Mitch Collins examines how data can support the work of third sector organisations

Data analytics is the process of turning data into information. For example, each donor’s individual donation is data, whereas the size and frequency of all donations across a year is information. This information can then be used to inform strategy, policy or highlight patterns.

Being able to deal with and understand data is crucial for many areas of the business. Knowing about the right ways to store, evaluate and present data is important for all employees and helps organisations to get the best insights. However, with the sheer amount of data that organisations hold and process – particularly in the third sector – it can be a daunting position to know where to start to gain insight into where to start.

All organisations are on a journey to harness value from the data they hold, and we can help clients with the entire journey – from setting a data strategy to embedding a culture of analytics in the organisation.

There are five key areas in which data analytics can improve organisations:

Identify trends, patterns and high-risk issues

Understanding key trends around staff can help to inform company policy. For example, a recent piece of analysis on staff absence due to sickness revealed that employees were twice as likely to be off sick on a Monday as any other day of the week. This simple piece of analysis provided management with a key insight and prompted them to review the culture surrounding sickness absence within the organisation.

Value-add insight through statistical analysis

Data analytics can also help to provide businesses with insight as to the accuracy of reported results. Manipulations of data, such as moving transactions from one period to another to meet key deadlines or targets can be highlighted through a data analytics review. For example, we can evaluate the distribution of credit card spend in a charity to understand whether the spend peaks or troughs around certain dates or users.

Greater assurance through population testing, rather than sample testing

Data analytics can test an entire population of content, instead of just a sample. Population testing increases the chances of exceptions being found, rather than leaving the analysis up to the luck of the sample. For example, analysing an entire database of key donors to a charity would determine whether there are patterns in seasonality or regularity of donations. This can be a complex area where sample testing could provide limited insight.

Improve efficiency and effectiveness of audits through automation

A number of tests on the audit plan have repeating elements, either within the testing programme or the same test on an annual basis. For example, to provide assurance over system administrator access across a range of applications, we can create bespoke suites of tests which are turned into a script that can be run on a daily, weekly, monthly or quarterly basis. Results of this can determine whether privileged access is appropriate within the business.

Bring data and insight to life through data visualisation
Data can be presented in dashboards which are interactive and user friendly. This can be used to analyse data in a visual way, allowing users to spot patterns and trends that otherwise could be missed. The display also allows for easy interpretation, making it ideal for communicating high level results in reports or demonstrating the success of specific fundraising events or sources of funding.

Mitch Collins is technology audit manager at Scott-Moncrieff