Knowing how to capture the right data and use it efficiently isn’t just helpful; it’s a necessity. Capturing and processing data still requires significant human intervention; whilst automation (in the form of Robotic Process Automation or RPA) and now AI continue to refine and enhance the process, it is yet to eradicate the need for data capture specialists.  

These technological advancements have certainly, over the years, helped to greatly increase processing volumes and the speed at which they are handled. They minimise inaccuracies and can even help identify patterns. The question is, what does all this mean for the future of data capture workforces?  

The Impact of AI on Data Capture Processes 

Data capture has long stood as a pivotal process in the realm of information gathering. It encompasses the collection of data from various sources (text, images, PDFs, voice recordings, and more). The primary objective is to collect valuable data and convert it into a format that can be processed, analysed, sold, and so much more. 

For years now, technological advancement has been revolutionising the data capture landscape. AI and automation tools have helped to drive an efficient, streamlined, and powerful process. In fact, the market for automatic data capture and identification tools is expected to grow to a value of $134.7 billion by 2032.  

How AI Improves the Data Capture Process

AI-driven solutions offer sophisticated capabilities for the extraction, recognition, and interpretation of data, potentially minimising human intervention.  

With artificial intelligence, companies can: 

• Improve data quality: With adaptive learning and machine learning tools, companies can benefit from systems that automatically adjust processes and improve the accuracy and quality of the data captured for assessment.  
• Translate raw data into insights: Data analysis is a complex process which requires significant expertise. While AI may not yet be able to match the skills of an experienced data analyst, it can help identify data and rapidly offer insights into potential trends and patterns, making the data captured by businesses more valuable.  
• Streamline complex data capture: AI tools can capture complicated data from a variety of structured, semi-structured, and unstructured documents. Pre-processing tools can even annotate key data fields and ensure data is labelled correctly for analysts.  
• Accelerate data capture: AI tools can capture data from systems, processes, and interactions in real time. This reduces the need for employees to spend endless hours creating notes and uploading documents into systems. Real-time tracking also ensures companies can maintain complete visibility into their operations.  
• Automate data validation: Manually validating data can be a time-consuming and error-prone process. AI-based solutions can enhance the processing workflow, using templates and pre-implemented methods to validate and identify data. The right tools can even ensure data is stored in the right place or sent to the correct teams.  

AI and Data Capture Experts: Better Together

So, if AI in the data capture landscape is so powerful, does it eliminate the need for data capture experts, such as data entry professionals and analysts? Simply put, the answer is a resounding no. While McKinsey suggests about 64% of data collection activities can be “automated”, many companies have discovered that the best results come from using AI tools and human skills in tandem.  

AI can certainly help data capture experts accomplish more in less time and even improve the accuracy of data capture strategies. However, data capture experts are still necessary for many parts of the process. For instance, AI can use machine learning to attempt to determine which forms of data need to be captured for your business, but it can’t effectively separate the best insights for your business goals from endless volumes of data points.  

AI tools also have a number of limitations. AI tools, despite their capabilities, do come with certain limitations. Even if they’re trained to detect and redact personally identifiable information from documents, there are instances where important details can be overlooked – particularly where the format of the data source varies or is inconsistent in structure. Some solutions can make mistakes when processing data, and others struggle to process certain forms of unstructured data with a high level of accuracy. Such limitations can have significant impacts on businesses when it comes to data protection regulations.  

Additionally, AI can only handle so much of the data collection and analysis process. It can collect data rapidly but can’t always check it for correctness or convert information into valuable formats, consider medical data or allergen information, for example. The accuracy of this data is essential; mistakes can be a danger to life. Can we, or would we, ever be inclined to trust that process to ever go ahead without human interaction? Many of our client projects use a blend of OCR technology and human agents in a hybrid solution, leveraging both the advantages of technology and the skills of a data capture specialist. For example, OCR might read a form/document/label image of a product, and a human data capture agent perform a QA check to ensure the data aligns with processing rules and third-party regulations and corrects any OCR errors, thus feeding back to the OCR system and improving the technology.  

Ultimately, AI is having a positive impact on the data capture landscape, just like it’s leading to progress in various other business operations and tasks. However, it’s simply a tool that can help to improve efficiency, scale data processes, and boost productivity. It’s not a replacement for human experts. AI should be seen as an assistant for data professionals.  

It should empower these experts to be more effective, efficient, and accurate in their roles than ever before, allowing them to unlock better results for businesses. While AI is a powerful tool for positive change, it’s not a magic solution for every data entry or management problem. If you’re planning on implementing AI into your ecosystem, don’t rush it. Consider what you want to achieve and engage with those delivering that task currently; they are the data experts and will have valuable perspectives and insights into the best use of AI technology and where it can play the most effective role. 

Take the time, consider the applications that can best benefit your business and teams, and make sure you’re leveraging the right combination of machine intelligence and human expertise.  

Why not engage with an expert data capture outsourcer who can help you identify the right approach to solve your challenges and unlock value in your data?  

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So, delivering good customer service must be balanced against keeping costs as low as possible. At the same time, it’s vital to understand and manage compliance with ever-changing industry regulation – balancing a complex set of requirements around the Licence Conditions is tricky – and understanding the constant flow of information from the regulator and changing government policy is vital to ensuring that your business model stays compliant. 

Sounds simple, right? Of course not! That’s why partnering with organisations across the sector that can specialise in certain aspects can be so fundamental to success.   

Why is getting it right from the start so important? 

We’ve been working with energy suppliers for many years and have seen the full range of issues as they occur. Experience tells us that energy is not an industry that forgives easily – It can be very difficult to recover service levels from a build-up of errors– but can you stop issues from occurring in the first place?

The first critical stepping-stone is to try and solve customer problems on first contact, which can stop issues from escalating and means less bad debt further down the line. A customer is unlikely to settle a bill in dispute – so as soon as you can resolve the issue, the sooner the bill will be paid, and the debt is unlikely to escalate, compounding the problem. But how do you avoid those expensive customer contacts in the first place? 

Reducing Customer Contact  

Getting the first bill right is critical to preventing errors from snowballing (and avoids that first customer inbound contact) and means you can build up a trusted relationship with a consumer.  That means suppliers should be taking a razor-sharp focus on the onboarding of new customers. 

Some key questions that you should be asking yourself before things start to go wrong. Do you have the correct data from your customers, and do you know what your system does with that data?  Where are the gaps?  Who is working on the issues, both in terms of preventing them and solving them? 

First things first – have you gathered the right data from customers to make sure you can bill them?  Has the first Direct Debit been collected correctly? Are you actively checking for failure, and is the data you’ve got from the previous supplier correct?   

Getting your systems set up correctly is critical here, too – have you got debt tolerance and meter read tolerance set correctly, for example?  Too tight, and you will get ‘pinged’ with errors and failed bills constantly, and too loose, you’ll set yourself up for disaster further down the line when large amounts of debit or credit may build up in the system, impacting cash flow and damaging customer trust. 

Lots of questions, but how about some answers?  

Granted, we focussed a lot there on potential pitfalls and things to consider. But, when in business are things simple, when do we get the luxury of having to consider only one or two things? The good news is that there are people and organisations that can help.  

As an outsourcer with extensive experience in utilities, we have helped solve many of these issues for energy suppliers. From end-to-end processes to a more modular approach. Each supplier is different, and therefore, so is our approach to solution design.   

Key to our offering is being able to support from both a customer-facing perspective and also working on back office tasks in the background, ensuring everything is running smoothly. It gives us a holistic view so our experienced agents can truly support customers and avoid future contact.  

Get in touch to learn more.