Tableau Software : How visual analytics helps audit and risk professionals shorten time to insight

The single biggest key to success is ensuring that finance and audit domain expertise is supported by team members who have equally strong knowledge in data acquisition and data preparation. It definitely takes both of these skills for success with self-service data analytics. Having completed over 200 successful, data-driven internal audit projects across a variety of industries, we Visual Risk IQ continually see that this combination of skills is required.

Borrowing from the Association of Professional Research Analysts, who have developed a Body of Knowledge specific for data analytics in the fund-raising world, we have found that similar areas of expertise are needed for successful data analytics for finance and audit professionals:

1. Project management
2. Data acquisition and manipulation
3. Statistical techniques
4. Visual reporting techniques
5. Communication
6. Finance and audit domain expertise
7. Change management and strategic thinking

All of the above skills are rarely if ever found in the same individual, hence we believe that finance and audit-focused data analytics should definitely be considered a team sport instead of an individual one. And that supplementing audit or finance skills with data-specific and visual reporting schools is an especially powerful idea.

In our experience, the visual reporting techniques are often the least developed skills from this Body of Knowledge in the finance and internal audit community. Finance professionals are very quick to run confirmatory queries to identify issues; for example, confirming if any invoices have been dated prior to a purchase order date. But instead of first exploring the number of days between invoices and purchase orders to understand the average or a minimum or maximum number of days, a confirmatory table that says 'list all if Date A is prior to Date B' is too often considered an ultimate answer. Perhaps finance and audit professionals are better with confirmatory queries because scripting languages and traditional report writers are better tools for developing confirmatory queries than they are for developing exploratory queries.

Exploratory queries lead to data discovery and aligns better with the future of self-service, data analytics. Special IT or programming skills are no longer needed because modern tools like Tableau make exploring and analyzing populations of data easier. It only takes a few clicks to rank or sort transactions from largest to smallest or oldest to newest. And together with a few filters, an interactive dashboard can be created for exploration and finding greater insights than ever possible with spreadsheets or scripting languages.

For more on visual reporting techniques including matching your chart type to your business question, we recommend Stephen Few's Show me the Numbers book and blog. One of the most important techniques for visual reporting done with Tableau are dashboard actions and 'viz within a viz' where a high-level exploratory chart (e.g., time series or part-to-whole) can be used to select or filter a Ranking chart specific to a category or date range. This allows the person who is asking and answering an initial question to solve their next question without additional programming.