Why IDP and iPaaS are the Future of Business Automation
For organizations searching for ways to improve the efficiency of core processes and maximize profitability, business automation is the clear solution.
This once meant implementing robotic process automation (RPA) technology. While this technology still has its place in the digital landscape, an innovative automation tool focused on integration has taken the market by storm.
Over the last 18-24 months, iPaaS or “integration Platform as a Service” has experienced exponential growth because it offers several advantages as a standalone integration solution and a supplemental technology to existing RPA architecture.
What Is iPaaS?
Generally speaking, an iPaaS tool is an automation platform capable of standardizing how various applications are integrated into an organization’s overall business model. This allows IT staff to implement automation more quickly, especially at scale. An iPaaS will also facilitate the sharing of data across multiple applications.
The goal of iPaaS is similar to that of RPAs. Both solutions seek to eliminate redundant manual processes and minimize an organization’s dependence on spreadsheets.
Simultaneously, iPaaS is geared towards increasing accuracy, speed, and visibility across an organization.
RPA to iPaaS: Evolution, Not Extinction
Integration Platform as a Service is a truly innovative business process automation technology. However, it is not going to mark the extinction of RPAs.
Instead, iPaaS should be viewed as the natural evolution of the long-standing RPA technology.
For some businesses, RPA systems still present the most viable solution for their integration needs. Specifically, RPAs are beneficial for organizations that only need to replicate a few very specific tasks and have the technical resources available to do so.
However, iPaaS is a much more elegant solution. As many iPaaS vendors have expanded their platform’s capabilities to include workflow and basic process automation functionality, it helps shorten the flow of non-duplication.
An iPaaS also provides organizations with superior scalability, which is valuable for large companies and growing businesses. It offers a versatile and user-friendly experience, which means that a variety of industries can successfully integrate iPaaS solutions.
True No-Code Integration Solutions
iPaaS is an excellent solution for organizations that are integrating new applications and those that want to upgrade from an RPA system. For businesses that choose to, moving from RPA to iPaaS is a seamless process that can be completed efficiently.
In addition, integration Platform as a Service offers a true no-code experience, which is perhaps the most appealing aspect of the solution.
While many RPA companies refer to their technology as “low code” solutions, building out bots often requires a relatively high level of coding competency. RPA solutions are more developer-friendly, but they might not provide the most streamlined experience for the average user.
iPaaS applications have a much simpler interface. Average end-users with basic digital competency can eliminate redundancies and integrate applications that would otherwise not communicate.
Data Behind iPaaS: Intelligent Document Processing
Any type of application, whether it is iPaaS, RPA or another workflow tool, needs structured data to make it work. When users implement an intelligent document processing (IDP) system, it transforms process-dependent documents into machine-readable and actionable data which different systems can use for that business process or task. It knows which software to call on to get the job done. Having a way to onboard document-centric information in the right format using IDP is how companies can get the best results from iPaaS and drive hyperautomation enterprise-wide.
Measurable Benefits of Modern Business Automation Technologies
While automation technology has been in existence for decades, many industries still do not leverage these solutions to their maximum potential.
For instance, a 2021 Ephesoft survey revealed that only 15% of accounting departments are entirely paperless. Two-thirds still rely on manual invoice processing. This overreliance on manual processing drastically hinders the productivity of an organization.
Conversely, both IDP and iPaaS can boost efficiency across various facets of a company’s operations. Organizations can leverage cloud business process automation to improve multiple departments, including finance, compliance and HR. The leading benefits are productivity, efficiency, accuracy and cost-savings.
IDP technology customers reported all of these benefits and more:
Innovative Automation Solutions from Ephesoft
Ephesoft is committed to providing our customers with valuable IDP solutions that transform work productivity and wrap it in a great experience. Our team is constantly challenging the status quo to provide maximum value to our clients. With those goals in mind, we are also among the first organizations to embrace iPaaS as a leader in intelligent document processing as we embrace the synergies and powerful automations IDP + iPaaS can deliver. Whether you want to increase your platform’s performance by 10X, reduce validation time of invoices or need to reduce customer onboarding times from days to hours, we can help. Ephesoft will provide you with tailored solutions that meet the unique needs of your organization. Get your free trial today.
Taking Digital Transformation into the Cloud
Enterprises understand the need for automation, digital transformation, data intelligence and accelerated processes. Cloud capabilities are what make these critical initiatives achievable goals. Whether you are a small business looking to automate your document-centric processes without the added burden of server management or a global enterprise aiming to take advantage of cloud capabilities and ensure business continuity, Ephesoft’s cloud can provide the capture tools you need.
