Evaluate BI solutions and decide

Which selection criteria and BI solutions are the right ones depends heavily on goals, the data situation, and resources. Solo operators need different tools than large enterprises. But BI is no longer reserved for companies with extensive resources, neither in terms of capital nor working time.

Using data as a basis for decisions creates comparability between options, enables performance tracking, and shows clearly which measures work and which do not. For that to succeed, the chosen solution must fit your requirements.

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This article shows how to move from a requirements profile to a concrete tool decision. Use cases for different company types make the process tangible. The article Define requirements for BI solutions covers which types of BI tools exist and which evaluation criteria are relevant. The article Develop a BI strategy describes an overarching strategy for KPIs, governance, and adoption.

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Create a requirements profile

Before you research vendors, it should be clear what the solution has to deliver. Which data matters, where does it come from, and how will it be integrated? Which general requirements does the solution have to meet?

Data can come from internal or external software, be researched externally, or be maintained manually. A requirements profile translates your own goals into concrete expectations for a BI tool.

You can find a ready-made criteria catalog for evaluating vendors and a template for a data catalog in the article Define requirements for BI solutions.

Prioritize decisions and value

What are the most important business decisions, and where does BI create the greatest added value?

For example, decisions made by company leadership set the direction for many activities across the business. Marketing and sales drive growth. Depending on the situation, customer satisfaction, for example support or retention, can also be a sensible starting point.

Assess teams and effort realistically

Which departments and roles have high priority when expanding the BI process, and which have lower priority?

Besides the effect on business performance, you should consider where data is already available and where there is capacity for implementation. This matrix helps with prioritization:

Self-service vs. your own platform

Depending on ambition, depth, and resources, you need to decide which type of solution fits. This decision determines the effort, cost, and speed of the entire BI rollout.

An all-in-one solution or self-service BI application takes over many processes around company data: import, partial cleaning, storage, and access protection. In the application, data can be visualized, exported, managed, and shared.

This usually does not require deep specialist knowledge, your own data platform, or a large data team. Initial dashboards can be available in just a few clicks.

A traditional in-house BI setup, by contrast, means the entire data management stack is built and operated internally. Data has to be imported, stored, cleaned, protected, modeled, visualized, and maintained over time.

That requires building and maintaining know-how, technical structures, and a suitable team, and therefore comes with time, effort, and cost.

Architecture and vendor selection

With regard to time, budget, staff, and individual requirements, you need to determine whether to build an internal data platform or use a self-service BI solution.

Define requirements: which data should be analyzed in the short and long term, and how will it be integrated?

To minimize friction, data should be transferable into the system as simply and as automatically as possible.

Functions such as drag-and-drop interaction and dashboard templates help with a fast start and easier maintenance.

A role system is often useful as well so that you can make certain data available only to selected groups and control visibility clearly.

Data protection should be an important decision criterion, especially in Europe. The GDPR requires, among other things, clear legal bases, access controls, transparency, and, depending on the setup, a data processing agreement (DPA) with service providers.

Use cases: BI tools in practice

The following examples show how different company types go through the selection process, from prioritizing the criteria to making a concrete decision.

1. BI for marketing agencies: Fast and interactive client reports

Employees at a marketing agency spend a lot of time preparing client reporting manually. To do that, they have to download data manually from email campaigns, organic and paid social media campaigns, paid search, and web analytics software. Then they prepare, clean, and filter the data and create individual PDF reports from it.

Based on these goals and requirements, they identified self-service, data integrations, functionality, usability, role distribution, and sharing as especially highly weighted criteria.

Phase 1: Time spent on client reporting should be reduced by at least 50%. Follow-up steps after success are already planned, but at this point still without hard targets:

Phase 2: Internal marketing campaigns should be visualized for marketing managers in a central overview so they can be managed more effectively.

Phase 3: KPIs for individual sales activities should be made available to each sales employee and in aggregate to the manager so they can learn from one another.

Phase 4: Accounting and controlling should be connected as well in order to reduce reporting effort there and further increase reporting flexibility.

