The tech and telecom industry is dynamic. When firms evolve or expand quickly, their monthly, quarterly and annual financial close processes can become more complicated.
Financial close processes are often more manual and time-consuming than the other processes in a tech or telecom firm. These processes don’t receive daily attention, but their inefficiencies create a loss of business value every time a financial close rolls around.
Common inefficiencies come from:
- data inconsistencies across source systems
- errors in posting of entries
- gaps in accruals and prepayments
- a poorly structured chart of accounts
- manual offline calculations in spreadsheets
- local close calendars that don’t work for worldwide collaboration
“The challenges of the close process lead to inefficiencies, errors, increased risk, higher cost, lower employee morale and the inability to retain talent.”
“The challenges of the close process lead to inefficiencies, errors, increased risk, higher cost, lower employee morale and the inability to retain talent,” said Grant Thornton Transformation Director Justin Quan.
That’s why many tech and telecom firms are trying to streamline their financial close processes. To streamline the processes, firms must look for opportunities to:
- reduce the manual touchpoints
- ensure data is accessible
- ensure data is accurate
Intelligent automation technologies can play an essential role in achieving these three goals and streamlining financial close processes. In our recent tech CFO survey, more than 90% of respondents plan to continue or increase their investment in automation this year.
For financial close processes, streamlined automation can generate business value at the end of every month, quarter and year. It also supports strategic business goals like:
- lower costs from streamlined infrastructure, more efficient use of resources and reduced manual processing
- reduced risks from fewer errors, with decreased audit issues and less risk for financial misrepresentation
- less time required, with automation and built-in business rules that reduce rework and manual tasks, freeing up resource time
- better retention and satisfaction from more time directed to value-added activities, making employees happier, more easily retained, and more likely to improve customer satisfaction
To achieve these benefits, it’s important to map your financial close processes to the right mix of automation options.
Understand your automation options for financial close
Every tech or telecom firm works with a unique set of business processes, systems and other factors to complete its financial close. That’s why firms can select a mix of automation technologies to tailor a streamlined solution.
To automate your financial close, you can integrate six key automation technologies. These technologies can scale as your needs grow or other solutions change. It’s important to analyze and identify the right technologies and the right timing to automate your unique processes.
- Intelligent character recognition (ICR)
Advances in machine learning and image technology can give you data collection options, even when you cannot standardize templates from suppliers. ICR can even work with handwritten information.
- Robotic process automation (RPA)
This technology is central to automating standard manual tasks — particularly repetitive tasks — which saves money and lets analysts spend more time on higher-value work.
- Data analytics and visualization
Data visualization tools, like dashboards, can play a key part in monitoring processes and other business outcomes for financial close. With the right solution, this can be a much more efficient and effective way to derive insights from your data.
- Predictive analytics and machine learning
Trying to map out the future is a core function of financial operations. But, the increasingly turbulent business environment in the tech and telecom industry means that predictive models must constantly evolve. Predictive analytics and machine learning in accounting functions can help you quickly analyze the latest data and evolve ahead of the competition.
- Low code application platforms
Tech and telecom firms often have employees who are working across unintegrated business systems, and who can envision more efficient solutions. Low-code and no-code platforms can help them improve their experiences while also driving efficiencies.
- Natural language processing
Natural language processing can derive meaning from unstructured or non-standardized data, like contracts from outside parties. This can help turn extensive searches and other manual processing work into streamlined reviews and confirmations.
How can these technologies combine to form a financial close solution?
Grant Thornton National Managing Principal for Transformation Roy Nicholson cited one example, from a firm that had to reconcile about 1,190 bank transactions each month. The firm was using two systems, and it kept encountering inconsistencies.
The project’s automation solution needed to address some complex issues. “This automation runs for three days solid, going through the reconciliations and also managing some of the exceptions,” Nicholson said. As automation technologies advance, the technologies can streamline increasingly complex work.
Automation in your financial close process can ultimately connect with other systems to empower new paradigms and drive digital transformation across your organization.
Given all of the options available, it’s important to know how to make the right choices.
Choose the right options for your financial close
To streamline your work effectively, you need to analyze your unique needs, data and other considerations:
- Define which technologies will be appropriate for the specific business and process.
- Create a “data lake” repository of information, which can be structured or unstructured, depending on the processing solution.
- Establish rules that use logic, digital intelligence and other analytical methods to identify deviations to correct before the process begins.
- Use future-ready technology for processing and throughout the organization to ensure broad compatibility.
- Monitor any anomalies in the data with strong internal controls and a master data governance framework.
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