Enterprise Software Development: Steps, Timelines, and Cost Factors

Enterprise Software Development Guide - ScienceSoft

In software development since 1989, ScienceSoft carries out the development of modular multi-user software, which efficiently controls complex business operations.

ENTERPRISE SOFTWARE DEVELOPMENT: THE ESSENCE

Enterprise software development implies building software that standardizes and automates business processes (customer relationship management, enterprise resource planning, supply chain management, web content creation, etc.) and synchronizes enterprise-wide data. Enterprise application software (EAS) is mostly large modular systems that have many simultaneous users and support high availability.

ENTERPRISE SOFTWARE DEVELOPMENT PLAN

The end-to-end development of the first version of enterprise software or several essential enterprise software modules usually takes around a year. The exact timelines depend on the business domain it is used in and the composition and complexity of the required modules. Below we describe typical phases of an enterprise software development roadmap.

Step 1. Discovery

Duration: 1-2 months

  • Documenting key business processes and how they’re covered with existing software, understanding the capabilities and limitations of the existing IT environment.
  • Eliciting business needs and concerns regarding the existing and desired business process flows.
  • Analyzing a broad business strategy (e.g., planned company growth and IT budgets) that can affect architectural and tech choices for planned software.
  • Drawing up high-level functional and technical requirements to software.
  • Evaluating risks of possible negative impact on business processes due to the introduction of the new system (e.g., lost productivity and downtime associated with transitioning to new digital processes, business user training).

Step 2. Enterprise software planning and design

Duration: ~ 2 months.

  • Drawing up technical requirements for the new enterprise software.
  • Deciding on the architectural style of the new enterprise software system (mostly, point-to-point/event-driven service-based or microservices) and developing its detailed design.

Note 1

Often, it can be more cost-efficient and less risky to re-use a part of your legacy enterprise systems than develop and implement new software modules and enable their communication with other enterprise systems. When you decide to re-use existing legacy modules in a new enterprise software development, you’ll need to plan all or several of the following activities:

  • Reverse engineering of the legacy system (including all connections and interdependencies), interfaces between software components, data structure, and data design.

Show all activities

  • Code re-factoring to simplify conditionals, remove unneeded code parts, improve code structure, review complex or memory-intensive algorithms.
  • Adding new intuitive and integrated interfaces.
  • Designing and implementing the integration of the legacy modules with new software (see more info on software integration in Note 2).

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Note 2

When integration with other enterprise or third-party software is required, add to the plan:

  • Identifying integration touchpoints.
  • Choosing integration approaches (integrating via common data storage, mediated integration of SOA/microservices via message broker/ESB or PaaS, point-to-point integration, integration via UI/RPA, etc.) and technologies (e.g., for an ESB-based integration – Talend ESB and SAP PI, for iPaaS-based integration – Azure iPaaS or Informatica iPaaS).

NB!

Non-invasive integration (integration via UI/RPA, data storage) is less flexible but also less costly and risky. Invasive integration (e.g., via implementation of SOA with re-usable functional modules that communicate via ESB) can improve enterprise agility and be cost-efficient in the long-term, but it’s expensive in the short term, architecturally risky, and may require quite deep preliminary code changes (very dangerous for legacy applications with their old, not well-documented code). We recommend prioritizing non-invasive integration approaches when it comes to legacy software and considering the adoption of the iterative integration approach for more complex invasive integrations to better control risks and prove architecture feasibility in the early iterations.

  • Enterprise application integration architecture design.
  • Planning how data should flow and whether it needs to be transformed into a different format.
  • Checking how many communication protocols between integrated applications will be used.
  • Designing additional security enhancements.
  • Preparing a comprehensive QA strategy to verify all uni- and bidirectional calls between the integrated systems, backup and recovery mechanisms, how well the integrated system works within established bandwidth limitations, etc.

Step 3. UX and UI design

Duration: 1 – 3 months.