The team chooses an out-of-the-box self-service application with a predictable annual contract and clearly defined usage limits. It offers:

• Relevant data can be imported automatically via OAuth
• Prebuilt templates for especially fast setup
• Intuitive drag-and-drop interaction for easy customization
• Rights management makes it possible to control who can see which data
• Clients can access the dashboards live through a viewer account and interact with them, but not edit them

2. BI in a startup: Agility and flexibility

A SaaS software startup wants to integrate business intelligence deeply into the company from the beginning, providing live KPIs across all business areas for improved decision-making. Many areas are still being built, and the technical solutions in use are not yet final.

Critical business decisions should be assessable and analyzable live. This should make it possible to detect poor investments quickly and identify the best investment opportunities. Broad integration capabilities of modern solutions are important to them.

They defined self-service, cost, support, functionality, usability, performance, and exit strategy as especially highly weighted criteria.

Phase 1: Leadership wants live visibility into sales and marketing data so it can shift budget agilely toward the more successful channel during the critical growth phase. Department leads should use this live visibility to evaluate, assess, and optimize all decisions and activities of their teams. The ROI of both channels should increase by 20%.

Phase 2: User behavior data from the product should be visualized for the developers so they can better understand user behavior and prioritize further development more effectively.

Phase 3: Support requests should be shown through the same system, with the goal of monitoring and improving user satisfaction and reducing churn.

Phase 4: Website visitors and SEO measures should be monitored, as should cold-mailing results. Insights about what works particularly well should be collected and shared across the team.

The team decides on the starter plan of an all-in-one BI platform with a strong self-service focus and transparent subscription tiers. It offers the following:

• Clear and well-structured product documentation
• Support response times defined as less than 3 business days
• All dashboards accessible through a central team workspace
• Role management to control who can see which dashboards and numbers
• High dashboard performance even with large amounts of data in just a few seconds
• The option to export all connected data in bulk or selectively

3. Enterprise (500+ employees): Compliance and scalability

A large enterprise wants to push BI further. It has already integrated some areas into a BI process, but is dissatisfied with the solution overall and is planning a switch rather than an expansion.

It already has a comprehensive database system. When creating dashboards, its strict requirements must be observed, and dashboards must not be adjusted independently without review. Instead of an all-in-one solution, it is looking for a visualization tool to display its data.

It has defined cost, security, data integrations, role management, governance, and data protection as especially strongly weighted factors.

Instead of making dashboards available only to management, employees should get access and visibility into their own performance. Their working time should become 20% more effective, with 15% better results.

Phase 1: Existing BI processes are migrated to the new solution.

Phase 2: As a pilot phase, the rollout takes place first in one department. Surveys and meetings are used to discuss the process and the results. Based on that, the further rollout is planned and optimized.

Phase 3: The solution is expanded to the planned departments. A dedicated data team takes care of storing, cleaning, managing, and importing the data as well as setting up the standardized dashboards. The IT department supports users when issues occur.

They decide on a visualization tool that uses the data from their existing infrastructure and has comparatively low user-based license costs. It offers them:

• Cost-efficient use of their existing structures
• Their IT team continues to manage the high security standards of their data servers
• The solution supports integration with their database system so all data can be used
• Roles control which employees can access which dashboards and data
• Their existing governance system, for example around quality and definitions, continues to be used
• They continue to manage the data protection standards of their architecture independently

Troubleshooting during tool selection and rollout

Even with good planning, typical problems can occur during the selection and rollout of BI tools:

For further information on governance, KPI definition, and adoption, see the article Develop a BI strategy.

Conclusion

Choosing the right BI tool does not start with the feature list, but with your own requirements profile. If you know your goals, data sources, and resources, you can decide in a structured way.

The most important steps:

• Derive the requirements profile from use cases and the data inventory
• Make the fundamental decision between self-service and your own platform
• Evaluate vendors using a weighted criteria catalog, see Define requirements for BI solutions
• Start small, gather experience, then scale

As a rule, the best solution is the one that is actually used, not the one with the most features.

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