This is what we do

Identify data-related business opportunities

Artificial Intelligence, machine learning, and Big Data won’t add much value to your business unless you carefully plan for it. By now, we’ve seen many organisations jump into data (science) head first, and failing to provide immediate value to their business.

All these new technologies promise to fundamentally change businesses, and being late to the game might be fatal. However, no algorithm will magically add value to your company without a clear strategy and value proposition.

With years of experience in data-driven companies, we help you select and specify projects that immediately add value and impress your stakeholders. We help you develop a roadmap that starts with simple solutions as a proof of concept, assist you in taking incremental steps towards a more advanced solution, and finally help you transition into a fully productized solution.

We help you identify opportunities by:

  1. Conduct interviews to understand business goals & data
  2. Design metrics to make goals measurable
  3. Work with your team to generate initial hypotheses for improvements
  4. Run exploratory data analysis to identify, validate, and quantify opportunities
  5. Provide a stack-ranked list of options by impact & effort

Implement anything data from MVP to cutting-edge technology

Our process in short:

  • Create a deep understanding of the business problem
  • Build a minimum viable product (MVP) to prove value
  • Iterate towards a cutting edge solution

Data, artificial intelligence, and machine learning are on their way to fundamentally change many industries. They allow services that were previously unthinkable, either technically or economically. Top-of-mind examples are self-driving cars, chat bots, and self-landing rockets.

But these are just the shiny revolutions on the surface. The real revolution is happening right below the surface. Google, Facebook, and Amazon’s ranking algorithms are changing how we interact with content and make decisions. Even classical businesses like delivery now heavily rely on machine predictions to optimize routes, order packaging, and traffic patterns.

Many companies understand the opportunity and are aiming to implement these new technologies. Yet few succeed: 87% of machine learning projects fail to be implemented. A key driver is the technological complexity but even more important is immediate value to the business. Most AI/ML projects fail to deliver any value for the business within a reasonable time frame.

We leverage our expertise from countless AI/ML projects to help you create immediate value for your business by starting with a simple prototype and only moving towards more advanced technologies after value is proven. As in product development, we start with a minimum viable product that shows e.g. that a certain feature is feasible in production. Then we assess together the potential to add value and only then start using cutting edge technologies. This approach helps us focus on value, impact, and speed.

From there on we iterate and help you build world-class technology based on years of industry experience and the newest research papers. Leading academic researchers on our team ensure we’re always on the cutting edge of technology.

What is the common denominator behind big tech companies’ success? They all practice data-driven decision making. Meaning they make decisions based on scientific principles to guard themselves against biases like, e.g. confirmation bias, base-rate fallacy, and more. A data-driven approach ensures high-quality decisions in today’s fast changing world.

Build world-class machine learning & data science teams

How we can help:

  • Map out the goals for the data science functions
  • Define the capabilities needed
  • Recruit world-class candidates
  • Setup & run robust hiring processes

Today strong data capabilities are core for many businesses. Start-ups often aspire to embed data in their DNA. Additionally, founders are more aware of the technological possibilities and design of their core product with machine learning capabilities in mind.

We help young and established companies to break down their roadmap and set clear goals for their machine learning and data science functions. From there we define the team that’s required to achieve their goals.

In the hiring process, we support by using our established network to find high-quality candidates, help interviewing, and build robust interviewing process for future hires. This helps companies to avoid false starts by hiring inexperienced or unqualified candidates. After all, data science is a very technical field and it’s often impossible for an outsider to judge the quality of a candidate.

Ask our friends at Orderchamp how we helped them building their world-class data science teams.