5 Advanced Technology Examples to Improve Your Business

These automated bots are excellent at carrying out repetitive jobs much faster and with more precision than their human counterparts. The ”bots” in RPA are simply programs that are specifically configured to perform particular tasks, like data entry, supply chain management, and data gathering.

Bots can operate 24/7 without assistance and make fewer mistakes than humans when assigned data-oriented tasks. This allows your staff to spend less time on the manual labor, and more time on analysis.  

By alleviating your employees of repetitive and perhaps monotonous tasks they used to perform, RPA can effectively improve the employee experience by making everyone’s lives easier.  

“With 80 million jobs in the US considered good candidates for automation, it’s no surprise people are scrambling to implement automation solutions in their organizations.”

RPA is a rapidly growing market worldwide, and there are more solutions available to businesses of all sizes than ever before. In fact, the global RPA market is growing so fast it’s currently projected to grow from $10.01 billion in 2022 to $43.52 billion in 2029. This further demonstrates just how fast this industry is growing and how many organizations are adopting RPA solutions worldwide. 

2. Document Data Extraction

Intelligent methods for extracting data and processing them is another example of a modern technology solution. Document data extraction is a software that quickly scans documents, knowing what information to look for, and pulls it automatically.  

Oftentimes, this data is then exported to a more usable format, such as a spreadsheet or other database.  

For many years, workers have become accustomed to transcribing data from a document and manually entering it into a system of record.

Data extraction allows users to extract meaningful information hidden inside unstructured data sources.

Purchase orders, client documents, customer records, invoices—all and more can be quickly and easily scanned for information in an accurate manner, improving data validation. Data extraction software combined with machine learning will improve the programs' ability to handle datasets over time.

Document data extraction is also especially useful when dealing with unstructured documents. Unstructured documents are those that lack easily quantitative data and therefore require more sophisticated scanning software. Blogs, videos, pdfs, images, and other free-form mediums are all examples of unstructured data.   

Vendors like DocuWare are increasingly able to provide these functions to SMBs in full while keeping affordability in mind.

Another benefit of having a data extraction system in place is the ability to store your data exactly where you need it. Processed document information can be output into multiple systems and be associated with existing data for easy integration, visualization, or other analysis.  

According to a study by McKinsey Digital, CEOs spend almost 20% of their time on work that could be automated (like analyzing operational data and reviewing status reports).

Document Data Extraction in Action

Document data extraction is a common application of automation in business.

Consider a business processing applications for its services manually, requiring employees to review PDF documents and then input the data they see into their work computer. 

This takes many hours and decision-makers are dissatisfied with how slowly it takes staff to respond, so they implement a document data extraction solution to help.

Now, using the solution, PDFs are automatically parsed, scanning each field and reporting the information to a repository, where an RPA bot can then take over the process. Extracting data from documents like this means the team can spend their time doing more valuable operational work. 

3. Workflow Tools

One of the chief concerns of a business undergoing a digital transformation is improving data workflow within the One of the chief concerns of a business undergoing a digital transformation is improving the data available to the organization. Fortunately, new advances in business technology offer ample opportunity for creating better data sets and streamlining workflows.

With modern technology examples like document management, digitized data can now be efficiently processed and stored. From here, it’s a relatively simple step to get that data downstream to the right people at the right time, regardless of department.

Workflow tools, specifically cloud-based systems, are excellent at providing platforms for organizing work processes and projects within teams, ultimately granting key players more visibility over their role within the context of larger projects.  

The functionality of these tools extends to management best practices, such as approval routing, data validation, and ensuring the integrity of data before it goes into your ERP system.

Workflow Tools in Action

We had a client, WaterTech, come to us with concerns about their document management. They relied heavily on paper-based processes and felt that their system was significantly slowing down their operations, particularly with regard to the sales order process.

4. AI Assistants

AI assistants are becoming increasingly popular. With ChatGPT and Google Bard finding their way into endless headlines and Siri or Google Assistant in our homes and phones, AI assistants are an innovative technology that can be wonderful assets when used properly.

One of the most common technology examples of automated tech in business is the use of chatbots. Think smaller versions of ChatGPT – like the automatic chat bots that pop up on a website when you’re browsing.  

People engage with bots for customer service more than ever, and businesses are more frequently utilizing chatbots in their organizations. 

“58% of companies in a B2B sector actively use chatbots, compared to 42% of B2C companies.”

They are excellent at solving simple issues, while more complex problems can be escalated and sent on to the right people within the organization.

This means a lighter load for staff who can now focus on the more complex issues and value-based customer service interactions.

In the past, it was common for people to have an aversion to dealing with AI assistants, but new technology means a litany of improved functions such as AI-assisted voice recognition and sentiment analysis of messages and emails. 

As a result, the majority of customers feel more comfortable than ever interacting with AI and AI chatbots in specific.

For businesses, the goal of this is to get the relevant people involved as soon as possible while streamlining engagement with the client, without sacrificing the quality of the customer experience.

AI Assistants in Action

A business is consistently being swarmed by customer queries about its products and services. Customer support staff are replying as fast as they can, but it’s not enough, and customers are bouncing, losing them business.

They decide to implement a chatbot that can answer the most frequent questions quickly to site visitors, alleviating staff from repetitive questions and allowing them to spend more time on other queries that need their time.

They are able to respond quickly and handle multiple requests simultaneously using the chatbot. 

Chatbots are also scalable, meaning if there’s an influx of users, they can be scaled up to accommodate demand and then scaled down during less busy periods.

5. Low-Code Applications

The current rate of expansion for the managed services market is a result of SMBs increasing their expectations for what platforms they use in every aspect of their business, from their customer relationship manager (CRM) to their mobile platform.

The gap between off-the-shelf software capabilities and the needs of workers on the ground is growing.

Companies want customized solutions for unique processes, and when they don’t have the correct procedures, users take matters into their own hands, inventing ad-hoc methods to fill the gaps.

This will typically lead to tribal knowledge and siloed organizations, making tasks like onboarding new hires difficult. Fortunately, industry-leading low-code platforms like Mendix are readily available to SMBs of any size and offer the opportunity to address needs an off-the-shelf solution cannot.

Low-code development means easy to use app-building tools which can tackle or optimize complex and detailed tasks. It’s as simple as dragging and dropping, takes less time than regular development, and can help organizations create a whole suite of unique solutions for their processes.

“In North America, nearly 60% of all custom apps are now built outside the IT department by professionals who have little or no IT coding experience.” 

Whether it improves customer engagement or operational efficiencies, low-code platforms can offer enterprise-level apps for a fraction of the price for SMBs.