Market Trends
According to Flexera’s 2020 State of Tech Spend Report, cloud spend finally surpassed on-premises software spend. In a survey conducted in 2019, more than 80% of the study respondents reported that they planned to increase their Software-as-a-Service (SaaS), Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) spend in 2020. Despite technology survey results, concern about cloud usage from security-conscious organizations for storing, processing or routing documents and data have not fallen by the wayside.
Companies of all sizes have embraced mission-critical business tools like CRM and ERP in the cloud as SaaS solutions. Look at the wild success of applications like Salesforce and NetSuite, respectively. Why not extend the same principles to documents and data? Flexera found that the top IT initiatives for enterprise organizations are digital transformation, cybersecurity and the shift to the cloud. Given this focus and the increased tech spend, industries like Financial Services that previously refrained from cloud usage, are going to start dipping their toes in the waters of the cyber sky.
Coupled with the fact that Gartner predicts SaaS will be the largest category of cloud computing, we’re looking at a major change in the way businesses interact with technology vendors and the manner in which companies demand cloud continuity for their line of business applications. It’s unreasonable to look at any type of trend or market analysis without taking a world-wide health crisis into consideration, though. And in the wake of the global pandemic, business continuity and security are key concerns for companies in every industry. Even though IDC projects a slower growth rate of 2.1% for cloud applications than previous predictions, it is still the largest area of anticipated spend for everything IT-related.
It’s crucial for companies to adopt a cloud-first approach to operational tasks and projects if they want to remain competitive and profitable. Enterprises around the world still need to unlock and access their valuable information to better serve their customers. With the new version of Ephesoft Cloud and service/feature pack 2020.1.2, this transformation can be easier and faster.
As the market drives toward remote needs for the enterprise and a cloud-first mentality, we’re embracing the change with a refresh of our public cloud offering to support capture in the cloud to drive digital transformation of the future. Transact Cloud is a global single tenant cloud solution that transforms your physical documents into usable data by automatically identifying document types, extracting key information and delivering them directly to any type of repository or workflow.
Hosted in the Amazon Web Services cloud (AWS), Transact Cloud provides secure, scalable, intelligent data capture capabilities for organizations to automate their document processing without the added burden and expense of server management. Transact Cloud customers can go live in hours – our SLA is within 24 hours – compared to the days, weeks or months often required for on-premises deployment.
With the latest version, we’ve also added data import functionality from AWS S3 buckets, server performance monitoring, and accelerated feature deployment for continuous product updates. Something a lot of companies don’t consider when looking at the comparison between cloud subscriptions and on-premises purchases is the cost of IT overhead for internal (or contractor) employee time to manage and support the software application. When you factor in the (difficult to calculate) opportunity cost associated with cash flow and potential investments of a large upfront purchase versus a smaller year over year spend with a subscription, the monetary benefits weigh heavily in favor of the cloud. Ephesoft’s intent is to be able to provide hosted, subscription-based capture solutions with a lower cost of ownership and capital expenditure to cloud clients.
Security
Forefront on everyone’s mind when you talk about the cloud is security, so I want to highlight how Ephesoft is working toward creating a secure environment for a company’s data productivity needs.
Ephesoft achieved SOC 2 compliance and we adhere to standards for securely handling data. Transact Cloud has been evaluated by independent third-party security and vulnerability assessment companies. There are automated dynamic and static code scanning tools built into the engineering pipeline. The Ephesoft engineering team regularly completes security awareness training. And finally, data is secured and encrypted in transit and at rest.
With COVID-19 in mind, continuity is crucial for line of business applications. AWS has numerous global regions where they offer their services. An availability zone is a data center in a region. Each zone in a region has redundant and separate power, networking and connectivity to reduce the likelihood of two zones failing simultaneously. At Ephesoft, we select regions with at least 3 availability zones to ensure high availability. Customers are allocated instances across different availability zones. For example, Customer A will have an instance in Zone A and in Zone B – so they will not be affected if one of the zones goes down.
For security purposes, we allocate within our Virtual Private Cloud separate customer-specific security groups. A security group acts as a virtual firewall for your instance to control inbound and outbound traffic. The security group is set to only allow in connections from the load balancer or the jump host. And to minimize the chance of a host attack, Ephesoft administrators connect via a VPN connection to a Jump Host.
New Capabilities
The AWS import plug-in is built for large volume document import and easier collaboration for both cloud and on-premises users. As AWS consumption soars, we realized how important it was to have the native ability to ingest content with an S3 plugin. An AWS S3 bucket operates as an additional ingestion point into Ephesoft Transact, expanding from your traditional ingestion points like email, folder monitoring and Web Services calls for mid-workflow document capture processing. Using the S3 Import plugin, a batch class – the document capture configuration – can be configured to import files from an S3 bucket. Once the plugin is configured, the S3 bucket is monitored every minute for new files. When new files are detected, Transact uploads the files into your specific batch class, and the file is removed from the bucket after processing. This makes for an efficient processing workflow of large file volumes in Ephesoft Transact.
