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OUR MULTI STAGE PROCESS OF IDENTIFYING KEY CUSTOMER NEEDS TO CREATING STATISTICAL DATA MODELLING LEADS TO A SELF LEARNING SYSTEM.

Process loops

Discovery workshop

We conduct Discovery workshops to identify and prioritise the problems and challenges the organization faces.

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Identify feasible initiatives

We identify a broad spectrum of initiatives and select ones that are most likely to deliver value to the customer.

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Plan experiment

We create a cross functional task force to look at data from different domains. This helps the organization identify focus areas for experimentation.

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Execute - Implement Experiment

We create an experiment funnel and select projects to implement. To simulate scenarios that the organization will have to face in real time, we design experiments that represent challenges.

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Industrialize

From the lessons learnt from experimentation we move to data industrialisation. Industrialisation is automation – we move from what was done manually to automating.

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Analyze - Review

Experimentation establishes correlation between data. However the real value of data comes from its predictive capabilities.

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Process loops

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