Here’s Why You Should Audit Your System Reports For Human Error

By PRETTY BOOKS ON November 14, 2022
HERE'S WHY is a collection of simple explanations for the things in your business that just don't make sense. There are a lot of moving parts in your business, and not all of them are obvious. Here's Why gets right to the point in identifying what's happening, why, and what you can do to improve your operations. Here's the deal, you need clarity in your finances to make data driven decisions for your company.

Last year you purchased a new software to track and manage your inventory. It was rated 5 stars, and had a training package, to ensure your people are trained properly. Now, a year later, you’re having trouble making sense of the numbers reported. The numbers don’t seem to align with your understanding of your actual operations, and you aren’t sure why. Here’s the deal, you haven’t set up a process to account for human error.

Why? People aren’t perfect.

The software may be highly sophisticated, but if data isn’t entered correctly, it will create issues. Across the board, if people are entering information that is not well managed, it will cause errors. The accuracy of the data outputted is only as good as what’s put in it. Over time, even small errors can impact the accuracy of the reports generated by the software.

Imagine this. You have a warehouse manager who records the inventory shipment that enters the warehouse. Every time a shipment comes in, they log it into the software. What if that manager didn’t record a shipment, and the inventory count every now and again? Recording inventory coming in is just one component of your inventory process. There are a lot more areas of inventory, from inputting purchase orders to setting up pricing, it leaves room for human error. Imagine if things are missed across all areas of your inventory software. Your reports from this software could lose its accuracy. If the data isn’t clean, your reports may not be as meaningful.

Why? You haven’t created clear processes

When your company does not have written policies and documentations, knowledge is lost with every transition. Is there a well documented and cohesive process for inputting data that can be referenced? Are your expectations for the people managing this data clear and well communicated? Do your operators have access to documentation and FAQs in case certain scenarios arise? If you do not have documentation, then they are forced to improvise if something goes awry. Their approach to solving the problem may not always produce the correct and accurate data you require.

Aside from documentation, the lack of connection between the goals of the software and the company overall can also lead to data errors. Overall, if your team and operator do not know how their work impacts the company, it will naturally lead to a lack of concern and follow-up when issues arise. Over time, any errors could compile and affect the reports you generate.

It is important to align your team with what is important. What issues are you trying to solve with this software? What are your goals for this technology? You need to communicate to everyone involved with the system what their role is, how their work impacts the business, and what to do if something does not go as planned. Make sure you revise your policies periodically in order to maintain the most updated knowledge about your system and processes.

Why? You didn’t take time to build an audit process.

Unless there is an audit process in place, you might not be able to tell if there are any misinterpretations on how to use the system. The way the system is set up to collect data must be consistent with the way data is input. Complications around how the system recognizes units, metrics, and quantity impacts the overall understanding of your data.

Imagine this. You asked your employee to input the price of eggs into your inventory software, so they find the price on the purchase order and input it. But now, looking back on your numbers, something doesn’t seem to add up. It seems like an easy enough task, but the software has it’s own way to input pricing that might not coincide with what’s on your purchase order. There’s a big difference between the price of a single egg and two dozen eggs. If you input the wrong price, your software’s data will be very inaccurate.

You need to set up a system to make sure your people understand how your system reads data. Your operators need to be in alignment on the units, metrics, and conversions of data. Set up collaborative effort to evaluate and assess the quality of your operators’ work, the quality of the data, and the quality of your processes frequently. During this process check for consistency, any possible errors, and any loopholes in your processes. If you are proactive about auditing processes and data, you will be able to continuously refine your standards and align your expectations for your people and data.

Check for inconsistencies in the systems themselves, too. Systems go through updates all the time, and any one of them could affect how it reads and calculates data. It isn’t uncommon to find engineering or mathematical misalignment coming directly from the software system itself.

How do I manage my data systems?

It’s important to note that missed entries and operator “human error” is a two way street. It is a concoction resulted from the company’s oversight of people and processes, and a lack of connectivity between people and systems.

  1. Align your people. When you bring on a new software, make sure that everyone who operates and uses the system is on the same page. Everyone needs to know what the goal of the system is, what it is trying to solve, and how their work impacts the success of the company.
  2. Have clear, written processes. Make sure everything about how data is input and managed is well documented, including unique scenarios that may come up and frequently asked questions. Have protocols in place to support people in their work and create an overall sense of proactiveness.
  3. Audit your data. Work with your financial analytics team and develop a process to periodically audit the data from this system. You need to sample the data to check for consistency, human errors, and system errors to ensure that the data you are reviewing and the reports being generated are reliable and meaningful and in alignment with reality.

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The information provided in this post is for general informational and educational purposes only and is not a substitute for professional advice. Consult your financial, business, or tax advisor with respect to matters referenced in this post. Pretty Books assumes no liability for actions taken in reliance upon this information.
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