Data analytics

Turning the opportunity into a competitive advantage requires proactive use of analytics and proactive changes to people, process, and technology.

Data analytics. Data analysis is the process of inspecting, cleaning, transforming, and modelling data to test systems, transactions and the integrity of data. BDO Digital Advisory uses data analysis techniques to analyse large volumes of data, while looking for anomalies, patterns and exceptions. This allows for a complete coverage of all transactions. From data analysis and data mining, reports are built to provide management with new decision-making tools and identification of new opportunities, resulting in competitive advantage.

Business Performance Insights. Businesses struggle with obtaining a cross-silo view of the firm. Additionally, business functions can make decisions that benefit their own objectives without taking into consideration how the entire system is impacted. This can lead to business decisions that appear optimised but that are in fact sub-optimal from a holistic organisation perspective. Our business performance insights combine data from the supply chain, operations, sales, and human resources functions to help you identify the cross-functional drivers of business performance. Displayed in an intuitive and graphical manner, these insights will enable to make business-wide decisions with confidence.

  • Forecasting. Businesses typically forecast future performance using historical accounting data. However, accounting data seldom possesses the level of granularity required to perform robust forecasting. BDO’s forecasting analytics make use of detailed information generated by the various business processes to forecast performance. Additionally, the forecasting process includes scenario testing that will enable you to visualise the impact on your business - should low probability events occur (e.g. black swans).
  • Forensic Analytics. The perpetration of fraud is one of the major challenges that faces private and public sector entities. Various methods exist for the identification of potential fraud, one of which is data analytics. We use pattern analysis to identify suspicious transactions, narrowing down the amount of manual analysis and investigative work that the forensic team needs to perform.
  • Advance Analytics. Advanced data analytics can help drive innovative business decision making. Advanced analytics and reporting use sophisticated tools for data mining, big data and predictive analytics to mine data for important trends, patterns, and performance. As the amount of valuable data any company gathers increases, so will the need to use that data for insights that provide a competitive advantage.
  • Data mining. The process is the discovery, through large data sets, of patterns, relationships and insights that guide our clients in measuring and managing where they are and predicting where they will be in the future.
  • Predictive analytics. Predictive analytics is the process of using data analytics to make predictions (based on data). Our process uses data along with analysis, statistics, and machine learning techniques to create a predictive model for forecasting future events.
  • Data conversion and system data interface reviews. Data conversion is the translation of data into a new and different format. CAATS are commonly used to test data conversions when a new system is implemented and where data is transferred from one system to another. These tests are done to ensure the integrity of data is maintained once it is converted and transferred into another system or database.
  • IT due diligence reviews. CAATS are also increasingly being performed in due diligence reviews and company valuations. Analysis of data and the use of business intelligence provide a great deal of information to investigations and valuations. In many cases CAATS allow for a more in depth and complete view of an organisation, especially when 100% of the data is analysed.