  • UX designers and Business Analysts collaborate on UX research to understand the target audience and their needs, goals and mental models.
  • UX designers describe how a user will interact with the system (identify digital touchpoints) and design information architecture.
  • UX designers create wireframes that demonstrate basic content layout and functionality.
  • Wireframes get combined into a prototype of the application.
  • The prototype undergoes user testing.
  • Once the prototypes pass user testing, UI designers transform them into full-color graphic interface mockups that are then handed over to front-end developers.

Step 4. EAS development and testing

Duration: from ~ 6 months to several years (depends on software complexity).

  • Back-end development – to build the server side and APIs of new enterprise software. It also includes integration with required business applications.
  • Front-end development – to transform static interface images provided by UI designers into a fully functional enterprise client side and ensure its communication with the server.
  • Reviewing whether the system matches functionality, performance, security, and integration requirements. Testing usually runs in parallel with development.
  • In parallel with software development, training materials should be prepared to help users adopt the new system.

Note

You can shorten the time to release and optimize the development budget by developing an MVP. It is a software version with only the essential features, which helps you test whether software meets the key stated user needs. Upon confirming or adjusting the initial EAS idea, you can add other features to the MVP. The first working version of enterprise software of small to medium complexity can be delivered in 4 – 8 months, with new functionality being added during major releases each 2-6 weeks.

Step 5. Data conversion and uploading

Duration: 3-6 weeks.

  • Inspecting the legacy data to migrate, avoiding duplicated or inconsistent data.
  • Deciding on the supported data formats and handling the required conversions if several data formats are in use.
  • Extracting, transforming and loading the legacy data.
  • Conducting ETL testing to ensure data stays complete and adequately transformed (also, where feasible, developing and running automated ETL testing, e.g., using tools as QuerySurge, Informatica DVO, ETL Validator)

Step 6. EAS deployment

Duration: 1-2 weeks.

Software gets deployed and integrated with the required corporate infrastructure. Complex software should be first moved through staging and testing environments so that the team could safely introduce changes or catch remaining mistakes before release.

Note

A trial implementation is recommended for applications to minimize possible downtimes in production. The trial implementation is done for a limited number of users and requires comprehensive technical support in case any problems are encountered. Trial stages usually take up to 1-3 months.

Step 7. Regulatory compliance assessment and certification procedures

Duration: up to several months.

This stage is relevant for enterprise software or its parts falling under government or industry regulations, e.g., HIPAA, CGMP, PCI DSS. At this stage, the team compiles comprehensive documentation created during all stages – from software design to verification and validation – to prove that software and software development life cycle meet all essential requirements of a standard or a regulation.

Step 8. Further EAS evolution in iterations

Duration of releases: 1-3-6 months (depends on a development and deployment strategy).

The development and delivery of new working software modules continue iteratively according to the following scheme:

SKILLS REQUIRED FOR AN ENTERPRISE SOFTWARE DEVELOPMENT PROJECT

Below we describe the common roles involved in complex enterprise software development projects. Additional talents may be required, depending on the nature of the project, for example, you may need the skills of data scientists, 3D designers, etc.

Project Manager

  • Keeping the project on schedule and within the scope and budget.
  • Controlling project milestones and deliverables
  • Facilitating and coordinating communication between all team members.
  • Managing project risks.

Business Analyst

  • Uncovering the underlying business issues that need to be addressed.
  • Translating business needs into enterprise application capabilities.
  • Organizing, specifying and documenting requirements to the new enterprise software system from all stakeholders.
  • Representing business interests during system design and software configuration planning.

System Architect

  • Designing software architecture.
  • Designing integrations with other in-house and third-party software systems.

Note: A system architect should have a good knowledge of advanced software architecture approaches, including ESB-driven service-oriented architectures and microservices.

UX Designer

  • Performing UX research.
  • Designing user interactions with the application.
  • Designing the information architecture.
  • Conducting usability testing.

UI Designer

  • Deciding on the colors, icons and screen layouts of the application’s GUI.
  • Creating a UI kit for quick development of user interfaces.

Database Developer

  • Developing and implementing databases, building data models.
  • Optimizing resource consumption and storage space needed.
  • Developing and support ETL/ELT processes.

Back-end Developer

  • Writing back-end code and APIs.
  • Performing unit tests.

Front-end Developer

  • Creating functional components of the user interface.

