Data AnalysisFinding needles in haystacks |
The challenge
There are two distinct flavours to data analysis:
- Diagnostic analysis is of an audit nature, where we are holding up a mirror to data and saying this is what it looks like. Typically it will be used to reconcile financial information and takes advantage of many of our proprietary tools.
- Value added analysis sets out with a specific decision making or business process purpose in mind such as predicting marketing responses or supporting revenue assurance.
The exponential growth in data volumes has led to numerous opportunities for data analysis to add value. Typical examples include:
- Industry
- Financial services: uncovering unusual trends or activity to identify fraud.
- Retail: predicting customer behaviour to reduce churn.
- Function
- Audit: identifying poorly designed controls.
- Finance: analysing revenue drivers.
Irrespective of industry or function, it is vital to establish an empirical data quality baseline to build upon.
Getting the right information to the right people at the right time is critical to developing and maintaining competitive advantage. Yet organisations are constantly challenged by both the quality of their data and the increase in its quantity as they look to derive value.
How we can help you
By providing you with objective, statistically valid information, we can help you to improve the decision-making process and reach informed, clear conclusions. Whether you need a simple analysis of operational data involving a few key measurements, or you need to develop new insights into a complex business operation, we have the tools and expertise to help you.
By making use of profiling technologies to set a foundation on which to improve, we can help you move from a data quality culture based on mistrust and doubt to one of confidence and belief in the data underpinning both your operations and management information.
We aim to deliver valuable business insights that allow you to make better decisions and increase the performance of your business. The Data Management practice combines industry, functional and technical expertise. This combination enables the practice to embed solutions into business as usual practices, as well as being able to perform one-off analysis engagements.
