About our clients & services
We have a broad portfolio of clients in 10+ industries. Some are international global players, and some a local scale-ups. Most of our clients are within Maritime, supply chain, logistics, Finance, Real-Esate, and Healthcare.
Our clients hire us to get their business fully data-driven. We align with them on business strategy, tell them what they really need (and what not), and design & build it end-to-end. The best way possible.
End-to-end custom BI implementations
Data platforms & custom applications
Dashboarding & predictive modelling
Data strategy & consulting
BI Team
To deliver the best BI solutions for every client's specific situation, you need a fully specialized and experienced BI Team, with knowledge of their business.
That is what we offer.
They get a fixed BI Consultant that dives into their business and delivers our "WOW!" effect. In the background it is possible that the whole team has worked on the project, delivering their piece of expertise at the right moment. We usually sell one sprint, deliver massive value fast and get them hooked. This is how we scale projects and build long lasting partnerships.
BI at Scale
This is our service for large enterprises. The service is almost identical as BI Team, as we deliver a fully specialized BI Team.
The difference is that we focus on building custom data platforms, data applications and predictive models, instead of just reporting solutions. Most of our data science projects are for those clients.
How we work on projects
Scoping projects
During the sales fase our consultants explore our clients business and strategy. They also check with the team if we like the project.
They paint the bigger picture, set out the roadmap for the first fase and define the scope of the first sprint. We try to scope small so we can deliver fast and keep complexity to a minimum.
Sprint Zero
All our clients work in our sprint rithme. Sprint zero is the kick-off of the project. The timeline of this sprint is not fixed. We onboard clients and the goal is to retrieve all the requirements necessary to start the project. This includes login details, the necessary rights to source systems and databases, current reports, etc.
We do not start the project before sprint zero is 100% completed.
Sprint Planning
We work in fixed sprints of 3 weeks. Before the new sprint we prepare all new stories individually and we plan the new sprint with the whole team. (might change as we grow).
We go through all projects, assign stories across the team and make sure the workload is reasonable for everyone.
After the planning, everyone knows exactly what to do for the next 3 weeks.
During Sprints
During the sprint we work individually on our stories. But we all take responsibility for the end result. We work as óne team, like the marines. In case of questions, uncertainties or challenges, we seek each other out and are happy to help each other. It is an effective way of working together. Some of us wrote a detailed blog about their work week: Check them here
Our 6 biggest projects
(at the moment)
1) Optimizing the global supply chain for a top-3 logistics player
The clients challenge
The customer wants to optimize its global logistics chain and develop new products based on available data. They have asked us to set up the global data infrastructure, to implement the BI solution across all locations, to guide the organization towards a data-driven culture and to think about possible optimization opportunities using ML and AI.
The technology we use
ADF Azure Machine Learning Azure SQL database Azure SQL server Data Lake Dremio GIT Jupyter notebooks MS self-hosted integration runtime Power BI
What we are working on right now
- Extension of the standardized BI platform with the Finance and asset management domains (data flow, data model, reports).
- Expanding the data science team and applications.
- Rolling out the standardized BI platform across 5 new locations.
- Handle all exceptions from the new locations in the standardized BI platform.
- Implementing Master Data Management at head office level.
- Setting up and expanding a Business Intelligence Competence Center.
Project Highlights
- We got the sponsorhip of the headoffice's C-suite for our vision on the global BI architecture;
- We built one standardized BI platform for all locations with built-in flexibility for local extensions;
- We developed one data model for all different locations;
- We developed a central BI platform where all data from the location comes together;
- We developed predictive models to predict the productivity of key business processes at the sites. This allows us to optimize the logistics chain on a global level instead of a local level.
2) Real estate consultancy firm wants to become the market leader by using data
The clients challenge
The client is a consultancy that advises real estate companies about investment opportunities and the performance of their real estate portfolio. They expressed an ambition to become the market leader by offering the best service based on all available data. They want to take analytics for their customers more seriously so that it provides more insight and takes less time. In addition, they want to make benchmarking analyzes possible and continue to innovate with new products in the future.
The technology we use
Excel SQL database Logic Apps Azure Data factory Power BI
What we are working on right now
- Enriching the benchmark reporting with data from external sources such as CBS and well-known real estate systems.