QA

  • Designing a test strategy.
  • Selecting test tools.
  • Designing, developing, and maintaining tests.
  • Documenting, implementing, monitoring, and improving the testing process.
  • Tracking test results, finding and reporting bugs.

DevOps Engineer

  • infrastructure.
  • Incorporating an infrastructure-as-code approach.
  • Optimizing orchestration.
  • Designing and creating CI/CD pipelines for automated deployment.
  • Selecting and configuring tools to execute daily monitoring of the enterprise application system.
  • Performing root cause analysis of EAS performance faults.

An entire EAS development process is in-house

Pros:

  • Direct supervision over the development process and team productivity.

Cons:

  • High costs.
  • Lack of experience and resources can lead to the project delay, setup and management risks.
  • All hiring and managerial efforts are on your side.

A mix of an in-house team and outsourced consultancy

Pros:

  • In-house team has a deep understanding of internal processes and software environment and direct access to all assets.
  • Outsourced consultancy provides expert guidance, mentors through the most challenging migration activities, closes up the gaps in specific tech skills.

Cons:

  • Risks related to vendor selection.
  • Requires time and experience to establish smooth collaboration and communication between the in-house and consultancy teams.
  • Project team coordination, the concerns about quick and quality delivery, risk management are partially/totally on your side.

Full EAS development process is outsourcing

Pros:

  • Established EAS design and development processes.
  • A vendor assumes full responsibility for the team arrangement and management, quality of the project deliverables and related risk management.

Cons:

  • High vendor risks.

POPULAR TECHNOLOGIES USED FOR ENTERPRISE SOFTWARE DEVELOPMENT

We recommend cloud development for EAS as a cost-effective and fast way to deliver scalable, resilient and adaptable enterprise applications.

Microsoft Azure

Best for: applications with strict compliance requirements, advanced AI needs.

Description

Leader in Gartner Magic Quadrants for Cloud Infrastructure and Platform Services, Full Life Cycle API Management, Enterprise Integration Platform as a Service (eiPaaS).

  • 200 + services (compute, containers, CI/CD, integration, migration, databases, IoT, AI, etc.).
  • 60+ availability zones.
  • Storage: Azure Blobs, Azure Files, Azure Tables, Azure Queues, Azure Disks.
  • ETL: Azure HDInsight.
  • Analytics: Azure Databricks, Azure Stream Analytics, Azure Data Factory, Azure Data Lake Analytics, etc.
  • Machine learning: Azure Machine Learning.
  • BI: Power BI, Azure Analysis Services, Azure Synapse Analytics.
  • Compliance with CIS Benchmarks; ISO 20000-1:2011, 22301, 27001, 27017, 27018; SOC; WCAG; HIPAA; HITRUST; FERPA; FDA CFR Title 21 Part 11; FFIEC; GxP; SEC 17a-4; SOX; CCPA.
  • Smallest instance offered: vCPU – 2, RAM – 8 GB, Price - $70 per month.
  • Largest instance offered: vCPU – 128, RAM – 8.89 TB, Price - $6.79 per hour.
  • Discount for long-term usage (1-3 years): Microsoft Enterprise Agreement (up to 72% discount).

AWS

Best for: large-scale applications.

Description

  • Has been leading Gartner Magic Quadrant for Cloud Infrastructure and Platform Services for 9 consecutive years.
  • 175+ services (storage, databases, containers, serverless computing, application integration, migration, application management, ML, AR & VR, IoT, etc.).
  • 77 availability zones.
  • Storage: Amazon Simple Storage Service (S3), Amazon Elastic File System, Amazon Elastic Block Store.
  • Analytics: Amazon Data Pipelines, Amazon Redshift, Amazon Kinesis Analytics, Amazon Elasticsearch Service, etc.
  • Machine learning: Amazon SageMaker, Amazon AI: Intelligent Search, Automated Data Extraction and Analysis, Language, Vision, Industrial, Business Metrics Analysis.
  • BI: Amazon QuickSight.
  • Compliance with CSA; ISO 9001, 27001, 27017, 27018; PCI DSS Level 1; SOC 1, 2, 3; FERPA; GxP; HIPAA; HITRUST CSF; MPAA; PIPEDA; SEC Rule 17a-4(f), etc.
  • Smallest instance offered: vCPUs – 2, RAM – 8 GB, Price - $69 per month.
  • Largest instance offered: vCPU – 128, RAM – 3.84 TB, Price - $ 3.97 per hour.
  • Discount for long-term usage (1-3 years): EC2 reserved instances provide up to 72% discount.

