Data & Analytics | KPMG | LV
Data & Analytics

Data & Analytics

Data & Analytics

D&A

D&A

Data and analytics services.

Data & Analytics

KPMG projects involving Data & Analytics solution development here in Latvia have helped our clients increase revenue, decrease costs, automate processes and gain better understanding of their cost drivers as well as make educated pricing decisions.

We have defined 5 types of Data & Analytics services that help bring our clients value:

  • Management reporting and analytics automation, KPIs & dashboards;
  • Data quality improvement, automation of data extraction, transformation, loading (ETL);
  • Predictive analytics, machine learning, cognitive computing and AI;
  • Robotic Process Automation (RPA);
  • Analytical model development, e.g. pricing models, cost allocation models.

Read on below to find out more about our services.

Data analytics

Management reporting and analytics automation, KPIs & dashboards

  • Review of existing reports to identify potential for consolidation & automation
  • Support in choosing the optimal Business Intelligence platform
  • Development of automated tools, including management dashboard design and development in QlikView, QlikSense, Power BI, Excel, other
  • Recommendations for industry specific KPIs definition, process optimization and management reporting framework improvements

Key questions:

  • Is significant manual work involved in preparing reports?
  • Is there large number of internal reports with no clear structure?
  • Are your reports prepared in time?
  • Are your reports easily comprehensible, and dynamic?
  • Are your decisions supported by your data?

Data quality improvement, automation of data extraction, transformation, loading (ETL)

  • Algorithm development

Key questions:

  • Does lack of data quality requireregular manual work prior to analytics?
  • Are there regular, standardized manual tasksinvolved in analytics?
  • Is there low trust in data & analytics?

Predictive analytics, machine learning, cognitive computing and AI

  • Customer analytics – cross sale, upsale, dormant client activation
  • Location analytics – branch/store/atm network optimization
  • Process optimization – through automated analytics of ERP/CRM data
  • BI and Data Analytics strategy and governance
  • Predictive asset management and maintenance
  • Churn & dissatisfaction prediction models, revenue forecasting

Key questions:

  • Is application of innovative technologies and analytics one of priorities for gaining a competitive advantage?

Robotic Process Automation (RPA)

  • Blue Prism & Automation Anywhere

Key questions:

  • Is significant manual work involved in execution of routine rule based tasks?
  • Full automation of standardized tasks. i.e. invoice creation, payroll, policy/cards cancellation, preparation & sending of client specific info, claim registration, etc

Analytical model development, e.g. pricing models, cost allocation models

Key questions:

  • Do you know the cost of the product?
  • Can you do the product/service pricing quickly and in a standardized way?

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