Another new set of features for Transact 2020.1 Service/Feature Pack 2, available in the Ephesoft Cloud, is the ability to capture handprint data, optical marks and perform signature detection without having to create templates or fixed forms. If you look at the panel on the left hand side of the screen in the screenshot below, new fields have been added to the Key Value rule configurations that allow an administrator to select what type of extraction method they’d like to use for document data capture, including handprint. For capturing handprint data (using an ICR engine for text conversion) administrators will not have to open a separate tool or user interface to define zonal locations on a page for handprint capture rules.
Similarly, check box detection – or OMR for form features like radio buttons or toggles – can be configured using this same Key Value approach to capture the data. This saves administrators time and effort when creating a batch class designed to capture this visual data from a document.
This new key value configuration mechanism comes in handy when defining variables for extraction like signatures. When working with highly unstructured documents like contracts or packets of mortgage loan documents, the ability to perform signature detection without having to specify a specific region on a page provides flexibility and scalability to any capture project.
The mortgage industry presents countless ideal use cases for capture in the cloud. Unlike invoice processing or mailroom workflows, which present a fairly steady stream of physical and paper documents that need to be ingested, categorized and indexed, mortgage documents are often received or processed in bursts at very high volume. Turn-around time is crucial, and we’re going to increasingly see the need for remote (or distributed) account opening and loan closure processes.
In the last several weeks I bought a new house and sold my old house, and I can say from personal experience, financial institutions are scrambling to keep up with the changing pandemic guidelines, support people who require remote closing and in general just work with the huge volume of content at a pace that’s acceptable to their clients.
Cloud-based capture solutions are ideal for mortgage use cases and more. At Ephesoft, we have a depth of experience working with customers in this particular financial services niche and supporting the cloud needs of small businesses and enterprise organizations. It's time to take digital transformation into the cloud!
Watch the webinar on BrightTALK starting on August 27. Register here. Learn more about Transact Cloud here.
Improve Productivity with Ephesoft Mobile
Research shows that almost 90% of your workforce uses mobile devices for calls, emails, calendar, texts and communication apps. And those employees that use their mobile devices for work tasks save 58 minutes each day. For companies that have embraced a mobile strategy, this comes out to an additional 240 hours of work per employee every year. It’s a logical leap. Your sales manager can respond to that demonstration inquiry while walking to the café for a coffee. The accountant can approve an invoice for payment while sitting on the train on their commute home.
Syntonic tells us that 87% of businesses are dependent on their employee’s ability to access mobile business apps from their smartphone, like SalesForce, Slack, Expensify and Zoom. So why not extend content acquisition to your mobile device as well? Why not take advantage of these powerful, portable devices by enabling in-the-field document capture for true, integrated process automation? If employees and clients are already using phones for content-related activities, it would be an oversight to not give them the power to contribute to/participate in business workflows that require document upload.
Ephesoft Mobile provides an easy, reliable and secure way to ingest and upload content into Ephesoft Transact from any mobile device, which accelerates workflow and business processes. The mobile app features live edge detection, foolproof image cropping and enhancement filters. Supported in iOS and Android operating systems, all communication is kept secure by utilizing HTTPS protocols. Moreover, no documents or information are ever stored on the device itself.
Ephesoft Mobile can improve workflow efficiency with minimal configuration to integrate this new capture source into your existing business process. It helps feed time-sensitive information into those crucial back-end applications and databases from anywhere in the field. Given all of the shelter in place and likely long-term work from home strategies in place at companies of all sizes right now, this kind of field flexibility for content acquisition is going to be crucial for maintaining profitable business operations.
Lastly, Ephesoft Mobile can increase productivity of end-users both internal – like your employees – and external – like your clients or constituents. The flexibility of how this can be deployed is key here. One way is that it can be embedded in your organization’s app with the mobile Software Developer Kit (SDK). Simply customize your company app by embedding Ephesoft’s mobile content acquisition technology into your native application for seamless and transparent on-the-fly capture. Alternatively, you can skip the customization work and go-live immediately by using Ephesoft’s out-of-the-box application along with our globally accessible web-based Administrative Portal.
Let’s review some industry-specific use cases for Mobile to put the productivity potential into perspective.
Use Case: Healthcare
The applicability of Ephesoft Mobile to expedite infectious disease screening is clear. The process starts when screening forms and IDs are captured on a tablet or phone with Ephesoft’s Mobile. Ephesoft Transact QuickScreen – an ID-specific capture component of Transact – can automatically extract IDs from more than 200 countries (and the variations within US states). The app then passes the documents to Ephesoft Transact, a secure processing server which can either be installed on-premises or hosted in the cloud, depending on the clients’ or industry security requirements. Transact then identifies the type of document that was captured, extracts the necessary metadata data and validates against a third party database. Finally, it passes the indexing information to a database and repository for archiving purposes.
