Do you only use Python?
No, the name Python Predictions originates from the Greek mythology, where the Greek god Python resided at the Oracle at Delphi. Hence, it was the first Greek god capable of predicting the future. We chose this name in 2005 for that reason only.
Python, as a coding language, has become increasingly popular recently, also in our team. But we equally use R, or even commercial software packages such as SAS or IBM SPSS. In short, we use the solution that makes most sense for a specific client.
So while we also love Python – the Python in our brand name does not refer to the programming language.
How can we assess the opportunities?
Most clients address us with a specific problem. For example, some companies aim to improve customer retention, others aim to improve new client acquisition, others aim to reduce fraudulent behavior and others aim to optimize stock levels. However, we have also helped clients with more general questions, such as: ‘is my company mature to benefit from predictive analytics?’. The time needed to perform such assessments may vary from as little as one meeting or as much as a week. Most often, such questions result in a strategic roadmap for data science projects.
How much internal expertise is required?
While some of our clients have a large team of internal data science experts, we have equally worked with companies that have no previous internal experience. In the different settings, we work towards the same goal: offering powerful predictions that can be interpreted and trusted by the business users. This means that we always strive for an optimal solution, but we aim to adapt our communication and presentation to the interests of the user, balancing the focus between managerial and/or technical aspects.
How can we collaborate practically?
Depending on the availability of hardware, software and office space, we can perform our activities at our client’s location or at our offices. Our primary goal is to perform projects from A to Z, i.e. starting from the problem definition to the solution and recommendations. Furthermore, we also offer support and guidance during the implementation of the solution in the customer’s IT infrastructure. An initial data assessment may be useful to identify and quantify opportunities.
We also offer company-specific training and coaching in the areas of data science, predictive analytics and machine learning, and customer segmentation. These courses are adapted towards the (desired) level of expertise and interests of the client.
Do you invest in analytical communities?
Absolutely. Since the launch of Python Predicitons, we have invested both time and resources in analytical communities. Most recently (since 2015), we are actively collaborating with the Brussels Data Science Community and DigitYser where we offer training for managers as well as Data Scientists. Previously, from 2012 to 2015, Python we were responsible for programming Predictive Analytics World London, an international vendor-neutral event focused on bringing together managers and practitioners in the domain of Predictive Analytics. In ancient history (from 2006 to 2009), we were heavily involved in building baqmar.eu, a large vendor-neutral Belgian community for analytics practitioners.
Is data science useful for my industry?
Data science is useful across a wide variety of industries and applications. Although retailing, e-tailing, mail-order, banking, telecommunications and subscription services provide some of the most obvious players that currently profit from data science, the methodologies and technologies used are generic and industry-independent. However, we consider an accurate definition of the business question and an understanding of a company’s strategy and tactics crucial to deliver valuable results.
Are you connected to universities & business schools?
Absolutely. We regularly provide introductory sessions about our work at respected Belgian universities such as Ghent University and KU Leuven. And we have contributed to business school programs and workshops at Solvay Business School (Belgium), Vlerick Business School (Belgium), and IÉSEG School of Management (France). Moreover, we have a long-standing structural academic collaboration with Prof. Kristof Coussement at IÉSEG (France).
Data science or predictive analytics?
Many successful data science projects contain an important predictive component. Predictive analytics is a term more often used for challenges in a business context. It refers to the methodology needed to convert historical information into valuable and accurate predictions of future events, in order to improve decision making. In this way, banks aim to predict who will repay credits, retailers aim to predict who will visit the store, and which item they will buy next, etc.
While the majority of our projects still have an important predictive component, we have also embraced other activities related to modern data science projects – often of a more exploratory nature.
Do you offer a newsletter?
Twice per year, we keep contacts informed about our latest developments and future events and presentations. If you wish to receive these informative updates, please sign up here. View an example of a newsletter here.