Tap Data’s Value with an Integration Lifecycle Strategy
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The world’s largest and most influential businesses are rethinking how they handle data so they can increase business agility, develop stronger customer relationships, and spur more product or service innovation.
A key requirement is to integrate data across different boundaries, including system, departmental, and company boundaries. But the increased use of SaaS applications has accelerated the pace of application updates and fragmented application portfolios making the integration challenge even more burdensome. Organizations realize that to tap in to the value of their data, they must pay special attention to managing the lifecycle of integrations that keep data flowing across their organizations and between their customers and partners.
The rise in cloud computing has dramatically increased the number of applications organizations use. Instead of relying on a single, pre-integrated application suite from one vendor, organizations are selecting applications to serve specific needs. Typically these come from different vendors and require custom integrations to ensure systems talk to each other and data flows between them. Integration is further complicated by the fact that each SaaS application is updated continually – often three to four times per year.
Looking for a quick fix to these integration challenges, some organizations may be tempted to integrate multiple apps in as short a time as possible with an off-the-shelf connector. Yet research from Gartner has shown that the initial development and deployment of an application may represent only 10 percent of its total cost of ownership. The other 90 percent is the cost of updating, maintaining, and supporting the application over its useful life. Taking such shortcuts can make it harder to debug issues or take advantage of new application capabilities down the road. Further, a bad or inflexible integration can ruin a system deployment entirely, such as a CRM system that is populated with out-of-date information and gets a reputation within the sales force for causing delays in sales deals.
Integration Lifecycle Management
To capture the most value from their data and to minimize integration costs, organizations should develop an integration strategy that considers all of an integration's lifecycle phases. These include:
- Lifecycle Phase: Design
- Modularity – Can you separate endpoints from integration logic to simplify maintenance and accelerate debugging?
- Performance/scalability – Consider throughput, latency, performance, and functional capabilities of the integration solution and, if it’s cloud-based, the hosted infrastructure that drives it.
- Design in customization and extension – Will your integration approach allow you to easily extend an integration to cover additional target systems or take advantage of additional application capabilities?
- Expert advice – Are there company or community experts that can help with data architecture?
- Lifecycle Phase: Develop
- Build/test/production environments – Can the integration solution support the number of extensions you expect to roll out during the lifecycle of the integration?
- Documentation – Are there aids for improving documentation, such as self-documenting development tools? Proper documentation can shorten maintenance and debug activities, help you adjust to IT staff changes or transfer integrations to a run/maintenance staff.
- Collaboration – Does the integration approach allow you to leverage various application experts at different stages of the development process through collaboration tools?
- Lifecycle Phase: Deploy
- Cloud or on-premise installation options – Consider costs and infrastructure requirements.
- Staging and production environment tools – Are there tools to help you test integrations and move them to a production environment?
- Lifecycle Phase: Run
- Multi-tenant management environment – Does the integration approach simplify management and reporting by separately tracking integrations by department or organization?
- Proactive alerting / automated health checks – What events are detected and how much control do you have over detection logic and alerting workflows?
- Lifecycle Phase: Commercialize
- Cost structure and levels – Do your required costs for the integration approach allow you to price your solution as desired now and in the future? Are there other pricing options that can streamline your sales process?
- Provisioning – How fast can you deploy an integration for a new user group? Does your organization have the skills required to handle the customization/provisioning?
Taking a long-term, lifecycle management approach to integration helps you think beyond the initial deployment and build agility into every lifecycle phase. By adding agility to the ongoing processes to track, debug and update integrations on a continual basis, organizations can make staffing changes more seamlessly, react to runtime issues more quickly and respond to the data-driven needs of the business more precisely.
About the Author
John Joseph is vice president of marketing at Scribe Software. Follow the company on Twitter @ScribeSoft
