7 Steps to Select the Best Business Intelligence Software


Implementing the right business intelligence software is a strategic investment that enables organizations to harness data-driven insights for achieving growth. However, the wide array of BI solutions makes finding the ideal platform aligned to your needs challenging. This guide outlines a proven, step-by-step methodology to identify, evaluate and select the best business intelligence software tailored to your organization’s specific requirements.

In the modern information age, leveraging data to drive decisions is no longer optional but essential for enterprise growth and survival. According to Forbes, companies that adopt data-driven decision making are 23 times more likely to acquire customers and 19 times as likely to be profitable as a result.

With the global business intelligence software market expected to reach $32 billion by 2026, per ResearchAndMarkets.com, adoption is accelerating rapidly. However, the extensive range of available solutions makes selection difficult. Options span from established enterprise BI suites like SAP BusinessObjects, IBM Cognos, Oracle BI, to rising startups and modern self-service tools like Tableau, Microsoft Power BI, Qlik Sense, Looker among others.

Finding the ideal business intelligence software requires aligning solutions against concrete organizational criteria to determine the best fit. This guide outlines a proven 7-step process to define your needs, create selection criteria, evaluate contenders, and select the top BI platform for driving maximum value.

While the process requires an upfront investment of time and resources, the rewards can be significant and long-lasting. With the right business intelligence software powering data-driven decisions across the enterprise, organizations can reduce costs, accelerate growth, increase productivity, identify new opportunities, and make every decision smarter.

Step 1: Define Your Business Intelligence Software Needs

The first and most critical step is to have a clear understanding of your key business needs and objectives for adopting a BI solution. Take time to comprehensively analyze and document:

TopicQuestions and Considerations
Business ObjectivesWhat are the specific business goals and desired outcomes driving your business intelligence software investment? What is the process for measuring return on investment (ROI)?
Users and DecisionsWhich business units and teams will rely on BI insights to improve decision making? What crucial decisions need analytical support?
Reporting NeedsWhat are the mandatory reporting requirements? Descriptive, predictive, prescriptive? How frequently?
Key Metrics and KPIsWhich data points, metrics and key performance indicators are most critical?
Pain PointsWhere are the problem areas where you need expanded analytical capabilities the most?
Data SourcesWhat types of data from which sources will you need to analyze CRM, ERP, social media, financials, IoT etc.?
Use CasesWhat are the mandatory analytics scenarios and use cases e.g. forecasts, predictive modeling, sentiment analysis?
Visualization NeedsWhat types of charts, graphs, dashboards and reporting do users need for insights?
User ExpertiseWhat are the skill levels of target users – expert, power user, casual user?
Mobile and Natural LanguageDo you require mobile, geo-spatial, conversational analytics?
Capability PrioritiesWhich capabilities are absolutely essential vs. nice-to-have?

Documenting this analysis creates a solid foundation to develop your selection criteria in the next steps. Invest time upfront to be clear on business intelligence software needs.

Step 2: Build Selection Criteria for Business Intelligence Software

With requirements defined, establish the key criteria to evaluate business intelligence software options. Example criteria spanning critical capability areas:

Data Connectivity

  • APIs and pre-built connectors to integrate with existing systems
  • Ability to handle on-premise and cloud-based data sources
  • The ability to scale to accommodate the growth of data volumes over time

Data Discovery and Visualization

  • Intuitive, interactive data exploration without coding skills
  • Highly customizable dashboards composed of rich visualizations
  • Desktop, tablet, and mobile experiences are supported by responsive design.

Self-Service Analytics

  • Augmented analytics through AI-assisted insights, natural language generation
  • Smart predictive modeling, forecasting simulations, and what-if analysis
  • Collaboration features to securely share analytics assets across the organization

Embedded BI and Customization

  • APIs, SDKs, and other development resources for customization
  • Ability to embed interactive analytics into business applications
  • Automating analysis using machine learning, artificial intelligence, and bots

Ease of Use

  • Short learning curve for users across persona types – expert to casual user
  • Clear navigation, built-in assistance, contextual help, and tutorials
  • Availability of online training resources, community forums, and certifications

Administration and Scalability

  • Advanced governance including role-based access control, usage monitoring, and data security
  • Technical architecture to handle increased data volumes, user adoption and application complexity over time
  • Cloud-based delivery model for scalability, high-availability and failover

Total Cost of Ownership

  • Predictable pricing model including license, maintenance, training, services, and technical support
  • Flexible options aligned to budget constraints perpetual license, subscription, consumption-based, or hybrid model

Vendor Services and Support

  • Packaged services for design, implementation, integration, change management, and adoption best practices
  • Responsiveness of technical support and community channels available, response times, resolution quality
  • Availability of pre-configured solutions, use case applications, and content packs tailored to your industry

Adjust and prioritize criteria specific to your most critical business intelligence software needs. This drives a selective evaluation process.

Step 3: Shortlist Leading Business Intelligence Software Solutions

With selection criteria defined, the next step is to research the market to create a shortlist of potential business intelligence software options.

Use the following approaches to build your list:

  • Consult analyst reports such as Gartner’s Magic Quadrant for Analytics and Business Intelligence Platforms for top-rated solutions
  • Read credible product reviews in industry publications and online forums to understand pros and cons
  • Directly inspect product functionalities, interface designs and visualizations through live demos
  • Talk to your industry peers and professional network connections about their experiences and lessons learned
  • Include a mix of established BI suite vendors as well as niche, emerging solutions
  • Maintain a balance of traditional on-premise and modern cloud BI solutions
  • Keep the initial list to around 5-8 leading recommended options that warrant deeper evaluation

The goal is to create a focused shortlist of business intelligence software solutions aligned to your needs for further evaluation in the next steps.

