Enterprise Asset Management Consulting Services
Enterprise asset management (EAM) consulting serves to digitalize asset management for maximized ROA. In software development since 1989, ScienceSoft designs, develops, implements, and supports EAM solutions for tech-driven asset planning and optimization.
Go-to Functionality Modules and Integrations for EAM Solutions
Asset tracking and monitoring
- Up to 50% reduced asset downtime
- Up to 24% asset productivity increase
due to optimized asset usage, minimized asset loss and rationalized asset expenditure.
Asset maintenance management
- Up to 25% reduced maintenance costs
- Up to 70% fewer asset breakdowns
- Up to 12% fewer scheduled repairs
due to optimized asset maintenance and real-time monitoring of asset operation.
Asset planning and optimization
- Up to 21% OEE increase
- Up to 5% reduced capital investment
due to optimized asset utilization scenarios and asset investment planning.
Key Integrations for EAM Software
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ScienceSoft recommends: to reduce time-to-insight, start with developing an MVP with the minimal optimal feature set to address most acute problems and then, if viable, extend the functionality with more advanced capabilities. |
More on enterprise asset management solution functionality, integrations, success factors and ROI in our enterprise asset management software guide.
Enterprise Asset Management Investments
The cost and duration of the EAM solutions ScienceSoft implements and supports depends on multiple factors, including:
- Types of assets, their number and growth rate.
- The number and diversity of the functional modules of EAM software. If case-specific functionality is required (e.g., asset condition monitoring, ML-based asset maintenance cost forecasting, real-time object recognition).
- Number and complexity of systems to integrate with (custom and off-the-shelf software, hardware (barcodes, tags, chips, etc.).
- Complexity of the required asset analytics reports and dashboards.
- Solution availability, performance, security, latent capacity and scalability requirements.
- Number of platforms supported (web, mobile, desktop).
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ScienceSoft recommends: to reduce enterprise asset management implementations costs, consider:
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Solid experience in advanced technologies
- 34 years in data analytics, data science, ML and AI.
- 18 years in BI solutions and data visualization.
- 12 years in IoT (expertise in all components of an asset tracking ecosystem, including IoT data capture, storage and analysis).
- 10 years in big data.
- 10 years in image analysis, including defect recognition and machine vision-supported remote monitoring.
Strong team of consultants
- 25+ business analysts with hands-on experience in manufacturing, logistics, oil & gas, telecom, retail, healthcare, professional services.
- 20 + software architects.
- In-house Project Management Office experienced in complex projects on software integration and elaborate enterprise systems, e.g., ERP solutions with 500+ functions.
Proven tech capabilities
- Partnerships with Microsoft, Amazon, and Oracle.
- ISO 9001 and ISO 27001-certified assuring the quality of the services provided and the security of our customers' data.
The Financial Times Includes ScienceSoft USA Corporation in the List of the Americas’ Fastest-Growing Companies 2023
For the second year in a row, ScienceSoft USA Corporation ranks among 500 American companies with the highest revenue growth. This achievement is the result of our unfailing commitment to provide high-quality IT services and create best-value solutions that meet and even exceed our clients’ expectations.
Our Portfolio for Enterprise Asset Management Digitalization
Fleet Maintenance Software Development
- Real-time role-based dashboards to monitor and control fleet.
- Automatic inspection/availability checklists for each equipment type.
- Push notifications for critical events.
- Automatic maintenance remainders and maintenance completion reports.
Technologies: Microsoft Azure, .NET, ASP.NET MVC, Microsoft SQL Server, Xamarin, iOS, Android.
Development of Software for Managing Building Inspections
- Functionality for customer support specialists: configuring request settings, managing inspectors and necessary inspection procedures, etc.
- Functionality for inspectors: viewing the list of assigned inspections, assigning/changing set time of inspection, cancelling an inspection, etc.
Technologies: ASP.NET Web Forms, DevExpress, C#, Microsoft SQL Server, Java , etc.
Development of Defect Recognition Software for an Oil Drilling Equipment Manufacturer
- Optimized drilling equipment condition monitoring.
- Timely detection of emerging drill bit defects with machine learning and visual recognition algorithms.
- ML-based recommendations on an optimal date for drill bit replacement and maintenance.
Technologies: TensorFlow, Keras, OpenCV, Scikit-learn, NumPy.
Development of an RFID-Enabled Application for Livestock Management
- RFID-based wireless collection of livestock data from the field for animal monitoring and management of various farm activities.