- Expanding the benchmark report with landmarks on important real estate business drivers (rental price per m2, % vacancy and number of lettable units per object) in order to be able to provide proactive advice.
- Automating all actions that still take place manually. For example, enriching data from external sources.
- Expanding a data warehouse with a huge amount of data from as many sources as possible. So that they always have all the necessary data available and remain commercially ahead with the most valuable analyses.
Project Highlights
- All data dumps supplied by external parties are now translated into a generic data model, which makes comparisons possible.
- The data from complex and polluted Excel files with strange dependencies are neatly and automatically written to a database, with a notification system if the import is not accepted.
- We have developed a benchmark report for real estate clients, whereby a real estate party can select an object (or complete portfolio) from its own portfolio to compare it with data from all other real estate parties.
3) Maritime company wants to work more professionally and data-driven
The clients challenge
The only BI employee of the customer left. At the same time, the organization had a growing demand for insight. Too much for one person. They were urgently looking for a BI partner who could professionalize, optimize and maintain the current infrastructure, and then expand it with more reports and data points.
The technology we use
SQL server management studio Azure Data studio Azure DevOps GIT Power BI Desktop
What we are working on right now
- Keeping the BI solution operational;
- Documenting the entire BI environment to remove dependency;
- Get feedback from the organization to develop the roadmap for the next phase.
Project Highlights
- The first phase of our project, which mainly involved the automation of reports, has a very positive impact on the business. The customer is super enthusiastic, continues to expand the project with new questions and even introduces us to new customers;
- Test environment set up for both the data warehouse and Power BI Service;
- Excel source phased out to Data Warehouse for most important reports;
- Master Data Management model implemented for all different subsidiaries.
4) Guiding a housing company to a data-driven way of working
The clients challenge
The client is a Dutch party that offers residential properties to private individuals. They expressed the ambition to drive the organization data-driven step by step. The current BI team was looking for a specialized BI partner who could provide additional capacity for the development of the data lake, data model and Power BI reports. During the project, the assignment was expanded with a trajectory to guide the organization towards a scrum working method.
The technology we use
Azure Data Factory Databricks Power BI
What we are working on right now
- Setting up reporting for the portfolio management department.
- Creating insight for key strategic pillars in the field of sustainability and energy.
Project Highlights
- Scrum methodology introduced and refined for the entire data team;
- Current Excel reports phased out and transferred to Power BI with the intervention of a Data Lake;
- Reports including the entire underlying data flow, set up on the most important product groups for the purchasing organization.
- All data from external parties conforms to their own standard
5) A software company needs insights into its Finance and Sales
The clients challenge
A software company has been taken over by a major competitor. The management of the new owner wants to have insight into the most important business drivers such as new business, churn, ARR, etc. We have joined as a BI team to realize this project.
The technology we use
Locale SQL server on premise Power BI
What we are working on right now
- Building reports on Churn and new customers;
- Validation of numbers and calculation methods.
Project Highlights
- All customer contract data has been made accessible and transparent;
- Existing data flow is automated;
- Complexity of calculations in reports has been reduced and all calculations have been simplified and housed in a Data Warehouse;
- We have developed a system ourselves that fills a historical model based on mutations between supplied snapshots;
- We have developed one reporting table with contract data, which is built from two different source systems from which the data does not match.
6) Creating insight into the core business of a transport company
The clients challenge
The customer wants to have an overview of the performance of all vehicles, travel movements and the goods that are transported. With full insight into their own data and the possibility to run analyzes on it, they want to drive and optimize the core business data.
The technology we use
Azure Data Factory SQL server Power BI Python
What we are working on right now
- Taking first steps with Machine Learning: predicting outcomes on a journey
- Continuously expand data model with new data points
- Building reporting on the movements of goods to the vehicles, sales, maintenance, cost per trip.
- Developing Snapshot Analytics
Project Highlights
- Set up DWH with staging layer, reporting layer and Power BI connected to it;
- All reports automated with Power BI;
- Big time savings: building reports now takes hours instead of days.
- Trend analyzes delivered across all dimensions (vehicles, travel movements, goods)