Business intelligence tools should be the highest-impact software an organization uses. But this potential comes along with huge amounts of complexity and ambiguity around purchasing.
While other key tools like CRMs and ERPs are similarly complex, they solve very specific, functional, and describable business needs for easily identifiable stakeholders.
BI tools have to do all that while also enabling more aspirational goals like changing data culture for a much wider and more diverse group of audiences.
All this leads to a daunting purchasing decision.
No standard view of need or requirement
The brief becomes vague (“easy to use”) or prone to featurism (”we want AI”)
And it's never grounded in company benefit or business case
So, how should a company navigate these waters? And what should the baseline requirements be for a BI tool in 2025?
In this article, we strip back the rhetoric and share three key questions to ask yourself before buying a BI tool. We’ve also created a list of over 55 requirements based on these questions (including hygiene requirements) so you can easily build out your assessment criteria.
DISCLAIMER
You may have noticed that we have skin in this game. And we do definitely believe that Count is an excellent BI tool for many companies that are looking.
But the reasons we believe this are very different to the overly reductive comparison of features common in the market.
We believe a better, broader definition is needed of what a BI tool actually is. Though we have a strong belief in what the best answer is to the questions below, we believe they are objectively the right questions to be asking.
Three questions to ask before buying a BI tool
There are a few obvious and foundational hygiene requirements a BI tool needs to meet, such as security, connectivity, etc.
Once these basics have been met, there are only three simple criteria that should drive your decision:
Will the BI tool increase operational clarity in the business?
Will the BI tool support the business to reach decisions quickly?
Will the BI tool improve the return on investment for the entire data function?
Let's flesh these questions out below to help you understand their implications for your business.
1. Does your BI tool increase operational clarity in the business?
The traditional view is that a BI tool gives people access to data.
15 years ago—when many of today’s incumbent tools were launched—the definition of both “people” and “data” was much narrower. Today, data flows from almost every business software platform and is demanded by ever more people and presented through an ever-growing sprawl of dashboards.
Instead, we see BI tools as helping the company communicate a clear, simple understanding of how it’s performing and what’s important: making data the language of the company’s operations, and opening it up to be understood, interrogated, acted upon, and improved by anyone in the business.
The best BI tools aren’t just data portals. They use data to make the business feel simple and amplify the valuable signal from the informational noise that floods companies today.
Does your BI tool add to the information chaos that most businesses now face? Or does it help make the business simple and help clarify what matters?
FURTHER QUESTIONS TO ASK
How widely is data used (rather than just looked at) across the business?
How clear is the operating model to employees? Is there real clarity on what’s important?
How empowered does the average employee feel to use data in their work?
2. Does your BI tool support the business to reach decisions quickly?
Almost every BI tool markets itself as “helping organisations make better decisions.” But it’s important to remember that in any organisation there are range of decisions that take place, from the very tactical/operational to the most strategic and complex.
A good BI tool needs to support both, and put data at the heart of both.
Operational decisions are typically taken quickly by one person who can:
Quickly see a number
Instinctively know what has to happen
Take action
Dashboards or simple interfaces for “self-service data exploration” are great for this situation.
However:
When the decision is complex or cuts across teams and functions, dashboards are no longer sufficient. These decisions need a tool which supports not just data but the wider workflow via collaboration, easy iteration, and discussion—and the combination of data and qualitative information.
Quicker decisions become better decisions when people have confidence and comfort in both the inputs and the outcome. The role of a BI tool today has to be to create and maintain that.
Does your BI tool allow for easy collaboration and discussion to help with strategic decisions? Or just spit numbers out onto a dashboard for tactical insights?
FURTHER QUESTIONS TO ASK
How easy is it for domain, but non-technical experts to use data in their work today?
Is data used only in big course changing decisions, or in day-to-day course-correcting ones?
Are decisions and their underpinning data communicated in a way that builds confidence and alignment?
3. Does your BI tool improve the return on investment for the entire data function?
While it's tempting to try and optimize the tech stack by consolidating products or even adding a new product to the mix that offers new functionality, the surest way to maximise ROI across a data function is to unlock the way the team can work with—and across—the business.
Simply put: the cost of any single tool is dwarfed by the team payroll.
A more nuanced version of the purchasing motivation is that most data teams have their workflows split across 3-4 different tools, which makes collaboration inside the data team and with stakeholders slow and error-prone. While swapping one tool for another that's faster or cheaper is tempting, bigger savings are found through products that support the data team to work and solve problems together with the business—while increasing its trust in the data and its processing.
FURTHER QUESTIONS TO ASK
Is data seen as a way of reporting impact, or creating it?
What would the process be if a domain-expert asked for data analysis? At what points would they be involved and engaged?
Could you explain to an investor how data drove an improvement in a key metric? Could everyone in your team?
BI tool requirements checklist
We think exploring the three questions above can help you explore the BI market from a more informed position, and with more clarity of your business’ needs. We’ve also created a table of over 36 different requirements and another 19 hygiene factors to support you as you go on to examine possible solutions more closely.
Note: Requirements marked with a * are the most overlooked by traditional BI tools.
Criteria
Theme
Requirement
Description
Does Count support?
Improve operational clarity
Visualization capabilities
Standard graph types for KPIs
There is a range of standard chart types for plotting KPIs such as line, bar, scatter plots, single metric cards and sparklines? Can these different chart types be overlaid on a single plot?
Y
Create tables of data
You can create tables of data including pivot tables, sub-totals and aggregations?
Y
Formatting
All visualization types be customized including date time, number, currency formats, chart axes, grid and company color schemes.
Y
Geographical mapping
Geographical data be overlaid on to maps.