This solution has the potential to reduce wait times in lines for drive-through screening – like many states are experiencing with long queues for COVID-19 tests, provide real-time data on important feedback elements like flagging duplicate test recipients, and help with the creation of that patient’s record from the moment of the first touchpoint.
Use Case: Financial Services
Customer onboarding for banks can be a complex process requiring a mix of customer-sourced, digital and physical documents. Acquiring usable documents from your prospective customer can be a challenge given the variety of methods financial institutions receive documentation and the slow responses from the applicant. Think about how many times you’ve applied for a loan, opened a new account, or applied for pre-approval for a mortgage where you’ve had to find a way to scan and email a copy of your driver’s license or a bank statement and other documents to that company. Now think about the employee at the bank that had to take that scanned image, and manually enter all your details into their system of record or application for actuarial review.
Instead of this manual process, take advantage of Ephesoft Mobile as the capture source for all these documents by embedding it into your company’s app with our Mobile SDK. Applicants can capture and send all necessary documents from the comfort of their own home, and you receive the information in real-time. Used in conjunction with Ephesoft Transact for automated document categorization and data extraction, all sources of documents are acquired and then processed securely and quickly. With the historically low interest rates for new and refinanced mortgages, lending institutions are going to be flooded with new applications, Ephesoft can alleviate the burden of data collection.
Resources:
- View the recorded webinar here.
- Read more about Ephesoft Mobile here.
- Watch a demo of Ephesoft Transact QuickScreen solutions in this video.
Top 4 Tech Predictions for 2020: Focus on Building Context
In this fast-paced era of ever-changing technology trends, the race for better and accelerated processes and content automation is continually leading the pack. Positions like Data Scientist and AI Subject Matter Expert have taken a giant leap as some of the leading careers in technology to help evolve what enterprises around the world both want and need. Let’s take a look at some of the top tech trends in which we see our customers and partners pinpointing as essential strategies in 2020.
#1: Cloud-only and SaaS, I/PaaS
According to Flexera’s 2020 State of Tech Spend Report, cloud spend (including SaaS and I/PaaS) has finally surpassed on-premises software spend. More than 80% of the study respondents surveyed report they plan to increase SaaS and I/PaaS spend next year. Yet, the reluctance expressed by many security-conscious organizations for storing, processing or routing documents and data in and through the cloud remains.
Companies of all sizes have embraced mission-critical business tools like CRM and ERP in the cloud as SaaS solutions. Look at the wild success of applications like Salesforce and NetSuite, respectively. Why not extend the same principles to documents and data? Flexera found that the top IT initiatives for enterprise organizations are digital transformation, cybersecurity and the shift to the cloud. Given this focus and the increased tech spend, companies will see industries, like Financial Services, that previously refrained from cloud usage, start to dip their toes in the waters of the cyber sky.
#2: A continuation of departmental-only rollouts of RPA systems
Recently, a consultancy partner expressed some dissatisfaction with using robotic processing automation (RPA) tools. Specifically, they were taking a step back from leading with RPA as a tool for digital transformation initiatives. The sentiment was that RPA on its own doesn’t actually overhaul business processes or address issues stemming from inefficient workflows. It simply makes slow processes faster. And many of the analysts agree, as is evident in this rant article from one particularly dissatisfied industry expert or and this disappointed recap of the state of RPA.
The inherent flaw in the methodology of RPA vendors is the almost exclusive focus on automation rather than true transformation. Boiled down to the most basic level, RPA companies license their software by bot count. The more processes, the more bots, the greater the purchase price. It is not in an RPA vendor’s best interest to solve a problem or perform the due diligence required to identify useless or superfluous processes. And with that myopic gaze, enterprise success will have a limit
The consultancies and RPA-partners that work with their clients for true process-evaluation and deep analysis of business workflow will have the greatest success and highest likelihood of true digital transformation.
#3: A surge in machine learning-powered point solutions
This year we witnessed a handful of veteran technology companies and emergent startups announce purportedly machine learning (ML) capture platforms with varying degrees of success and follow through. Chasing the elusive market share of this unavoidable
Having the framework in place to leverage ML algorithms to automatically identify and extract data from unstructured content isn’t the challenge. The hurdles to surmount are in-house (or outsourced) industry expertise and access to a large enough sample set of data to deliver an ML model that can automate the identification and extraction of data from go-live. Customers don’t want to invest the time and effort into providing that knowledge and content in addition to paying for access or a license to use the solution. A common refrain, voiced by the discontented consumer is, “You’re telling me it’s going to take a year of processing documents before I actually see the results?” If you’re promoting an ML-only application without a specific use case framework in place, that will likely be the case.
