The Center of Analytics at Grant Thornton is designed to provide research and analytical services for internal and external user groups with in-depth insights about their services using the state-of-the-art tools of data analysis and business intelligence, data mining, statistical modeling, and machine learning.
Depending on the task, our team is ready to go well beyond traditional data analysis techniques, and by discovering patterns in the data, we aim to give our clients intuitive and key understanding about their customers, business, and operational processes to help them gain a competitive advantage in the respective industry. Our solutions are designed for companies from diverse industries, and from data processing, modeling, and visualization to business understanding and result interpretation, we have a well-designed and highly automated data analytics pipeline to deliver the outcomes with high quality and in a timely manner.
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Data Analytics at Grant Thornton offers solutions in two major directions:
Advanced Visualization through Dashboards: To monitor the health of your business processes, we analyze and display key performance indicators for a better visual understanding. In case you have dynamic data, our dashboards can incorporate data changes and display updates in real-time.
Descriptive Analytics: Includes utilizing data and statistical analysis techniques to analyze your historic data and see what happened in the past or is currently happening. Examples may include modeling correlation in the context of finding relationships or conducting hypotheses testing about various operational processes. Subfields of Descriptive Analytics include Performance Analysis to quantify the performance of your company over a given period, Retention-Rate Analysis to improve your customer acquisition and retention activities, Cash-Cycle and Working-Capital analyses for making key operational and policy decisions, and Consumer-Behavior analysis to help in understanding how customers decide on a certain product.
Statistical inference and Machine Learning: By building statistical models based on data availability, we can predict how likely your employees are to stay in your company, diagnose medical disorders, find the optimal number of customer segments or assign probabilities to possible fraudulent transactions. If you have data that depends on time, we can utilize time-series analysis techniques to do budget, consumption, or sales forecasting.
We later use the findings obtained from your data to come up with the optimal set of recommendations to enhance the long-term growth of your company. Tableau, IDEA, SQL, Python and their cross-platform integrations are extensively used to deliver the best outcome for each specific case study.
Our team of highly skilled professionals in data analysis and visualization, finance, programming, and statistical modeling are always willing to dive deep into your data to fully understand your business needs and help you be part of the digital data-driven transformation.