How to test a BI solution properly: a checklist for the trial phase

This article describes the process for testing an all-in-one or self-service business intelligence solution. These solutions can be set up and tested within days. A traditional in-house BI infrastructure, by contrast, is a project that takes months, must be planned carefully, and cannot be tested in such a short form.

The trial phase is about obtaining evidence through practical use in a real use case. Up to this point, the assessment is usually based on information from third parties: vendor promises, review portals, and reports from other companies. Only in the trial do you see how a solution behaves with your data, your use case, and your team. This makes this phase particularly informative and decisive in the selection process.

Anyone who skips this phase skips the proof that the solution works as intended and fits their own team and processes. If things go badly, the pilot phase is carried out anyway and time and money are lost, even though the problems might already have been found during the trial phase.

A planned trial takes hardly any more time, but it provides a well-founded answer instead of an impression.

You can find a detailed comparison based on public information from different vendors here: BI tools compared.

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This article shows you what must be clarified before day 1, what a 14-day test plan looks like, and which scorecard to use for your final decision. It covers the most important points to check, typical testing mistakes, and the transition from the decision to initial production use. Define requirements for BI solutions provides the criteria catalog for selecting the trial candidates.

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What a trial can prove (and what it cannot)

The trial phase should prove operational use. A trial demonstrates the most important aspects of a BI solution: Can I get my data into it at all? Can my team use the solution without someone actively guiding them? And which steps are needed to integrate the value of the solution into the processes?

The trial does not cover the following, because they are part of the pilot phase: stability over months, support quality in a real incident, behavior with growing data volumes, and the reliability of the roadmap.

How quickly value is achieved can be measured directly in the trial and says more about later day-to-day use than any feature list.

If you can create a useful dashboard within a few days during the trial, that is a strong signal. If you already need help from the vendor in the protected trial environment, things will usually not become easier in regular operation.

Independently of the trial phase and before it begins, you must clarify whether the solution will also be able to connect the data for planned use cases in the future. This could be supported, for example, through OAuth, PAT, or API connections, or through spreadsheet uploads.

Preparation before the trial phase

For a smooth process, planning should happen before the trial phase starts:

• One or a few test cases. For example: “Revenue, pipeline, and marketing costs in one dashboard for management.” Test in a focused way instead of rolling out broadly.
• Real data, in a small volume. Two to three sources from the test case, if necessary as an export of the past three months. Real data reveals connection and compatibility problems.
• Two people, not one. One manager and one person from the team that will work with it. Usability for viewers is a criterion in its own right.
• The scorecard. Define the criteria before the trial, not afterward. Otherwise, the solution with the friendliest onboarding video wins.

The 14-day test plan

Fourteen days are the usual length of free trial periods and are sufficient if they are used in a structured way. The table shows a sensible allocation:

Put connection work first: if it fails, the trial ends after three days. That is a valuable result, not wasted effort. Whether data updates independently and correctly with the relevant connection only becomes apparent over several days.

The most important trial results

These are the decisive proofs for productive use in day-to-day operations:

1. Connect your own data

Connect the sources for your test case, for example through a connector, upload, or API. Do not only check whether it works, but how it works: How much time and how many steps does it take? Record the required steps and time so that you can compare them with other vendors if necessary.

2. Create a functional dashboard

Build the dashboard for the test case and then make changes to it. This gives you direct insight into the workflows of the people responsible. Again, record the steps and time to make comparison possible. Create effective dashboards explains what matters when structuring the dashboard's content.

3. Share, invite members, and set permissions

Test inviting your team to the solution and sharing dashboards with an external test user. You should also test the ability to restrict access rights to data and dashboards. The decisive questions for day-to-day use are: Can a person without prior knowledge manage on their own? And can permissions be differentiated as needed, including access for external users if you want to provide dashboards to customers or partners?

4. Observe updates

Let the connection run for several days and check without intervening: Are the values current? A manual reconciliation provides additional confidence in data quality. At what interval is new data loaded, and is it possible to update manually?

5. Test the exit path

Finally, you can test a possible future exit in advance: Can you retrieve your data and structures? Test exporting the data and, if possible, deleting the trial account. A vendor whose exit path is difficult to find could also cause problems when switching to other vendors.

The scorecard

This table shows basic criteria for evaluating how the solution is handled during the trial phase. You can add individual points from your requirements profile, award bonus points for features, for example, adjust the weighting if necessary, and assign points for each criterion, such as from 1 to 5.

Ideally, exclusion criteria should be marked as such in advance. If an essential connection is missing, a higher total score is not decisive. The weighting should also be fixed before the trial to avoid subjective favoritism.

Evaluate BI solutions and decide explains how to derive the selection systematically from these results.

Typical testing mistakes

Testers should be aware of these common pitfalls:

• Feature density: Smooth operation of the core features should be rated more highly than an abundance of additional features.

• Demo data: Demo data was set up by the vendor to work. Connect your own sources to assess the underlying processes and functionality.

• Technical testers: IT may find it easy to set up and use the demo. Depending on the use case, the managers and employees who will use it should also be involved in the tests.

• Setup by support: If support from the vendor is already required during setup, there is a good chance that this dependency will continue during regular use. The vendor's documentation may provide sufficient help that can be opened with a click.

• Trial without planning: A few clicks between meetings should not form the basis for building a company's data infrastructure. Requirements definition, vendor selection, and the trial, pilot, and operating phases should be planned, completed in a structured way, and documented.

• Too much in parallel: Instead of comparing too many candidates at once, plan a separate period for each application so that enough time remains for a reliable result.

The result of the trial phase

At the end, it should be clear which solution was selected, based on which criteria, and with which open points.

Open points from the trial belong on a short list with deadlines: missing connectors, contract questions, and unresolved permission requirements.

The use case from the trial phase should also become the first use case of the pilot phase, now with a real audience and a binding cadence.

You can find a concrete article on the pilot phase here: BI pilot phase in 90 days.

Frequently asked questions about the trial phase

Are 14 days enough to assess a BI solution?

For the most important questions, yes: connection, usability, time to first result, sharing, and data sovereignty. Other aspects such as stability over months and support quality are factors that are addressed during the pilot phase.

How can I do this effectively for several solutions?

Test the solutions one after another and use the same test case and scorecard. Two candidates are sensible. Anyone who needs three has probably not narrowed down the initial selection enough.

Can I load real company data into a trial environment?

Technically, usually yes. The privacy requirements should be clarified in advance. Alternatively, anonymized or shortened datasets without personal data can be used for the trial phase. If personal data is to be included, the same requirements apply as in production.

Conclusion

The trial phase is the least expensive and most important safeguard in the entire selection process. Preparation is decisive: a defined strategy, a test case selected for it, real data, several test users, and a scorecard.

Failing early is a success and saves you months of complications caused by holding on to the wrong solution.