Google Cloud

Best for: building resilient enterprise software

Description

Third in Gartner’s Magic Quadrant for Cloud Infrastructure and Platform Services.

  • 100+ services (storage, serverless computing, operations, migration, databases, container, AI & ML, IoT, etc.).
  • 73 availability zones.
  • Compliance with HIPAA, COPPA, FERPA, California Consumer Privacy Act (CCPA), Ontario's Personal Health Information Protection Act (PHIPA), GDPR, PIPEDA, etc.
  • Storage: Google Cloud Storage, Persistent Disk.
  • Analytics: BigQuery, Dataproc, Dataflow.
  • AI and machine learning: Recommendations AI, Media Translation, Healthcare Natural Language, Translation, Vision, Video, Text-to-Speech, Speech-to-Text, Dialogflow, Search API (App Engine), Google Genomics, etc.
  • BI: Looker, BigQuery BI.
  • Smallest instance offered: vCPU – 2, RAM – 8 GB, Price - $52 per month.
  • Largest instance offered: vCPU – 160, RAM – 3.75 TB, Price - $5.32 per hour.
  • Discount for long-term usage:
    • (1-3 years) Committed used discounts (up to 57-70% depending on the resource type).
    • (during the billing month) Sustained use discounts (up to 20-30%).

In our experience, SME can expect the costs of custom enterprise software to range anywhere from $50,000 to $200,000. For large enterprises, the cost will often vary between $200,000 and $500,000.

Major cost factors:

  • Application type (web, mobile, desktop); number of platforms and OS versions supported (for mobile).
  • Number and complexity of application features.
  • Number of business areas covered (finance, SCM, production, HR, CRM, etc.).
  • The number of business processes covered (e.g., for sales and marketing: email marketing, lead nurturing, case escalation).
  • The number of user roles.
  • The complexity of the application logic and workflows.
  • The number and complexity of integrations with custom / third-party systems.
  • Application availability, performance, security, latent capacity and scalability requirements.
  • The necessity to maintain existing data (in case of migration).
  • Frequency of the application updates and improvements.
  • Regulatory compliance requirements.
  • Special features required (machine learning capabilities, etc.).
  • Uniqueness and complexity of UI design.

So, How Much Will My Enterprise Software Dev Cost?

ScienceSofts consultants, architects and certification experts can help you with the custom quote for the future enterprise development project.

ENTERPRISE SOFTWARE DEVELOPMENT SERVICES BY SCIENCESOFT

Enterprise software development consulting

Our consultants:

  • Clarify enterprise application vision, elicit, and structure software requirements.
  • Assess tech and economic feasibility of the enterprise software development project.
  • Plan application security and compliance (HIPAA, FDA, GLBA, PCI DSS, etc.).
  • Develop a business case.
  • Form a holistic set of enterprise application features.
  • Deliver PoC.
  • Design enterprise app architecture, choose a tech stack.
  • Deliver a detailed development roadmap.
  • Plan a DevOps strategy.

End-to-end enterprise software development

Our team takes over:

  • Enterprise application development project planning: needs analysis, requirements specification, app architecture design.
  • UX and UI design.
  • MVP development.
  • Iterative enterprise software development with major releases every 2-4 weeks.
  • Integration with other in-house and third-party business software (SCM, CRM, BI, HR software, etc.).
  • Testing and QA.
  • After-launch support.
  • Continuous management and evolution of the new enterprise application (on demand).

About ScienceSoft

ScienceSoft is a US-headquartered global software development company with 32 years in the market. We employ extensive technical expertise and practical knowledge of 23+ industries, professional business analysis, and KPI-based development to help our customers re-engineer, build and integrate enterprise software that covers complex business processes.