We start with an assessment of how you manage your product or service quality today (including people, processes, data) and your customer's key pain points. We then identify your top three opportunities for improvement based on customer perception and experience analysis. Finally, we work with you to implement and sustain improvement recommendations.
We help organizations define and document their Operating Model (processes required to get things done), key roles/owners and governance structure.
As more and more businesses digitize their operating models, rich data sets become available to potentially assess the customer experience. This engagement allows organizations to identify leading indicators in the data and build analytics to predict customer experience.
Over the past several years, Python has become the leading platform for development of machine learning algorithms. This engagement allows an organization to develop in-house competency on Python for Data-Science. This training is designed to take individuals from zero Python proficiency to the level of expertise required to implement Machine Learning algorithms. Depending on the organizational needs, the training could start with a review of basic Python, and include Numpy library, Panda library, Matplotlib library, Tensorflow library and Scikit-learn library.