Choosing the right BI solution involves thoroughly evaluating the technology, understanding the expertise offered by the vendor, and implementing a process to ensure success. It also means keeping your customers top of mind as you determine requirements. These five BI requirements (both technical and non-technical) are critical to any analytics implementation and common to most evaluations.
1. End-User Experience
These are the core capabilities for all the end users of your application. Business intelligence requirements in this category may include dashboards and reports as well as the interactive and analytical functions users can perform.
Ideally, such self-service capabilities let users answer their own questions without having to involve IT. That frees up IT to work on more strategic projects rather than answering ad hoc requests. It also empowers users to be more self-sufficient.
“People want access to information and they want it easily,” says Trent McGrath a product leader at Citycounty Insurance Services. “The more they can get their hands dirty and really dig deep, they love it.”
During your evaluation, make sure the capabilities important to your project are demonstrated and understand how you will deliver and iterate upon these capabilities inside your application.
These common self-service capabilities may affect your business intelligence requirements:
User personas: Increase the adoption of analytics by providing a broad range of users with a tailored experience that matches their needs and skills.
Presentation and information delivery: These requirements affect you present data in visualizations, dashboards, and reports, as well as the compatibility of your BI solution across different devices and formats.
Interactivity and automation: Do users need to be able to interact with your dashboards? Consider whether you need to personalize visualizations, let users kick off workflows, or drill down into information.
Analysis and authoring: Empowering your users to query their own data, create visualizations and reports, and share their findings with colleagues can add value to your analytics application.
2. Data Environment
The BI solutions you evaluate should be compatible with your current data environment, while at the same time have enough flexibility to meet future demands as your data architecture evolves. These are the diverse data requirements commonly evaluated by application providers:
Data sources: Make sure your primary data source is supported by your BI solution. Also look for a vendor that supports generic connectors and has flexibility through APIs or plug-ins.
Data management: Consider what business intelligence requirements you have for directly querying the data source for real-time reporting, caching data, and blending data from multiple sources. Also ask yourself if your users need to transform or enrich data for analysis.
3. Embeddability and Customization
Depending on your organization’s need for embedding analytics into an application or existing software, a primary consideration may be the level of integration with your application’s environment. How much emphasis do you place on customization and integration capabilities compared to standard business intelligence implementations? Do you want to offer a seamless user experience within the context of an existing application? Have you struggled with adopting analytics in the past?
One way to look at embeddability is to focus on driving adoption. The deeper you integrate analytics into the fabric of the applications your users leverage every day, the higher your user adoption will be. For instance, if you’re a salesperson and you spend much of your time using Salesforce, you don’t want to go into applications that are siloed from your daily work. Organizations need to infuse that analytic workflow within users’ daily activities.
Consider these requirements around embeddability and customization:
Security: It should be easy to adopt the security from your application to the analytics content. Scrutinize vendors on the flexibility of their security models, implementation of single sign-on, and whether data needs to synchronized or replicated between applications.
Multi-tenancy: With built-in multi-tenancy, you can create a report once and deploy for multiple customers.
User experience: Many analytic applications need to be white-labeled to match your brand. Look for embedding APIs to ensure visualizations are rendered in the correct context.
Workflow: Create an efficient experience where users can immediately take action on what they see in any visualization or report.
Extensibility: Choose a BI solution that supports custom coding and third-party charting libraries to extend your application further.
4. Development and Deployment
Since time-to-value is so critical to the success of the project, having a development environment where you can create, style, embed, deploy, and iterate on analytics will enable your team to deliver the functionality your business demands.
These common capabilities may be part of your business intelligence requirements:
Development: A rich set of out-of-the-box functionalities is just the beginning. Also look for sample applications and rapid development tools to make both small functionality changes and mass changes that affect the entire application.
Deployment: Quickly deploy and scale an implementation that is aligned with your current technology stack. The best solution fits into your web architecture, minimizing the need to deploy proprietary technology, and utilizes well-known techniques to scale the implementation.
5. Licensing, Services, and Company Expertise
Choosing the right partner is not just about the technology. It’s also about finding the level of expertise you require for training, support, and services—as well as agreeing on the business terms that ensure shared success—to get you to the finish line, and beyond.
These factors may affect your business intelligence requirements:
Licensing: Terms of the license can depend on a variety of factors, including number of users/ customers, servers, usage, and whether you are embedding into a commercial product. Be sure the terms make business sense over the short and long runs.
Services: Completing your project on time may require technical support from your BI vendor, along with professional services to get you off the ground and ongoing training.
Customer success: Your BI vendor needs to be dedicated to your success. Look for one that supports onboarding, gives you a dedicated account management, and plenty of documentation and support offerings.
Expertise: The best analytics vendors have experience in your specific use case or industry.
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