N
Statistical charts*
Advanced charts are supported such as sankey, histograms, box and whisker, waterfall charts.
Y
Metric presentation
Multiple report options*
Reports can be built flexible layout formats, dimensions and page structures including dashboard, long-form report, slide deck etc all which are easy to navigate.
Y
Business mapping*
Relationships between metrics based on the business’s operating model can be visualized alongside the data.
Y
Present qualitative information*
Metrics and charts can be laid out flexibly and alongside qualitative information such as images, diagrams and text.
Y
Distribution
Automated alerting
Alerts can be sent out based on arbitrary logic (e.g. deviation from average).
Y
Scheduling
Reports can be sent out at a specific time of day, week, month, year and to multiple audiences.
Y
Caching / real-time
Data is updated on a sufficient timescale from real-time streamed to daily/hourly updates.
Y
Finding assets
Deep search
Make it easy for all users to find existing reports based on deep search.
Y
Report hierarchy
Use folders and hierarchies to make the BI tool easy to navigate for all uses.
Y
Making decisions faster
Faster operational decisions
Flexible report exploration
Allow users to explore reports with flexible filters and drill down either on a particular chart or across the whole report.
Y
Data upload
Users have the ability to upload data to reports to act as inputs to a decision model / data application.
Y
Easy-to-use self-service exploration
Non-technical users can explore data easily using defined metrics, dimensions and filters.
Y
Loading times
Initial time to load a report and any updates from filters is quick.
Y
Faster strategic decisions
Real-time collaboration during analysis*
Allow all user groups to discuss methodology and findings during the process for a tighter iteration loop.
Y
Real-time collaboration during presentation*
Real-time collaboration and discussion can happen during a final presentation.
Y
Combining quantitative and qualitative data*
Data and charts can be combined with screenshots, text and other qualitative data to structure and contextualise thinking.
Y
Real-time commenting
Allow users to tag users to highlight findings and ask for help.
Y
Static caching of data*
Data can be cached permanently so conclusions captured in the past can be referred back to.
Y
Query languages
SQL
Users can write arbitrary SQL to explore and clean data.
Y
Python*
Users can use Python for more advanced analytics and machine learning use-cases.
Y
Spreadsheet*
Users can use a spreadsheet to explore, analyse and import data from a wide range of data sources. Allows a large number of organization to explore data.
Y
Low code / AI
Users can explore data using AI or low code to find insights “self-service”.
Y
Language interoperability*
Users can move between different query paradigms to allow team-wide collaboration and the best functionality for every step of an analysis.
Y
ROI of data team
Seamless analytics and modelling workflow
Requirements scoping*
Users can define requirements for a new data project together within the BI tool for easy reference and discussion.
Y
Blend analysis, cleaning & modeling*
Analysts can move seamlessly between analysis, cleaning and data modeling during their workflow. Once the project is complete they can then move logic back in to the data warehouse.
Y
Version control
All an analysts work is saved at regular intervals automatically and multiple branches or versions can be saved and merged as team members work on a report or project at different times.
Y
Real-time analysis and review*
Analysts can work, code and discuss findings together or with stakeholders in real-time.
Y
Define flexible data models
Define metrics in code
Metrics, dimensions can be defined in code and used across multiple reports for consistency.
Y
Symmetrical aggregations*
All company entities and metrics can be combined using 1:1, 1:many, many:many relationships for maximize flexiblity.
Y
Push-pull logic from dbt / github*
Data models and metrics can be version controlled in github and/or dbt and edited in the BI tool.
Y
Lineage control*
Downstream impacts of changes to the data model are easy to see and check.
Y
Asset management
Detailed usage telemetry*
Data teams have detailed telemetry on report usage and performance to allow continued optimization.
Y
API control
Actions to maintain the platform can be done in bulk and using code using a client API.
Y
Hygiene
Security
Audit controls
Usage telemetry to understand historical data access and export.
Y
Compliance frameworks
BI tool has sufficient compliance certificates such as SOC2, HIPPA, GDPR, ISO27001.
Y
Deployment options
BI tool can be deployed in required geographies and/or on-premise.
Y
Support/SLA
The BI offers sufficient support SLA and up-time guarantees for use-cases.
Y
Authentication
The BI tool provides sufficient authentication options including SSO /SAML as required.
Y
Permissions
User/group permissions
The BI tool allows fine-grain user permissions at a report, project, workspace level.
Y
Row-level access
User permissions can be assigned to specific data tables, columns and rows to allow reports to be filtered appropriately.
N
Data sources & integrations
Database compatibility
BI tool can connect to relevant databases and data sources including csv files.
Y
Data limits
BI tool can handle the data volumes of the company and with sufficient performance.
Y
Blend data sources
Users can blend data between different data sources.
Y
Support with wider productivity tooling
BI tool integrations with company’s productivity tooling such as Notion, Slack, Microsoft Teams to enable easy sharing and discussion.
Y
Device compatibility
Browser support
BI tool works well and performantly on the standard internet browsers used by the company.
Y
Offline mode
The BI tool can be uses (at least in a limited way) by users who are offline.
N
Mobile/tablet support
The BI tool can be accessed and used (at least in a limited way) by the standard mobile and tablet devices used by the company.
Y
Commercials
Company-wide access*
The pricing model allows the whole company to access the BI tool at a reasonable cost.
Y
Pricing scaling
The price can scale efficiently as the company grows or shrinks.
Y
Lock-in*
The terms of the contract are sensible with transparent renewal clauses.
Y
Customer support*
The contract provides reliable access to human support during regular working hours and timezones of the company.
Y
Data limits*
There are no hidden compute costs to consider and any limits are sufficiently high as to not be an issue.