- Reduced time spent on data gathering and processing with RFID tags, scanners and palmtop.
Technologies: C++, C#/.NET, Bluetooth API, Windows API, COM
Development of an IoT Solution for Construction Health Monitoring
- Real-time monitoring with sensors installed on the key elements of a building.
- Automatic notifications for operators about a sensor failure or a construction defect.
Technologies: .NET 4.0, WPF, WCF, SOA, NHibernate, Ninject, NLog, Castle, AvalonDock, NUnit, Moq, Microsoft SQL Server Compact, SQLite, etc.
Development of a Truck Temperature Monitoring Solution
- A GPS-based solution for real-time cargo temperature and humidity monitoring.
- Alerting on delivery violations.
- Advanced reporting capabilities to display detailed information about a particular delivery, including temperature, humidity, door opening and closing, damaged packaging, etc.
Technologies: AWS, PHP, Symfony 2, AngularJS, .NET WPF.
Oil Well Monitoring Application Development
- User-friendly web-based application.
- Monitoring the condition of rod pumping equipment at any time and from any device.
Technologies: HTML5, CSS3 (SASS), Angular 1.5, Angular Material, xml2json.js.
Technologies and Methodologies We Use
Programming languages
Back end
Practice
19 years
Projects
200+
Workforce
60+
Our .NET developers can build sustainable and high-performing apps up to 2x faster due to outstanding .NET proficiency and high productivity.
Practice
25 years
Projects
110+
Workforce
40+
ScienceSoft's Java developers build secure, resilient and efficient cloud-native and cloud-only software of any complexity and successfully modernize legacy software solutions.
Practice
10 years
Projects
50+
Workforce
30
ScienceSoft's Python developers and data scientists excel at building general-purpose Python apps, big data and IoT platforms, AI and ML-based apps, and BI solutions.
Practice
10 years
Workforce
100
ScienceSoft delivers cloud-native, real-time web and mobile apps, web servers, and custom APIs ~1.5–2x faster than other software developers.
Practice
16 years
Projects
170
Workforce
55
ScienceSoft's PHP developers helped to build Viber. Their recent projects: an IoT fleet management solution used by 2,000+ corporate clients and an award-winning remote patient monitoring solution.
Practice
34 years
Workforce
40
ScienceSoft's C++ developers created the desktop version of Viber and an award-winning imaging application for a global leader in image processing.
Practice
4 years
ScienceSoft's developers use Go to build robust cloud-native, microservices-based applications that leverage advanced techs — IoT, big data, AI, ML, blockchain.
Front end
Practice
21 years
Projects
2,200+
Workforce
50+
ScienceSoft uses JavaScript’s versatile ecosystem of frameworks to create dynamic and interactive user experience in web and mobile apps.
Practice
13 years
Workforce
100+
ScienceSoft leverages code reusability Angular is notable for to create large-scale apps. We chose Angular for a banking app with 3M+ users.
Workforce
80+
ScienceSoft achieves 20–50% faster React development and 50–90% fewer front-end performance issues due to smart implementation of reusable components and strict adherence to coding best practices.
With Next.js, ScienceSoft creates SEO-friendly apps and achieves the fastest performance for apps with decoupled architecture.
ScienceSoft uses Meteor for rapid full-stack development of web, mobile and desktop apps.
By using a lightweight Vue framework, ScienceSoft creates high-performant apps with real-time rendering.
When working with Ember.js, ScienceSoft creates reusable components to speed up development and avoid code redundancy.
Mobile
Practice
16 years
Projects
150+
Workforce
50+
ScienceSoft’s achieves 20–50% cost reduction for iOS projects due to excellent self-management and Agile skills of the team. The quality is never compromised — our iOS apps are highly rated.
Practice
14 years
Projects
200+
Workforce
50+
There are award-winning Android apps in ScienceSoft’s portfolio. Among the most prominent projects is the 5-year-long development of Viber, a messaging and VoIP app for 1.8B users.
Practice
11 years
Projects
85+
Workforce
10+
ScienceSoft cuts the cost of mobile projects twice by building functional and user-friendly cross-platform apps with Xamarin.
ScienceSoft uses Cordova to create cross-platform apps and avoid high project costs that may come with native mobile development.
ScienceSoft takes the best from native mobile and web apps and creates the ultimate user experience in PWA.
Practice
8 years
Projects
300+
ScienceSoft reduces up to 50% of project costs and time by creating cross-platform apps that run smoothly on web, Android and iOS.
