About Us

WSTBZ Consulting Limited has partnered with MedEquality to deliver proven predictive analytics (data analytics) services to companies that are seeking to provide more insightful and actionable answers to their most common questions as well as more future-looking answers and recommendations to questions that cannot be addressed at all by business intelligence.

When people in financial sectors discuss about the banks of the future–they generally refer to external things that banks will have in the future. Highly advanced equipment like sensors and touch screens inside the office furniture that are connected to the IoT, that is, banks will have an appealing and attractive appearance to the customers, etc. However, the reality to the banks of future depends on what will happen internally – the decision making processes in financial institutions will become completely data driven with the extensive adoption of data science discipline in finance.

Big data essentially means all data and, as we know, data as such are meaningless. In order to harness true benefits, big data needs to be turned into actionable data, with a clear focus on the purpose, (combined) insights, actions and resulting outcomes. The true value of data lies in its application to a business process: the way it is being actioned in a business and/or customer context. To achieve that, relevant data need to be extracted and inserted into a business workflow to automate the specific business transaction. When process optimization enhances the real-time customer experience, it becomes even more valuable: it becomes critical for long term business success.

Given the nascent state of data science, it often falls to data scientists to fashion their own tools and even conduct academic-style research. WSTBZ and its partner have data scientists who are academically qualified and possess strong business savvy and curiosity to be able to make discoveries that can be communicated to business leaders as actionable insights.

Predictive analytics builds analytical models at the lowest levels of the business—at the individual customer, product, campaign, store, and device levels—and looks for predictable behaviours, propensities, and business rules that can be used to predict the likelihood of certain behaviours and actions. It takes the questions that business intelligence is answering to the next level, moving from a retrospective set of answers to a set of answers focused on predicting performance and prescribing specific actions or recommendations.

Before the era of Big Data, business analysts needed to aggregate data in order to have enough points to predict with reasonable confidence. Now we can develop predictions at the individual customer level, without the need to aggregate the data, for example, at the store level. WSTBZ advances the use of predictive analytics and specific tools to optimize its client resources as they look to make business decisions and take actions for the future.