In 2020, we predict a greater focus on point solutions for industry or department-specific capture use cases. Successful startups with a small customer base will develop niche solutions that tackle documents and data within a specific and narrow industry. Larger software vendors with a more robust network will be able to expand their ML-driven capture offering to a greater number of use cases with a shorter ramp-up timeline. To survive and thrive in this ML-mad climate, specialization in the form of point solutions will be critical.
#4: Conflux of Big Data and machine learning: Context is king.
Big Data has been trending in the technology industry for the better part of a decade. Experts and analysts alike predicted that Big Data would solve all problems in the world through its intrinsic value, realized by predictive analytics. The focus on Big Data predated machine learning as an ideal solution by a few years, but the mania of ML and its potential to automate workflows and provide insights matches that of Big Data.
However, the value of Big Data and the illuminations it can provide is only as good as the source of the data, its completeness and its cleanliness. With a primary focus on structured data (and the process of cleansing it), most data scientists only interact with a fraction of the organizational data available to them. This means they have an incomplete picture of the information they’re working to manipulate. Similarly, the ML model created is only as good as the samples used and human input provided to build it
So what do we get in the Vesica Pisces when the circles of Big Data and machine learning overlap? The answer is Context. It is the realization of all that potential and hype when Big Data is inclusive of unstructured content and ML models are created by industry experts and designed to alleviate informational problems. 2020 is the year when Context will reign King.
Better Capture to Fuel your RPA
Having the right content capture platform for RPA is necessary to ensure your project’s success. After attending UiPath Forward’s recent conference, we’ll discuss why the industry is talking about the importance of intelligent capture, how it relates to Ephesoft’s Activities in UiPath and the Web Services that power them. It’s time to cut through the noise and sort through what is really happening in this space.
For everyone that just attended UiPath Forward, you probably noticed all the buzz around AI-powered capture. It was difficult to turn a corner without running into a vendor extolling the potential of their hot new release of data intelligence for documents. And, if you’re like me, you probably couldn’t help but recall all the recent coverage of over-hyped and under-performing machine learning-based applications in the RPA space.
The Everest Group coined this burgeoning market category of capture vendors as Intelligent Document Processing, and analysts forecasted this market will grow by 80-90% over the next two years. Given this purported future, it’s no wonder that every RPA company and document-minded tech company is dipping its toes into the capture ocean. But there’s some risk to these newly released products, many of which seem to be an alpha version of the application rather than a production-ready product.
As we’ve seen from the announcements at UiPath Forward and other major RPA players, one aspect of process automation is clear: document intelligence is critical to the success of any RPA implementation. In fact, it’s estimated that over half of all business processes involve documents at some portion of their workflow. Given that, along with the Everest Group’s prediction of this market’s growth, it bears repeating that it’s not surprising so many RPA vendors and startups are trying to wrap their hands around content capture. So, with the aim of adding document intelligence to robotic workflows, most RPA systems now offer capture tools out of the box. Earlier this year, Gartner claimed that capture “is tangential to the core of RPA.” And out of nowhere OCR – or the conversion of image-only files to text-searchable documents – became shiny and new again. Let’s face it, OCR has been a lackluster, functional-but-boring tool since the 1980s.
But a capture tool that simply renders documents text searchable or looks for fields of information based on zonal regions of a page is going to fall short for most enterprise capture needs. If you want your bot to become truly document-aware, you should look to a company that specializes in intelligent capture and is agnostic to the RPA or BPM tool running behind the scenes.
As one of the top RPA analysts at the Everest Group, Sarah Burnett, says, “Intelligent Document Processing solutions offer a compelling value proposition for enterprises that face challenges in increasing process efficiency and accuracy.” While there’s a tremendous opportunity, it’s important to look for solutions and vendors that deliver results, not just an overhyped promise of Minority Report-level data extraction.
At Ephesoft, we believe in delivering both innovation and results. Ephesoft Transact, our flagship product, was built to support automated document conversion, categorization and data extraction to accelerate information processing and overcome expensive human errors. Transact uses a combination of supervised machine learning and rules-based logic to achieve high accuracy of extracted metadata with minimal samples required. We’ve seen a decrease in document processing time by more than 80% for many of our customers and an overall project set up time as significantly shorter than many of our competitors. Moreover, as a company, our sole focus is on intelligent capture. Almost ten years of experience in this market gives us an edge over many of the newer “jumping on the bandwagon” vendors hitting the scene.
