Quality Automation for Bookkeepers: Data Quality

The bookkeeping profession has long been synonymous with quality. In a world where numbers are everything, it’s important quality control is on point. Professional bookkeepers know that quality data, work processes, and reporting analytics are the pillars of quality in a bookkeeping practice.

At XBert we pride ourselves on helping you achieve the highest quality control in all of these four areas of your business, so you can focus on what really matters – building excellent relationships with your clients, and collaborating on helping them with great decisions and a flourishing business.

Quality data is the foundation of any quality control system. Without accurate and up-to-date data, it is impossible to monitor or improve the quality of bookkeeping services. Work processes and workflow automation are essential for ensuring that quality data is collected and processed efficiently.

Quality service client portals provide a way for clients to access their bookkeeping information and track the progress of their accounts. Quality reporting analytics help bookkeepers and clients to identify trends and problems so that they can be addressed quickly.

The pillars of quality in a bookkeeping practice are:

  1. Quality data
  2. Quality work process
  3. Quality reporting and analytics
  4. Quality client service

These pillars work together to ensure that bookkeeping practices provide high-quality services to their clients. Over the next four weeks, you’ll learn about these four pillars of quality automation in your business, why they’re important and how XBert will help you achieve it (with less manual work). What we’re going to focus on in this first of the Quality Automation for Bookkeepers series is the cornerstone for all bookkeepers and their clients: Quality Data.

Data quality and bookkeeping have a deeply co-dependant relationship – and unlike co-dependency in human form, this version is incredibly healthy. One cannot work without the other.

However, that doesn’t mean it’s easy. When you’re dealing with client’s less-than-professional bookkeeping, or taking on anew client – or even just growing your client base rapidly – ensuring you have all the correct information, in real time, can be tough.

What is data quality?

Data quality is the measure of the condition of data based on factors such as accuracy, completeness, consistency, reliability and whether it's up to date. Understanding and measuring the level of data quality in an organisation helps identify data errors that need to be resolved and can in turn, give key insights into whether the data can be trusted to make accurate, informed business decisions.

Why is it important?

Bad data can have significant business consequences for all sized businesses. Poor-quality data can be the bad guy behind many operational issues, inaccurate analytics and ill-conceived business strategies.

For bookkeepers and businesses, bad data quality can wreak havoc on providing accurate advice in a timely manner. Imagine putting on more staff, because your workload and cashflow permitted –only to discover many of your incoming invoices were duplicated, resulting in inflated cashflow numbers? Or, incur fines because your Superannuation Liability is outstanding? Or, realising you overpaid GST to a supplier who de-registered halfway through the tax year?

Erroneous or incomplete customer records, and fines for improper financial or regulatory compliance reporting – these are all very real issues when the data quality isn’t up to scratch.

What if the reason you have poor data quality is because of fraudulent activity? Is the source from within your team, your client's team, or external sources.

What is good data quality?

Data accuracy is a key attribute of high-quality data. To avoid transaction processing problems in operational systems and faulty results in reports and analytics, the data that's used must be correct. Inaccurate data needs to be identified, documented and fixed to ensure that business owners, executives, data analysts and other end users are working with good information.

While data quality does fall under the umbrella of responsibility for the bookkeeper – they are only as good as the data provided. And with more business owners managing the books themselves, it’s easy to have sneaky errors slip through the cracks.

Other areas of data quality that need to be considered include its completeness, consistency, lack of duplication or cross-over and its currency. When you meet all of these benchmarks consistently, you will be producing data sets that are reliable and trustworthy.

How does XBert help?

Accurate data is what we do. Starting with the transactional data itself, we help bookkeepers and business owners reduce the time manually checking for errors – and alert you to them as they arise. With more than 70 algorithms checking your Xero, MYOB and QuickBooks data multiple times a day, with quick-links to solve directly within your accounting files you will all-but-eliminate the time you spend on manual checks and rework.

Think: no more manual ABN or GST checks, ever. Duplicate bills and invoices, employee leave and junior birthday alerts, Superannuation alerts and a watch over coding inconsistencies (just to name a few)

That’s just the beginning. Find out more about how XBert can help you not only ensure quality data, all the time, but also quality workflows, quality reports and quality service.

So what are you waiting for? Start a free trial of XBert today and assure data quality in your firm, and with your client files - with less manual effort.

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