What is RPA?

Robotic Process Automation (RPA) is the utilization of programming with machine learning and AI capacities to deal with high-volume, repeatable tasks, and transactions. RPA is an innovation planned for computerizing business forms. Robotic Process Automation conveys direct productivity and improves accuracy transforming an organization’s workflow. Empowering RPA allows flexibility within the enterprise. Programming robots are easy to…

Summary:  Based on a McKinsey study we reported that 47% of companies had at least one AI/ML implementation in place.  Looking back at the data and the dominance of RPA as the most widely reported instance makes us think that the number is probably significantly lower.

We’ve been trying to get a handle on…

Summary:  Digital Decisioning Platforms is a new segment identified by Forrester that marries Business Process Automation, Business Rules Management, and Advanced Analytics.  For platform developers it’s a new way to slice the market.  For users it eases integration of predictive models into the production environment.

As…

Summary:  Advanced analytics and AI are the fourth great lever available to create organic improvement in corporations.  We’ll describe why this one is different from the first three and why the CEO needs the direct help of data scientists to make this happen.

If you’re a CEO or any other flavor of top executive leading a…

All businesses are at the mercy of data quality challenges. From the moment you capture your first lead, you’ll be fighting a battle against data decay. The bigger the database gets, the more problems the business can encounter, and it isn’t easy to single out a…

A simple metaphor for projects in predictive analytics

The analytical scene has recently been dominated by the prediction that we would soon experience an important shortage of analytical talent. As a response, academic programs and massive open online courses (MOOCs) have sprung up like mushrooms after the rain, all with the purpose of developing skills for the analyst or its more modern counterpart, the data scientist. However, in the …

For statistical process control, a number of single charts that jointly monitor both process mean and variability recently have been developed. For quality control-related hypothesis testing, however, there has been little analogous development of joint mean-variance tests: only one two-sample statistic that is not computationally intensive has been designed specifically for the one-sided test of Ho: Mean2<=Mean1 and StDev2<=StDev1 vs. Ha: Mean2>Mean1 OR StDev2>StDev1 (see…