ScienceSoft will save you from double or even triple expenses associated with platform-specific coding by creating cross-platform apps in Flutter.
With Ionic, ScienceSoft creates a single app codebase for web and mobile platforms and thus expands the audience of created apps to billions of users at the best cost.
Data storage and databases
Azure
Our Microsoft SQL Server-based projects include a BI solution for 200 healthcare centers, the world’s largest PLM software, and an automated underwriting system for the global commercial insurance carrier.
Azure SQL Database is great for handling large volumes of data and varying database traffic: it easily scales up and down without any downtime or disruption to the applications. It also offers automatic backups and point-in-time recoveries to protect databases from accidental corruption or deletion.
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
AWS
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
Google Cloud Platform
We use Google Cloud Datastore to set up a highly scalable and cost-effective solution for storing and managing NoSQL data structures. This database can be easily integrated with other Google Cloud services (BigQuery, Kubernetes, and many more).
Others
We’ve implemented MySQL for Viber, an instant messenger with 1B+ users, and an award-winning remote patient monitoring software.
ScienceSoft's team has implemented Oracle for software products used by GSK and AstraZeneca. We’ve also delivered Oracle-based SCM platform for Auchan, a retail chain with 1,700 stores.
ScienceSoft has used PostgreSQL in an IoT fleet management solution that supports 2,000+ customers with 26,500+ IoT devices. We’ve also helped a fintech startup promptly launch a top-flight BNPL product based on PostgreSQL.
Big data
By request of a leading market research company, we have built a Hadoop-based big data solution for monitoring and analyzing advertising channels in 10+ countries.
A large US-based jewelry manufacturer and retailer relies on ETL pipelines built by ScienceSoft’s Spark developers.
We use Kafka for handling big data streams. In our IoT pet tracking solution, Kafka processes 30,000+ events per second from 1 million devices.
Our Apache Cassandra consultants helped a leading Internet of Vehicles company enhance their big data solution that analyzes IoT data from 600,000 vehicles.
ScienceSoft has helped one of the top market research companies migrate its big data solution for advertising channel analysis to Apache Hive. Together with other improvements, this led to 100x faster data processing.
We use HBase if your database should scale to billions of rows and millions of columns while maintaining constant write and read performance.
ScienceSoft used MongoDB-based warehouse for an IoT solution that processed 30K+ events/per second from 1M devices. We’ve also delivered MongoDB-based operations management software for a pharma manufacturer.
AI and Machine Learning
Programming languages
Practice
10 years
Projects
50+
Workforce
30
ScienceSoft's Python developers and data scientists excel at building general-purpose Python apps, big data and IoT platforms, AI and ML-based apps, and BI solutions.
Practice
25 years
Projects
110+
Workforce
40+
ScienceSoft's Java developers build secure, resilient and efficient cloud-native and cloud-only software of any complexity and successfully modernize legacy software solutions.
Practice
34 years
Workforce
40
ScienceSoft's C++ developers created the desktop version of Viber and an award-winning imaging application for a global leader in image processing.
Frameworks
Libraries
Cloud services
Clouds
DevOps
Containerization
Automation
CI/CD tools
Monitoring
Data visualization
Practice
7 years
ScienceSoft sets up Power BI to process data from any source and report on data findings in a user-friendly format.
Real-time data processing
EAM advisory
Timeline: 4-8 weeks
- Analysis of EAM and implementation drivers.
- Assessment of the current EAM processes supported by technology (the automation level of the asset-related processes, features in and out of use, integrations, etc.).
- EAM solution conceptualization and design.
- Selection of a suitable EAM platform, optimal plan/edition selection with the list of needed modules and features, customization and integrations specification (if required).
- Custom EAM solution architecture and infrastructure design, tech stack selection, UX and UI design.
- EAM solution implementation planning, including cost and time budget estimation, etc.
EAM advisory + implementation and support
Timeline: ~2-10 months
- EAM needs analysis and solution conceptualization.
- EAM software architecture design (for custom solutions).
- PoC implementation (optional).
- EAM software development/customization.
- Integration of the EAM solution/solution components into the existing IT ecosystem.
- Hardware installation and integration (if applicable).
- EAM quality assurance (functional, UI, API testing, etc.).
- Data migration.
- Deployment to production and user training.
- After-launch support and evolution.
- SLA-based EAM solution administration, monitoring and maintenance.
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Note: to help you reduce EAM project risks, we offer starting our cooperation with:
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More about Asset Management
Asset Tracking