We aim and hit spot on with our predictive analytics solutions, because we see and understand business opportunities, and are able to translate it into data analytics solutions by identifying the right data and develop robust algorithms that create predictions with high validity
We offer a center of excellence in business data science, enabling companies to make more informed business decisions through refined data insight and trustworthy predictions. With our center of excellence, we provide companies of all sizes with the opportunity to make faster and smarter business decisions.
When we work with data science, we include a huge number of variables and large amounts of data. On that basis, we develop algorithms which predict the expectation of an event very accurately. But the results are not explained and can’t be interpreted. Therefore, results from data science and the use of machine learning are considered a ‘black box’.
In Rooftop, we go a step further. We utilize our economic and statistical competences to analyze the problem. Then, we break it down and identify the areas that can be explained through the use of economic theory, which is to be incorporated into the algorithms. This makes the prediction more robust, because the algorithm achieves the ability to make more accurate predictions, especially when environmental factors change and can’t be completely decoded in the data foundation. This is business data science.
By breaking down the problem into sub-problems, we gain an insight that has great value for companies. It provides insight into contexts that can be used constructively in decision-making processes. It simplifies the complex business problem without losing important information.
Not all tasks call for business data science but situations where business decisions have to be made in environments that can be influenced by markets, it makes sense - and creates value.
Most of the assignments we solve, are business economics decision problems within the following areas
We provide inspiring talks to network groups, corporate management or after-hours meetings, where we focus on the many topics and insights that lead to the transformation towards becoming a data-driven company.
We offer competent feedback and 2nd opinion on business ideas, project initiatives, and roadmaps with data analytics initiatives. Depending on the company's level of ambition, it can be performed through dialogue-based feedback, or through a deeper evaluation of the problem, solution proposals and data availability.
We prepare and carry out workshops, based on the specific challenges involved in the work of performing data analytics projects and implementing the solutions in the organization. We provide methods, tools, and approaches on how to initiate necessary activities; for example, identifying the company’s data maturity, prepare an optimal roadmap or project portfolio, and we uncover pitfalls particularly relevant to data analytics initiatives.
We strengthen your ability to see business opportunities in your data, which brings competitive and unique products and services, as our business data science competences are applied.
We verify the data your solutions are to be grounded in to create confidence that the data, you intend to apply, can be used in making your data-driven business decisions. One thing is the domain experts’ capability to understand and predict based on their knowledge, another thing is to have the relevant information grounded in the data, on which the predictions are developed.
We shape your business idea in a proof of concept to verify, if business data science is feasible, and whether it can release the ambition of a cutting-edge solution.
We transform the business idea into a pilot project, to uncover and test whether the required elements of the data analytics solution are in place. Besides business data science, this can also include verification of access to data and required IT platform, as well as business engagement to shape the solution and addressing the business transformation.
We prepare a business data science solution document, which explains the outcome of applying domain knowledge, economic theory, statistical modelling and machine learning, as this is the foundation for developing the data analytics solution; a document which explains the content of the ‘back box’.
We develop the algorithms and programming code to be incorporated into your existing IT platform. At the time it’s being installed, it has been tested and trained, the prediction has been validated. Your domain competences are comfortable with the predictions as well as the validity measures identified by the confidence intervals.
We manage the launching period, when the solution start being used. We critically evaluate the results and the data applied, to verify the robustness of the algorithm. In parallel, we facilitate the required business adaption and training of users, when the new solution is taken into use.
We lead the data analytics project implementation, where we use Rooftop's Predictive Analytics Model to develop the data analytics solution and follow our customer's preferred implementation method.
Smaller enhancements. Often, in-house data scientists have a broad area of responsibility as well as project participation on the agenda, which causes enhancements not being resolved, even when business benefits are proven. Therefore, the assignments should be outsourced.
On-the-job training. The ML-techniques evolve faster than the in-house data scientist can manage to keep up with. Therefore, there is a need to find effective ways for continuously learning. Resolving the actual assignments while having hands-on-training by an expert is the best way to learn and develop data science knowledge.
Business data scientist support desk. Over time, more data accumulates, and the algorithms and coding need to be tuned. Monitoring data, measuring performance and detecting irregularities are critical, but also time consuming and can be outsourced to experts..