Congratulations on completing
the Data and AI Maturity Assessment!
You are at
Operational
Stage
What this means
You're at the beginning of your data and AI journey. Systems are disconnected, processes are manual, and data isn't driving decisions yet.
You’ve started building. Maybe you have dashboards or a data warehouse, but things are still fragmented and not standardized.
You’re doing many things right. You’ve got BI dashboards in place and some experience with AI or governance, but gaps still exist in integration, automation, or scale.
You have a mature stack, trusted dashboards, and advanced analytics. Now it’s about scale, performance, and keeping things maintainable.
You’re among the most advanced teams in your industry. AI is deeply embedded. You’re setting benchmarks, not following them.
Where you are
Level
Data infrastructure
Data modeling & quality
BI & dashboards
Predictive & prescriptive analytics
Governance
AI applications
Level 1
Level 2
Level 3
Level 4
Level 5
How you can advance to the next tier
Data infrastructure
Data Infrastructure
At a maturity score of 9, the company likely has a solid foundation for their data infrastructure. However, they may be experiencing bottlenecks and inefficiencies due to the lack of a comprehensive data strategy and proper tools for data management and analysis. This could result in delays in decision-making and difficulty in scaling their data operations.
Here’s what we recommend you do next:
- Develop a clear data strategy that aligns with your business goals and objectives.
- Implement a data management platform to centralize and streamline data collection, storage, and access.
- Invest in data analytics tools and resources to improve data analysis and reporting capabilities.
- Regularly review and optimize your data infrastructure to ensure it can support future growth and changes in data needs.
Modeling & data quality
Modeling & Data Quality
Based on your maturity score of 7, your data modeling and quality is in a good state. However, there are still areas that can be improved upon. Some tables may have inconsistent metrics and the overall schema hygiene may need some attention. This can lead to potential data inaccuracies and lack of trust in the data.
Here’s what we recommend you do next:
- Regularly review and update table-level modeling to ensure consistency and accuracy.
- Implement processes for maintaining metric consistency across all tables.
- Prioritize schema hygiene by regularly cleaning up and organizing the data.
- Consider investing in tools or resources to automate and streamline these tasks for your limited team size.
BI & dashboards
BI & Dashboards
As a Seed startup with 50-100 employees, your maturity score for BI & Dashboards is 9. While that is a great score, there are still areas for improvement.
Here’s what we recommend you do next:
- Review your current dashboards and clean up any clutter or unnecessary visuals.
- Ensure that your metrics are clearly defined and trusted by all users.
- Foster a culture of user trust by regularly communicating updates and changes to your dashboards and metrics.
- Consider implementing a regular dashboard review process to ensure that your dashboards are always up-to-date and relevant.
Predictive analytics
Predictive Analytics
Currently, your startup has some ideas for ML use cases and possibly some notebooks, but none of these have had any real impact on production. In order to see tangible results, you will need to take some concrete steps.
Here’s what we recommend you do next:
- Identify a specific business problem that can benefit from predictive analytics, such as customer churn or sales forecasting.
- Collect and clean relevant data for this problem, using tools like Excel or Google Sheets if needed.
- Explore and analyze the data using simple statistical methods, such as descriptive analytics or regression models.
- Based on your findings, develop a simple predictive model using a user-friendly tool like Azure ML or Google AutoML.
Governance
Governance
With a maturity score of 8, your governance is in a decent state. However, there are still areas that need improvement. Messy access, lack of ownership, and shadow data can still be found within your organization.
Here’s what we recommend you do next:
- Implement clear access control measures to ensure data is only accessible to those who need it.
- Establish ownership tagging so that data can be easily tracked and managed.
- Increase visibility by regularly auditing and monitoring data usage.
- Avoid abstract policy design and instead focus on practical and actionable steps.
AI applications
AI Applications
The startup currently has a maturity score of 13 for AI Applications. This means that there is a lot of buzz and excitement surrounding AI, but there are no deployed use cases and possibly just a prototype that is not being used.
Here’s what we recommend you do next:
- Identify a specific business problem that can be solved using AI and gather relevant data.
- Build a simple AI model using open source tools or pre-built APIs.
- Test the model and gather feedback from end users to make improvements.
- Deploy the model and measure its impact on the identified business problem.
You’ve got clarity.
Now let’s make progress.
You’re probably duct-taping reports together, reacting to fires, and guessing your way through KPIs.
At this stage, velocity matters more than perfection. The challenge is building a usable foundation — without overengineering, overhiring, or overbuying.
How 5X helps:
We give you a plug-and-play data stack, ingestion, modeling, dashboards, and governance in one platform. Our experts build it with you, so you’re not stuck duct-taping metrics across tools that don’t talk to each other.
You’ve got pieces of the puzzle — a warehouse, maybe some dashboards — but it’s held together with best guesses and broken SQL. Every new request is a one-off build.
How 5X helps:
We help you consolidate the warehouse, model core business metrics, and introduce QA standards that don’t require new headcount. Your team gets answers they can trust, and you get out of the spreadsheet firefighting loop.
You’ve got dashboards, pipelines, models… but they’re not always trusted or actioned. Business teams want more, faster, and your data team’s burning out just trying to keep up.
How 5X helps:
We bring structure: tested governance frameworks, automated observability, and faster deployment paths for models and dashboards. You move from reactive support to proactive enablement without increasing your engineering footprint.
Your data team ships — but duplication, compute waste, and rogue dashboards are slowing things down. Your execs want smarter automation, but engineering cycles are stretched.
How 5X helps:
We help you clean it up by codifying logic, reducing compute spend, and building internal tools like smart alerts and AI-powered workflows. Your infra supports scale without spiraling.
You’re already running structured experiments, internal tools, and ML in prod. The question now is: how do you 10x your leverage without slowing down?
How 5X helps:
We help you co-build GenAI copilots, reusable ML modules, and internal accelerators tailored to your business DNA without duplicating work or slowing down compliance and governance.
Use this report as a strategic input
This report is designed for teams who want to move forward, not just score themselves. It’s built to complement your existing goals, and help anchor planning discussions with your leadership team. Use it as a clear, thoughtful guide to shape priorities across data infrastructure, analytics, and AI readiness.
Share your score on LinkedIn and we’ll include your org in our upcoming 2025 Industry Benchmark Report—a comparative view of how companies at your stage and scale are evolving their data & AI capabilities.
