Using data for our audits can help improve efficiency.
But not only in a traditional sense.
Audit efficiency and audit effectiveness are important objectives.
Most discussions about using data to achieve those objectives have an inward focus.
How can we make our audits more efficient?
The audit team's process, as opposed to broader efficiency.
We can extend that. To consider efficiency outside of the audit team.
You can make a whole bunch of tweaks within the audit team. Changing audit processes to be more efficient.
But where you're going to get far better value is beyond the audit team.
By also focusing on efficiency for the organization.
Efficiency, effectiveness, economy and ethics are the core areas that we help with.
Efficiency is something that we are very aware of. Particularly when we need to deliver more with available resources. Which is always.
With slower economic growth and rising public deficits, members of the public expect service delivery to be efficient. Sometimes we characterize this as removing waste in the system.
We want to focus on efficiency, but don't always know how to do it.
Back to the earlier point. Think outside of the audit function, focusing on our stakeholders. How can we make their lives easier? How can we adapt our audits to make the organization more efficient?
There are several solutions. One of those is the use of data.
Using data can help us with:
1. Audit efficiency [Internal focus]
2. Auditing efficiency, or efficiency as an audit objective [External focus]
3. Making consumption of audit deliverables more efficient [Internal and external focus]
4. Making remediation more efficient [External focus]
Using data for our own audit purposes. Relying on data to drive efficiency in how we conduct our audits.
There are a couple of pressures on audit leaders.
First, sometimes people consider audit to be a corporate function. A back-office function. We need to get better at describing our work to shift that perception. We need to play our part in running our own business with efficiency. So, we need to make sure that we're taking all opportunities to make our audit function efficient. We want to show our counterparts in other divisions that we're in this with them.
Second, we can't perform efficiency audits without turning the lens on ourselves. We can't draw conclusions or make recommendations about how the business could be more efficient, if we're not prepared to do the same. We must use the same yardstick to measure ourselves.
Okay, so we want to make our process and our function more efficient. Can we use data to do that?
Yes, but it depends on the nature of the audits that we undertake.
If you are doing the same sorts of audits every year, or involved in some form of continuous monitoring or auditing. Yes, easy.
If you are doing a range of individual audits every year, and the audit topics are new each time. Not so easy. It is a bit more difficult to get efficiency out of those audits. Many IA functions that have adopted newer approaches will have plans that are not static; the topics change.
There is still room for efficiency. But it takes time and it requires a deliberate approach. For example, you can gain some efficiency where there is overlap in data that you might need to use for different audits. But to achieve this, you need to share the intel and the data among the team, as described here.
In general. Using data within audits often produces higher effectiveness dividends than efficiency returns.
Don’t despair – the next three outcomes are far more positive.
Where we audit efficiency. Where one of our audit objectives is to determine whether something (e.g., a service or a program) is efficient.
Internal auditors are shifting towards more audits where efficiency is an audit objective.
Performance auditors have already focused on efficiency as an audit objective for some time. So there’s a lot that IA can learn from performance auditors in this respect.
How does data help with this?
Performance audits are usually conducted within the public sector by Supreme Audit Institutions, Auditors-General or Comptrollers. These audits aim to determine whether we’re getting the most out of the available resources. Quality and quantity. From the inputs provided. Are we optimizing to achieve a given outcome?
These audits used to follow a more traditional, paper-based approach. This made it difficult to understand all the inputs needed to drive a certain outcome. It was a bit more difficult to get the full picture - how efficient a particular program or service or outcome measure was.
This has changed. With the growing use of data, we can get a more complete picture. A better understanding of what the inputs used to deliver a particular outcome are. Then determining whether that is efficient.
This sometimes involves the use of statistical techniques to determine efficiency. Examples include Stochastic Frontier Analysis, Data Envelopment Analysis and the Free Disposal Hull technique. These are not bulletproof, but data analysis is rarely an exact science. There is potential for bias, but the models provide a better answer than not having anything at all, of course. The models are not perfect, but not completely wrong either.
Data helps identify efficiency gaps and process efficiency opportunities.
Whether you use one of the statistical models or focus on basic techniques to analyse processes, data helps achieve the audit goal.
Making it easier to read and develop our audit reports.
How can we use data to drive efficiencies in the creation and use of our audit products?
Audit reports can be lengthy. If they are also text heavy, we risk not connecting with our audience and diluting the impact of our work.
Report writing, like many aspects of our audits, has been evolving. We look for ways to make it easier to understand our reports. We remove jargon, write in plainer English and use diagrams and infographics.
Many audit leaders have been working with their teams to incorporate auditviz (data visualization) into their reporting.
Where we use graphs and charts in our reporting, the reader doesn’t have to waste time in trying to read and re-read to understand our words.
Here is an example:
This auditviz represents relative efficiency scores for services provided by 46 entities.
It is compelling and easy to understand for a few reasons:
So, in this example, the individual council model is often less efficient than others.
Auditviz like these can be supported by text. They convey messages and outcomes quickly to help the audience “see” the results.
The graphs help make that English explanation come to life. It makes for a faster, easier read. You often don’t even have to explain each of the data points. In fact, as we do this more often, the words are the support and the graph becomes the primary component. The words then exist to focus attention or remove ambiguity.
Auditviz makes it easier and faster for our audience to read our report. The consumption of the report becomes more efficient. And who doesn't like to save time reading reports.
In some cases, even writing the report becomes more efficient. You can start with the picture and explain what you are focusing on, to direct the reader’s attention. This can be easier than trying to write the explanation out without the graph as an aid.
Yes, it takes time to check accuracy. It takes time to present those visuals to suit the audience. Removing anything that is not necessary. Making sure that there is minimal risk of misinterpretation. But as with any work that we do, it gets easier and faster with experience.
And review. Audit reports generally go through various layers of review. If you make the review process easier, the effort will decrease.
At first, the review process might take a bit longer than usual. As people get to grips with a different style of report – asking questions like “what are we seeing in this visual?”, “does it make sense”, “can we release it”, etc.
Over time, that review process may become more efficient than it was before you introduced auditviz.
Making it easier to address the actions flowing from an audit.
How can we use data to streamline the approach to remediating gaps?
This has the potential to save even more time than the time we saved with the reporting improvement above. But this may not be at the executive level.
Consider our traditional audit approach. We sometimes make broad sweeping statements about control failures or process gaps. Then there needs to be further action by auditees to identify specific control weaknesses and issues before they can fix them.
We can make that situation a lot easier on management if we use data to identify the specific issues. Not always possible, but data often makes it easier to see what the root causes of those issues are. This is different to the traditional, pure controls testing approach. Identifying real gaps, not only theoretical gaps. It's still important to test controls. It's still important to go beyond the initial remedial action. But where you are also using data, you can identify the specific issue - where the control failure has created a real loss or potential loss. This is probably what needs to be fixed first.
Easier for management to sequence their remediation activity. A starting point to preface further remediation. Potential savings for the organization. In summary, audit enabling efficiency.
The benefits of using data for efficiency, and audit efficiency, are clear.
By considering each of the four items here, we can create better outcomes for all. The audit team. Our stakeholders. Our customers and citizens will reap the rewards of our efforts.