As it relates to UiPath, Ephesoft Transact Activities are available for download in the UiPath Go marketplace and can be found in the Integrations tab of the Activities window once they’ve been downloaded. It’s a simple task to drag and drop an activity into the design studio and configure that task to send documents to a specified Ephesoft Transact server. Depending on which Activity you choose for your process, you can easily start a batch of documents to be processed by a selected project, just return the extracted values, return split, categorized documents and their associated metadata, and more.
These Activities are essentially visual objects that act as wrappers around the Ephesoft Web Services that are available for developers. The Ephesoft Transact Web Services API provides a simple method for real-time integration and exposure of Ephesoft Transact processes to external applications. This allows developers to embed and employ smart capture capabilities and technologies in content management systems, BPM tools and – most relevant to this blog post – RPA systems. They allow for bidirectional communication between UiPath and the Ephesoft Transact server for a seamlessly integrated workflow. This means no more bad data or error-stalled bots in your organization’s document review and data processing workflow.
To watch a demonstration of Ephesoft Transact and UiPath working together to automate a tax form capture process, click the link: https://www.youtube.com/watch?v=DiLQUGwV27E&feature=youtu.be.
Paying Top Dollar: Data Scientists Need a Complete Set of Data
We’re seeing a rise in the demand for data scientists, but finding usable data is a challenge. How do we solve this to get a full picture of using multiple data points and sources in your tech stack?
A quick search for “Data Scientist” on LinkedIn yields 30,968 entries for companies seeking to fill recently vacated or newly created positions in the United States alone. According to Glassdoor, the national average salary for a Senior Data Scientist is $137,000. That’s nearly three times the national median income for a salaried employee (as is detailed in a Q4 2018 U.S. Bureau of Labor Statistics report). The benefits of using data science to create actionable efficiencies, cost savings and increased revenue are clear. And given the employment demand and salary expectations, it’s obvious that commercial organizations and government agencies alike are willing to invest in data scientists as employees and data-driven initiatives.
But a fleet of data scientists on the payroll will have a minimal effect on an organization if they are only working with a fraction of the data theoretically available. This dilemma stems from the nature of working exclusively with structured data as opposed to a combination of unstructured data along with structured data sets. Compared to a structured data set (which represents information that exists in relational database applications), unstructured data accounts for over 80% of all data and is growing twice as fast. Unstructured data includes machine-readable text (like the information in emails, Word documents, PDF files and communication, such as text and instant messaging) as well as images, video, satellite and surveillance data.
When running a predictive algorithm on consumer purchase trends for a manufacturing company, a data scientist is likely only working with the structured data generated by online credit card transactions, purchase metadata and information automatically logged and sent to the data warehouse. But what about all of the information tracked outside of that relational database? Perhaps there are product reviews logged on the company website or purchaser complaints sent to customer support via email. There could be a revised agreement with a materials supplier impacting product market pricing.
With an intelligent capture engine interpreting and extracting data from unstructured documents and organizational content, these vital data points could be included, considered and mapped for predictive analysis. Data scientists will have a more comprehensive dataset to analyze and be able to base results upon using all of the data available
A commonly-held industry statistic asserts that 60% of all business processes involve documents. Given that such a large portion of organizational workings relies on document-based processes, it would be an oversight to ignore critical text that could help organizations be more competitive or provide a better customer experience. information. Doesn’t it make sense to capture the valuable data locked away in documents to be incorporated into an organization's data warehouse? Why pay top dollar for a data scientist to turn rows of data into actionable insights if they’re only accessing a sliver of available information?
To truly realize the potential of any data-driven initiative or IT project, organizations should consider content capture an integral component of their data strategy. Leading tools should be able to ingest and interpret documents regardless of their location – internal or external documents. Based on content categorization, a capture tool should automatically identify and extract key metadata for purposes of data analysis downstream.
In theory, these are straightforward and seemingly simple guidelines. But in practice, content capture is challenging. For example, consider contracts as one type of unstructured document where valuable information is stored. No two contracts are alike. Even starting from the same template – a lease, a rental agreement or a mutual non-disclosure – if changes are made between terms, the contractual parties or addendums added by legal counsel can radically alter the nature of the document.
Collecting data from variable documents requires machine learning, natural language process and, at times, deep learning. Forward-thinking organizations will choose to partner with and buy from capture vendors that are using innovative technology to truly understand and organize unstructured content. Reaching the full potential for Big Data analysis will not only optimize the work for Data Scientists but it will yield benefits throughout the organization.
Are you prepared for more data?
How to Plan for ROI and the Future of RPA
The third RPA blog in a series of three.
