the results. It further gives recommendations on what to do next based on the analyzed data.

      Results and business value

      Timspark didn’t just create and tweak the classifier model; we did it thoroughly, making sure it fits the project’s special needs and industry standards. The client is satisfied with the outcome and still partners with us on more projects to facilitate computer vision in agriculture.

      Benefits for client

      Thanks to computer vision services, the customer has successfully put this technology to work and significantly cut down on banana seedling losses.

      Related cases

      see all case studies

      We appreciate your interest in Timspark

        Computer Vision Solution for Effective Advertising Placement

        computer vision device

        Computer Vision Solution for Effective Advertising Placement

        Our team developed an on-premises device based on AI technologies for detecting individuals and showcasing advertisements on DOOH displays in transportation or outdoor locations.

        #AI

        #WebDevelopment

        #Ecommerce

        Client*

        The client is a world-leading provider of comprehensive visual technology solutions.

        *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

        Project in numbers

        duration

        11 months

        team

        5 specialists

        Team involved in the project

        industry

        E-commerce

        solution

        Computer vision and artificial intelligence device for target audience analysis

        technologies

        Python, Pytorch, Cnvrg.io, AWS SageMaker, GCP Vertex AI, Fastdup, Pandas, Numpy, Scipy.

        1 x Lead Data Scientist

        2 x Data Scientists

        2 x Data Engineers

        HIRE THE TEAM

        Challenge

        The fundamental idea was to create a device harnessing AI technologies for analyzing captured images, discerning the audience’s average attributes, and enabling the presentation of targeted advertising.

        Related objectives

        Deploy the computer vision model on edge devices with limited GPU and RAM

        Train the AI computer vision model with labeled data

        Solution & functionality

        In collaboration with the client’s team, Timspark created a compact on-premises computer vision device that can capture and analyze visual data.

        Machine learning model training for successful object recognition

        The team developed and fine-tuned the classifier model to meet the project’s unique requirements. The model analyzes received images, determines the average class among all attributes of captured objects, and subsequently identifies the target audience for the advertisement.

        Deployment on Jetson Nano and Jetson Xavier

        To address challenges linked to the limited memory and slow data processing, the model was transformed into ONNX and TensorRT formats, ensuring its seamless deployment on edge devices such as Jetson Nano and Jetson Xavier.

        Results and business value

        Our specialists successfully developed a classifying model that detects and tracks individuals within the camera’s field of view. The model analyzes the captured visual data, accurately identifying selected class among all attributes, and displays targeted advertisements on nearby screens in accordance with the specified class request.

        Benefits for client

        The client successfully applies the computer vision software to show the advertisement effectively to the relevant audience.

        Based on the successful results, we are going to improve the model further in our ongoing collaboration.

        Related cases

        see all case studies

        We appreciate your interest in Timspark

          Health Management App: Cross-platform AI-driven Solution for Asthma Treatment

          AI/ML-based app

          Health Management App: Cross-platform AI-driven Solution for Asthma Treatment

          The team built a user-friendly asthma care app for iOS and Android platforms from the ground up, seamlessly integrating AI and ML algorithms.

          #healthcare

          #ai #ml

          #mobiledevelopment

          Client*

          A European company focusing on developing digital products.

          *We cannot provide any information about the client or specifics of the case study due to non-disclosure agreement (NDA) restrictions.

          Project in numbers

          duration

          12 months

          team

          6 specialists

          efforts

          1920 hours

          Team involved in the project

          industry

          Healthcare

          solution

          Asthma management application

          technologies

          Android, iOS, Python, Dart, Flutter, Django, PostgreSQL

          1 x Project Manager

          2 x Flutter Developers

          1 x DevOps Engineer

          1 x Python Developer

          1 x QA Engineer

          HIRE THE TEAM

          Challenge

          The main goal was to develop a cost-effective care solution harnessing AI and ML algorithms that would assist both medical practitioners and individuals with asthma in treatment goals.

          Related objectives

          Develop the app’s functionality and design

          Integrate AI and ML algorithms

          Implement a set of features (calendar, reminders, statistics)

          Solution & functionality

          Our team developed an innovative asthma management app that harnesses the power of AI and ML algorithms and helps users monitor their symptoms, inhaler usage, environmental triggers, and have a better control over their health.

          Two users mode

          The app offers two user modes: patient mode and administrator mode.

          The end-users of the application are patients who have asthma. They can actively interact with the platform to ease the management of their symptoms. This involves inputting details about their primary and emergency inhalers, setting up daily reminders, and other functionalities.

          Administrators are responsible for keeping the machine learning algorithm up-to-date with relevant data. They also ensure that the inventory of available inhalers within the application is consistently maintained. This guarantees that patients always have access to their prescribed medications.

          Personalization: tracking, reminders, recommendations

          In their personal profiles users can perform multiple functions that help evaluate and monitor the state of their health.

          • Users can fill in the information about the primary and secondary inhalers, customize reminders and notifications to create a personalized schedule.
          • Users get an overview of the day, like possible health risks, symptoms triggers, and the list of inhalations planned.
          • In the personal dashboard, users can access the Calendar section with the weekly and monthly statistics.

          AI/ML-driven analysis and predictions

          Thanks to artificial intelligence and machine learning algorithms implemented in the app, users get accurate analysis and predictions of their health state.

          • Based on various factors like weather, humidity, and others, the app can evaluate the risk of asthma attacks.
          • With submitted audios, the machine learning algorithm analyzes how patients use their inhalers and produces a summary and recommendations for further fine-tuning and usage.

          Results and business value

          Our team launched the MVP in 2 months, developing an innovative, user-friendly mobile solution for asthma management.

          Personalized care

          Symptoms control

          User-friendly interface

          Reduced hospitalization cases

          The application tracks the patient’s condition, analyzes the information about the inhalations the patient takes, and provides personalized guidelines, alerts, and reminders based on the information provided.

          Related cases

          see all case studies

          We appreciate your interest in Timspark

            Let’s build something great together

              Let’s build something great together

                Let’s build something great together

                  Let’s build something great together

                    Let’s build something great together

                      Let’s build something great together