
Transforming Telco: AI in Telecommunications
Based on our previous work with telcos and our research, we have identified many impactful AI-led use cases.
Manual document processing is tedious, expensive, and prone to human error. Yet many organizations continue using traditional systems that drain productivity.
Intelligent document processing (IDP) solutions promise to alleviate these issues through automated data extraction, validation, and routing.
However, before investing in this technology, it is fundamental to be able to evaluate IDP’s economic potential.
In this article, we’ll analyze the costs and possible ROI of implementing an IDP system. It will explore examples and use cases from two regions, North America and APAC, respectively, examining metrics such as processing costs, document turnaround, productivity costs, and ROI.
Whether you are considering initial IDP adoption or looking to maximize an existing deployment, this deep dive will uncover best practice calculations for using AI to unlock the full value in your organization’s documents.
What exactly is the return on investment (ROI) of implementing an IDP system? First, let’s examine the baseline costs of relying on manual document processing, which typically consists of time-intensive data entry and document review by employees.
In the following example, I’ve taken approximate US-based figures to build a hypothetic use case, please be aware that figures and costs will vary according to each company’s individual needs. Key cost drivers include:
When looked at more granularly across common business functions, the costs add up:
As you can see, even relatively short manual document processing times add up to major costs, especially for large organizations with thousands of documents being handled each week.
The aim of most of the IDP systems is to completely automate the process so that no time is spent by a person. Due to the process’ complexity it’s not always possible, especially at the initial stages of the system. In that case, the aim becomes to minimize the time spent by a person and make the process as easy as possible for them.
The person who interacts with the results of the IDP system is called human-in-the-loop (HIL). They are usually, but not necessarily, the same person who was doing the job manually before IDP system was introduced.
The effects IDP system has on the HIL in the process include:
All of the following calculations are based on this concept, though in more advanced systems scenarios, HIL involvement might be reduced to 0.
The costs above reveal the potential for automation using intelligent document processing. IDP software utilizes advanced AI and machine learning to automatically classify documents, extract and validate key fields of data, and route information through appropriate workflows.
Let’s analyze sample cost savings from the different business functions above when transitioning from manual to automated IDP-based document processing. We’ll assume the IDP solution implementation costs are $400,000, with $100,000 spent annually, including any licensing fees, IT support/maintenance, and allowances for incremental bandwidth and storage.
Accounts Payable
Contracts
Onboarding
Lending
Total IDP Annual Cost Savings = $846,435
As shown above, the cost savings from transitioning these common document processing workflows from manual data entry to an intelligent automation solution like IDP are substantial, even for a relatively small organization.
The more documents and heavier reliance on manual processing, the greater the savings grow.
Now we have crunched the numbers on cost savings, let’s continue our analysis to calculate IDP ROI and payback period.
First, we’ll recap the key figures from our savings above:
A payback period measured in months rather than years further showcases why intelligent automation delivers such a fast, material ROI for organizations.
The larger the rollout, the faster the investment pays for itself.
We’ve seen the significant cost savings and impressive ROI possible from deploying intelligent document processing now here are three key strategies organizations should consider to maximize returns:
1. Prioritize high-volume workflows
As the numbers above illustrate, processes like Accounts Payable invoicing lend themselves extremely well to automation, with thousands of repetitive documents to process daily. Focus initial IDP solutions on these document types.
2. Phase deployments thoughtfully
While an enterprise-wide rollout might provide the largest ROI, a gradual deployment allows for pilots, training, and change management to smooth the transition. Target fixes first for known pain points.
3. Combine IDP with other intelligent technologies
Integrating IDP with chatbots, RPA, natural language processing and more creates an automation multiplier effect. The solutions build on each other for even greater gains.
Neurons Lab collaborated with a partner in the APAC region that aims to process approximately 220,000 receipts per month for its 44 clients. The traditional manual approach to this task is not only labor-intensive but also fraught with hidden costs and risks.
To handle this volume of receipts, it would be necessary to employ a team equal to 46 FTE (full-time equivalent), given that the average processing time for each receipt is about 2 minutes. With a minimum wage of $320 the financial burden quickly adds up. The cost of 46 FTE needed to process these receipts manually results in a monthly expense of approximately $14,720.
Let’s consider that the expense of operating a cloud-based system to distribute tasks among the workers is $100 per month.
The manual solution is not just expensive; it’s also insecure due to high employee turnover, requires constant training for new hires, and is vulnerable to HR issues such as absenteeism. This model is unsustainable in the long run.
We’ve analyzed several scenarios to illustrate the cost savings our IDP solution offers. Please note that we include the cost of running of the manual (base) process during the implementation period in the implementation costs of the IDP solution.
In this scenario:
Result: Solution is profitable in 14 months after launch.
In this scenario:
Result: Solution is profitable in 17 months after launch.
These scenarios demonstrate that the IDP solution becomes profitable relatively quickly and offers significant monthly savings compared to the manual processing method.
Question: Is there an optimal point in time, when it’s most cost-effective to make an investment into the solution’s development and integration?
While it may seem intuitive to initiate the implementation of an IDP solution early on to reap benefits sooner, this is not always the case. Starting too early, when the client base is limited, can actually prolong the payoff period due to the initially low document volume. Our analysis indicates that there is a strategic moment for starting development that optimizes the payoff period.
Identifying the Optimal Investment Window
Determining the most advantageous time to invest in an IDP solution depends on two factors:
Investing in an IDP solution is most beneficial when a significant increase in the number of documents is anticipated. This strategic timing ensures that the solution is ready to handle the increased workload, leading to faster payoff and greater cost savings. Notably, this significant increase in volume might only be possible, and is enabled in the first place due to IDP solution integration.
The current processing volume of documents also plays a role in the investment decision. To minimize the time to achieve a return on investment, it may be advantageous to postpone the investment until there is a sufficient volume of documents being processed. Considering the significant expense associated with IDP implementation, it is wise to consider IDP once the business is mature enough.
The operational efficiencies and cost savings made possible by intelligent document processing are too substantial to ignore. As the examples and ROI calculations above illustrate, IDP solutions offer a fast track to material productivity improvements and headcount cost reductions.
Of course, financial returns are only one part of the equation – enhanced data quality, improved compliance, superior customer experience and freed up employee time for strategic work are intangible yet vital IDP benefits as well.
With the stellar ROIs involved, organizations that fail to explore intelligent document processing run the risk of severely lagging behind competitors who have already added IDP to their automation arsenal. The numbers don’t lie – integrating this innovative technology should be a top priority for nearly any enterprise today.
Neurons Lab delivers AI transformation services to guide enterprises into the new era of AI. Our approach covers the complete AI spectrum, combining leadership alignment with technology integration to deliver measurable outcomes.
As an AWS Advanced Partner and GenAI competency holder, we have successfully delivered tailored AI solutions to over 100 clients, including Fortune 500 companies and governmental organizations.
Based on our previous work with telcos and our research, we have identified many impactful AI-led use cases.
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