Digging Into ROI After Go-Live
There are eight main categories to measure return on investment. Your organization may only choose to measure several of these, or all of them, depending on your overall goals of the project. Understanding your Key Performance Indicators (KPIs) will help you discover whether, for example, you need to measure cost savings in terms of headcount or perhaps what happened when you didn’t pay an invoice on time, resulting in fines. Or, do you need to survey your employees on if they prefer doing higher level, problem-solving and more creative work without doing mundane manual tasks. What is the cost of an audit and the preparation time versus a robot running a report and printing out all documentation within minutes or hours? Typically, as mentioned before, labor costs and time savings are the easiest to quantify.
Top drivers to measure ROI in RPA initiatives:
- Labor Efficiency
- Time Efficiency
- Accuracy
- Compliance
- Risk Avoidance
- Cost Avoidance
- Creativity of Work
- Employee Satisfaction
Create a Long-term Project Plan for the Future
The result of your first implementation of Robotic Process Automation was a success. Now what? It is time to take the data you have gathered on the benefits of RPA tools and apply them to a comprehensive plan for the future of your business.
Your team should be ready to endorse:
- The results of your prototype implementation, including lessons learned for all future transitions.
- A roll-out schedule for additional processes to benefit from RPA including dates and business units.
- Resources needed for the ramp-up of RPA transformation.
- Ongoing metrics, data, monitoring and tracking mechanisms for cost-savings realized enterprise-wide.
- Finally, don’t forget that a change management strategy is necessary for employees to embrace and welcome new technology. Incorporating innovation and technology changes into your culture takes time and understanding.
If you are interested in learning more about pairing intelligent content capture and Robotic Process Automation with the leading RPA organizations or how to leverage digital transformation processes, visit RPA Solutions.
How to Pinpoint Your First Use Case for RPA
The second RPA blog in a series of three.
What is RPA typically used for?
RPA allows businesses to automate a recurring, manual process so that building and maintaining the process is easy and cost-effective. Processes that are repetitive, predictive, rule-based, have low exception rates and high volumes and that are mature or stable are best suited for RPA consideration.
At a basic level, RPA can be used for manual processes such as “copy and paste” functionality, filling in data to populate a spreadsheet or running reports to post in a shared drive. Most likely, almost every department has tasks they do daily that require this basic functionality. Therefore, looking at deploying RPA pervasively throughout an organization is optimal. You need to know where and when to automate for immediate success. Where are the most labor-intensive processes in your organization?
Typical use cases for starting RPA projects include finance, accounts payable, customer or employee onboarding, insurance claims, processing loans and higher education transcripts and managing mailrooms, among others. Most organizations with a high-volume of high-value documents that are used in repetitive processes are prime candidates for using an intelligent capture solution that feeds into an RPA solution. A process must be completely electronic in order to implement an RPA solution. Therefore, if the process is not entirely electronic, other technology solutions may be required for true automation.
Perform a Cost-Benefit Analysis
Once you have gathered data from your sources, potential software partners and expert opinions from within your organization; create a comparison of what each solution can do and how it would integrate with existing technology. While costs are important, look for a software that is scalable as your organization grows. Comparing the labor and time savings of digital workers to human workers will give you the best metrics. Another consideration is that your RPA tool can run 24 hours per day versus human labor that works only 8 hours per day, so depending on your needs, you can already get 3 times more hours with robots.
Now that you have found the perfect enterprise process to prototype RPA technology and the software that best fits the needs of your organization, present the results to your sponsor. Anticipate questions about immediate and long-term cost savings over one year, three years and five years. Indicate what other costs might be associated with the implementation such as related computer hardware, if any.
Quantify the investment of the software versus the anticipated savings of expenses related to manpower, space and managing paper documents. Provide details on how documents will be accessed if processed through automation. Discuss how testing and changes will be communicated to all stakeholders currently working within the impacted business units. Change management will be an important consideration in recruiting allies for the successful digital transformation of your business.
Employ RPA for a Quick Win that Demonstrates Results
Once your sponsor has given the green light and your team has scheduled implementation with your software vendor and development team, move forward with the testing. You or your team will need to set aside time to be hands-on in this process. It may be helpful to be physically present at the location where the processes take place to supervise the transition and answer questions. Measure the results of the test and keep your sponsor updated. If or when processes or results do not proceed as anticipated, record the lessons learned for future implementations. Update existing workflows and documentation for approval and inclusion in company SOPs.
As you explore implementing your RPA, you’ll learn that there can be multiple automations on one robot (machine). Therefore, you are not limited to one process in your testing.
Stay tuned for our next blog on RPA: How to Plan for ROI and the Future of RPA.
First Steps for Starting Your RPA Project
The first RPA blog in a series of three.
Where do you begin with Robotic Process Automation?
