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  • Writer's pictureMark

How to Identify Data Inefficiencies in Your Finance and Tax Department

In the following blog, Mark presents practical tips for spotting areas for improvement in your tax and finance departments' data processes, allowing you to take the first step towards optimisation.


Data is the lifeblood of modern finance and tax departments and with the continual compression of internal deadlines and real time reporting becoming increasingly common place, inefficient data processes can be a significant roadblock to business success. Identifying these inefficiencies is the first step towards optimising your data processes and unlocking its full potential.

In this blog post, we'll explore practical tips specifically for finance and tax departments to spot areas of improvement, paving the way for increased efficiency and competitiveness.

Map Your Current Data Processes

Before you can identify inefficiencies, you must first gain a comprehensive understanding of your existing finance and tax data processes. To accomplish this, initiate a thorough mapping of each process, detailing the steps involved, data sources, key decision points, responsible stakeholders, critical dependencies, and the tools and technologies employed. This foundational step enables you to visualise your processes and pinpoint bottlenecks, redundancies or outdated processes that could be impeding progress.

Based on our experience, it is essential to recognise that this stage requires an investment of time and cross-departmental collaboration to ensure its accuracy and value. Although there may be a prevailing belief that processes are well-known, this exercise often uncovers disagreements and misunderstandings that necessitate clarifications along the way. Embracing a collaborative approach and dedicating the necessary time and resources to this step will significantly enhance its effectiveness in identifying areas for improvement.

Analyse Time and Resource Allocation in Finance and Tax Tasks

Next, assess the time and resources allocated to each financial and tax data process, focusing on tasks that consume an excessive amount of time or resources. Are employees dedicating too much time to manual, repetitive activities like data input, data transformation or reconciliation, which could be automated? Can you find instances where considerable time is spent on data tasks that are like others and, with the right enhancements or technology, could be consolidated into a single process or the data repurposed to eliminate time wastage? Recognising these opportunities will help you pinpoint areas for improvement and optimise resource allocation for maximum efficiency.

For example, a common issue is employees spending considerable time extracting relevant data from sales and purchase invoices, converting the data into the required format for VAT submissions, and reconciling these figures with their accounting records. This is really a big data exercise and implementing automation and technological solutions in this context can significantly improve upstream efficiency by streamlining data processing tasks.

While streamlining processes itself is a worthy goal, you’re also freeing up employees to focus on more value-added activities, applying their expertise and judgment to important areas such as optimising your cash positions. In the context above, it may allow you to move to a more regular VAT filing pattern, especially critical if you are in a repayment position.

Monitor Finance and Tax Data Quality

Inefficient finance and tax data processes can lead to compromised data quality. To tackle this issue, establish a robust system for identifying and reviewing recurring errors, inconsistencies, and duplicates in financial reporting, tax filings, and compliance documentation. A pattern of persistent issues may signal that your data processes need refinement or automation.

Given the numbers generated by the finance department are subject to ongoing scrutiny, continuously monitoring data integrity, such as the accuracy and consistency of financial data, is crucial. This is because it impacts the quality and effectiveness of so many key activities like budgeting, planning, and external reporting.

Enhancing data quality close to the source often presents the most significant opportunity in optimising downstream processes, as it directly affects the potential for successful automation. Keep in mind the classic adage, "garbage in, garbage out." By concentrating on improving data quality and implementing automation where feasible, you can develop a more efficient and precise finance and tax data process.

Evaluate Data Accessibility in Your Finance and Tax Department

Evaluate how easily your finance and tax employees can access the data required to make informed decisions. If your team faces difficulty locating or accessing essential financial and tax information, this may signal inefficiencies in your data processes. Consider establishing a centralised data repository or enhancing data classification and organisation to ensure that your team can readily access the necessary information.

It's crucial to provide good quality and granular data for automation, as this helps maintain the integrity of summarised information. Avoid starting with data that's been rolled up inappropriately or lacks the required level of detail. A common example is corporate tax processes that start with the consolidation system. They often rely on summarised data that omits important tax details, such as intercompany movements or other immaterial group items. While the additional granular data straight from an ERP might be overwhelming, automation tools can do the heavy lifting. By focusing on improving data accessibility and quality, you can foster a more efficient and accurate finance and tax data process.

Lastly, bear in mind that the data retention periods for finance and tax are not equal and should a tax enquiry land after finance have archived source data, providing the requested information to the tax authorities in a timely manner could be at risk.

Identify Skill Gaps in Finance and Tax Data Management

Inefficiencies in your data processes may be due to a lack of skills or expertise within your team. Conduct a skills assessment to identify any gaps in knowledge and provide targeted training or hire additional talent as needed. Investing in your team's skills will pay dividends overall by improving the efficiency and effectiveness of your data processes while also improving retention.

Solicit Feedback from Your Team

Your employees are on the front line of your data processes, so their input can be invaluable in identifying inefficiencies. Encourage open communication and regularly solicit feedback from your team regarding any challenges or pain points they may be experiencing. This will not only help you identify areas for improvement but also foster a culture of continuous improvement within your organisation.

Benchmark Against Industry Standards

Compare your data processes to industry best practices and the performance of your peers. This can help you identify areas where your processes may be lagging industry standards and provide insight into potential improvements. Keep in mind that industry standards are continuously evolving, so stay up to date with the latest trends and innovations to ensure your data processes remain competitive.

Industry standard benchmarking

Examining your tax and finance data processes in relation to industry best practices can offer valuable insights for potential improvements and enable you to set realistic goals for your organisation. Here's a closer look:

  • Understand Industry Best Practices - Research best practices in tax and finance data management and processing, including data governance, data quality management, data integration, and analytics. Familiarise yourself with key performance indicators (KPIs) pertinent to your industry that can serve as benchmarks for your organisation. Industry associations and professional organisations such as our own ICAEW and CIOT can be excellent sources of information on best practices.

  • Conduct Competitive Analysis - Assess your peer’s tax and finance data processes by investigating their strategies, tools, and technologies. This can help you evaluate your organisation's performance relative to the competition and pinpoint areas for improvement. Our experience is that colleagues in other finance and tax teams are always willing to share how they are challenging their status quo.

  • Leverage Industry Benchmarking Services - Consider utilising consulting firms to get objective evaluations of your tax and finance data processes compared to industry standards, such as MJ Solution Consulting. This can help you find areas for improvement and prioritise your efforts. Engaging external experts can also introduce fresh perspectives and innovative ideas to your organisation.

  • Track Performance and Measure Progress - Routinely monitor your tax and finance data process performance using established KPIs and compare your progress. This enables you to gauge the effectiveness of implemented changes and make data-driven decisions for further enhancement. Continuous monitoring and performance measurement are essential for maintaining competitiveness and adapting to the constantly evolving business landscape.


Finding inefficiencies in your team's data processes is a crucial step towards optimising your operations and unlocking the full potential of your data. By collaborating with your team and following the practical tips outlined in this blog post, you can spot areas of improvement, make targeted changes, and pave the way for increased efficiency, productivity, and competitiveness.

At MJ Solution Consulting, we're dedicated to helping businesses like yours streamline and optimise their data processes. Our team can help you identify inefficiencies, develop tailored solutions, and implement best practices to drive significant improvements in your data management. Reach out to us today, and let's work together to take your data processes to the next level, empowering your business to thrive in the ever-evolving digital landscape.


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