Step 4: Perform In-Depth Evaluation of Business Intelligence Software

With a candidate shortlist identified, the next step involves detailed evaluation of each option against your defined selection criteria.

For example, assess how well platforms meet needs across:

IntegrationExamine pre-built connectors and ease of connectivity to cloud applications and on-premise data sources. Review custom ETL, data preparation, and modeling capabilities.
AnalyticsAnalyze breadth and flexibility of visualization formats. Evaluate smart capabilities like predictive forecasting, simulations, recommendations, and natural language narration of insights. Review extent of self-service analytics for business teams.
CollaborationAssess how securely analytics assets like reports, dashboards, and apps can be distributed through user management, sharing, and access control features.
CustomizationCheck availability of APIs, SDKs, embedded analytics, and other developer resources to customize, extend, and integrate BI into other applications.
MobilityValidate accessibility on desktops, smartphones, and tablets with responsive design adaptations. Check for native mobile app availability.
GovernanceReview administration capabilities for access control, usage monitoring, and data security. Examine scheduling, workflow automation, and DevOps abilities.
Cloud DeploymentConfirm availability of a multi-tenant SaaS delivery model in addition to on-premise versions. Review service uptime history, support resources, and change management processes.
PricingAnalyze TCO across multi-year ownership spanning license, maintenance, administration, services, training, and technical support. Request current pricing summary across all aspects.

Take advantage of free trials, online demos, and proof of concepts to validate claims versus your criteria. Document pros and cons of each option for easy comparison later. Resist vendor marketing that does not map directly to your needs.

Step 5: Compare Business Intelligence Software Head-to-Head

With detailed evaluations complete, the next step is to compare options head-to-head mapped directly against your selection criteria.

For instance, assess platform capabilities as Best, Average or Poor for criteria:

CriteriaVendor 1Vendor 2Vendor 3
Data connectivity and accessBestAverageAverage
Interactive visualization capabilitiesAverageBestAverage
Augmented analytics and MLPoorBestAverage
Customization and extensibilityAverageAverageBest
Self-service analytics enablementBestAveragePoor
Complex data preparationPoorBestAverage
Embedded BI and APIsAverageAverageBest
Cloud deployment optionsPoorBestAverage
Admin and user managementAveragePoorBest
Implementation and support servicesPoorAverageBest
Pricing model suitabilityAveragePoorBest

This illuminates software strengths and weaknesses. Focus evaluations on criteria you prioritized earlier as most critical for your needs.

Step 6: Select the Best Matching Business Intelligence Software

With detailed evaluations complete, the next step is to select the business intelligence software option that aligns closest to your needs.

Tips for this final selection:

  • Focus primarily on platforms rated Best for your must-have and top priority criteria. These are dealbreakers.
  • Do not overvalue Nice-to-have criteria with Average or Poor ratings. Keep priorities central.
  • Avoid overbuying capabilities you may not fully leverage. Seek just-enough-functionality for your current and near-term needs.
  • Consider starting smaller with a niche solution focused on your specific use case over a complex software suite. Expand capabilities over time.
  • Don’t underestimate implementation complexity, timelines and costs. This affects ROI realization. Seek vendor support.

Confirm choice by presenting findings and recommendations to executive sponsors and key stakeholders. Seek early alignment.

Proceed confidently by choosing the BI vendor clearly excelling in areas most critical for your success. Avoid decisions based solely on short-term factors like cost.

Step 7: Validate Business Intelligence Software with Proof of Concepts

Prior to final signoff, conduct short 2-4 week proof of concepts (POCs) with one or two top candidates to further validate fit. Focus POCs on 2-3 high-priority use cases to assess ability to deliver concrete value justifying the investment. Keep POCs targeted using dedicated resources from both business and IT sides, with vendor support.

Successful POCs prove the selected BI platform:

  • Provides the essential analysis, visualization and reporting features your users need, aligned to defined criteria
  • Integrates smoothly with existing data infrastructure and sources with good performance
  • Generates actionable insights that drive better business decisions
  • Enables users to quickly become productive with the right enablement
  • Delivers strong capabilities and ease of use relative to TCO

With proof points validated, make your business intelligence software investment decisively by choosing the vendor demonstrating relevance to your needs and capability to fulfill their promised value.


What are leading business intelligence software solutions I should consider?

Top options include Microsoft Power BI, Tableau, Qlik Sense, Sisense, Domo, Looker, Tibco Spotfire, SAP Analytics Cloud, Oracle Analytics, and SAS Viya, among others. The right solution depends on aligning to your specific needs.

Is open source business intelligence software a viable alternative?

Open source platforms like Metabase, Jaspersoft and Superset offer powerful, low-cost options but require more in-house technical skills. Evaluate capabilities carefully against commercial solutions.

How long does it typically take to implement business intelligence software?

Simple cloud BI tools can be up and running in days to weeks, while on-premise enterprise BI implementations often take months for full rollout. The scope and complexity are key factors that determine timelines.

What skills are required in my team to use business intelligence platforms?

Some BI tools are easy for business users without extensive technical skills. Advanced analytics, customization and administration require IT and data science expertise. Seek a balance between ease of use and depth of functionality based on your needs.

Should I choose cloud or on-premise deployment for my BI initiative?

Cloud BI offers faster time-to-value, lower startup costs, and more flexibility. On-premise provides more customization control and supports existing infrastructure investments. Weigh trade-offs to find the right delivery model based on your specific needs. Hybrid is also an option.