Unless you occupy the C-Suite of your organization and are responsible for long-term strategic planning, you will need to find an executive sponsor or sponsors to assign your exploration of RPA. Look to the leaders of the Operations, Logistics, Innovation and Strategic Support teams you work with as primary stakeholders. You may need additional resources assigned as part of a project team whose members should represent expertise from different areas of the organization. If a project team is not possible, ask leaders to identify Subject Matter Experts (SME) from those areas to answer questions as you explore options.
Once your project team is established, begin by examining the current capabilities of your business. Is it critical to assess your current technological capabilities and the status of business processes in order to determine your readiness for RPA?
Examine Documented Business Processes
A key to the success of implementing RPA is to look for quick wins in current business processes. Consult your company’s Standard Operations Procedures (SOPs) for the most current approved business process documentation that describes activities across business units. Defining the scope of work is essential.
Here are some questions to consider in choosing where to start with the implementation of RPA:
- How many independent business processes exist?
- Which processes take the most time and cost the company the most in materials and employee resources?
- Does current documentation provide an accurate picture of how business processes truly happen?
- What software solutions are used by your company? How are they integrated?
- Which business processes highly repetitive and are best suited for automation? Example: manual data entry processing.
- Which processes could benefit most from intelligent document capture and RPA?
- How would operations be impacted by RPA implementation in the short term?
Your team should plan to create a concise analysis of processes, formulating a plan for grading current process readiness and quick wins that will make an immediate impact across business units. Ideally, the first process to move to RPA should be able to be done in a sprint and tested for a few weeks, not months. Your analysis can act as a starting point for scheduling onboarding of other processes and business units to RPA in the future.
Stay tuned for our next blog on RPA: How to Pinpoint Your First Use Case for RPA.
OCR vs. Intelligent Capture for RPA
Making smart data decisions for your RPA tool
In retrospect, company file sharing paved the way for document management applications. Then, these document management tools led to cloud-based information management systems. From there, remotely accessible content and cloud computing led to Big Data analytics. And, the demand for process automation has led Robotic Process Automation (RPA) to seek document capture tools that can interpret content to power their digital workflows. As technological innovations guide the way for data-based insights and automated task processing, companies are realizing the importance of existing textual data within their documents and file stores.
With the aim of providing document intelligence to robotic workflows, most RPA systems offer Optical Character Recognition (OCR) tools out of the box. A recently published Gartner report on the RPA market makes the assertion that OCR “is tangential to the core of RPA.” However, if the goal is to replace a manual process with a robot, traditional OCR barely scratches the surface of document intelligence. Smart content capture – the AI-powered evolution of OCR technology – is required for true process automation.
When working with companies on digital transformation or document process automation projects, I regularly answer the question, “Do I really need a separate capture product? Why not just use the OCR activity/tool/VBO available in my RPA application?” An example comes to mind when I asked myself a similar question mid-way through a recent home project. Standing in front of a paneled wall with a picture frame on the floor at my feet, a level in one hand and a nail in the other, I realized I left the hammer in the garage. “Why not use the handle of this screwdriver to hammer the nail into the paneling?” If the wood is soft, the nail is sharp and the wielder of the screwdriver has precise aim, it is possible. But change any of these circumstances, and you’ll quickly realize this makeshift tool replacement is out of its league. The same is true when a developer or business analyst tries to force-fit OCR into document-centric RPA workflow when a smart, machine learning-powered content capture tool is needed.
Simply put, there is a world of difference between an OCR engine and an intelligent capture tool. An OCR or ICR (Intelligent Character Recognition often used for detecting handwriting) engine recognizes characters on an image and outputs text in a machine-readable format. Some OCR products include tools for textual pattern or fixed-form extraction, but these methods of identifying key text values from a document are rarely scalable or effective across a variety of document types.
The same Gartner report summarizes, “despite the claims of some of the RPA vendors, there are only limited opportunities to use machine learning in the core of RPA itself.” When it comes to document-based processes, the standard image-to-text tools like Google, Microsoft, Amazon and ABBYY OCR, are insufficient to meet the demands of a workflow that includes variable documents and textual repetition.
There are key document workflow attributes that should trigger an analyst or RPA developer to employ a smart capture tool rather than a traditional OCR engine:
- If there is variability in the text or layout of the documents that are being processed will not be enough. For example, if you consider invoices or purchase orders, OCR alone or OCR use in conjunction with some form of template-based extraction will not be usable if the template varies.
- If files need to be separated into individual documents prior to inclusion in an automated process, such as stacks of documents that were scanned in batches, OCR alone will fall short of expectations.
- If there is repetition in the key values or index fields (multiple dates or addresses in a contract or mortgage loan) needed for document workflow, again, OCR alone will not accurately extract the necessary data.
To learn more about how Ephesoft Transact integrates with best in class RPA systems to provide document intelligence to robotic action, click here. For a demonstration or to connect with an Ephesoft sales representative, email sales@ephesoft.com.
