We believe in value driven data collection, data correlation and realtime analytic where customer journey is in focus.

Benefits

  • Focus on the outcome of the analytics and value it creates for business instead of the technology components and architecture

  • Use the business and IT data from observability and analytics solutions to generate actionable business insight to enhance customer experience

 

COMMON CHALLENGES

  • How much data to collect? Data volume drives cost rapidly and justification of the cost will be questioned if no clear value can be shown for the data collected

  • What type of data to collect? How to define use cases that can really leverage value for business?

  • As 80% of analytics effort and challenges is related with data collection, identify right data sources and understanding of the format and streaming method will be the key.

  • Do we have the right data that can provide answers? What to do when we miss critical data checkpoints that are fundamental for our KPIs?

  • How to cope with data quality issues? Data quality can be related with attributes, time stamps, frequencies, formats etc. Instead of just backing off, what is the right strategy to cope with it?

  • How to significantly reduce the lead time from data intake to analytics dashboard? What are the right tooling choices and data streaming strategies?

  • How to discover abnormality and deviation with event based AI Machine Learning?

  • Purpose to gather data and observe is for the insight, goal with the insight is for actions. How to create actionable insight are the true mission of Observe and Analytics!

 

OUR EXPERIENCE & KEY ENGAGEMENT ACTIVITIES

  • Capturing requirement & current pain areas

  • Collaborate and engage with business stakeholders to identify business value based use cases

  • Define use case KPIs and engage technical teams for data collection & validation

  • Implement data-lake realtime analytics platform

  • Build and refine realtime business analytics dashboard and create actionable insight

  • Configure events and automated event driven integration with other systems

  • Define and implement AI Machine Learning strategy and evolve through continuous improvement

  • Demonstrate value with the insight and collaborate with stakeholders