Tag: automation

With COVID-19 causing risks to human health and disruption to our way of life in general, especially the way we work, companies have been forced to pursue alternate ways of making progress. Many of them are striving to use intelligent automation and AI to innovate their way forward while working safely from home.

This shift does not mean that we do not value human work, or the role people play in the enterprise. Think about the agricultural revolution. In the 18th century, people transitioned from hard laboring stationary farming to original inventions that altered the farming process. The new patterns of crop rotation and livestock utilization paved the way for better crop yields and the ability to support more animals. It was an opportunity to produce more, not a judgment of the reduced value of human work.

These agricultural changes impacted societies as there was a decline in both the intensity of the work and the number of farming laborers needed. Nevertheless, the positive effects of this disruption gave life to new technologies and opportunities as people migrated to the city to work in industrial jobs. As humans, it’s in our nature to innovate and create new solutions that become paramount to organizations and the people that work within them. We believe that as intelligent automation, Artificial Intelligence, and Machine Learning continue to evolve, we have an opportunity to harness this energy of innovation in a whole new way.

Our mission is to enable organizations to cross the human machine divide that has existed since the introduction of machines and enable them to co-exist seamlessly. We aim to reduce the friction between the two in a natural, human-friendly way. Eliminating the need for expensive translation mechanisms in the form of data entry, data synchronization and mundane activities allows organizations to become extremely efficient and resilient. Enabling innovation within the enterprise using natural language instructions, we bring out the innovator in the everyday business user. By letting the machines understand human language to achieve automation we drive speed in business transformation previously not possible. This is the core of our perspective on automation.

For too long, enterprises have placed contradictory expectations on their most talented thought leaders and employees. We have expected people to be innovative while also weighing them down with administrative tasks. Research shows “task switching” disrupts flow of thought and creativity. Ultimately, we launched cfo.jiffy.ai/ to reduce this phenomenon and to allow creativity to flourish and innovation to be unleashed in its most uninterrupted form. Our relentless commitment is to see a change in how organizations redesign their work, supporting them through the power that automation and AI offers to maximize strength, resiliency and scale.

Historically, automation was seen as a point solution for mundane actions. You gave it a specific function or set of functions, and it performed. Now, technology allows us to elevate and redefine the process and achieve progress through automation. This change is necessary in the ever-evolving landscape in which we live.

As we wrap up the first half of 2021, several parts of the world are still reeling under the impact of the successive waves of the pandemic. Maintaining business continuity and building resilience for predictable growth is an imperative for businesses across the world.  With industries gearing up for bullish economic weather, business leaders are leaving no stone unturned to remove all process bottlenecks that could pose hurdles in their resurgence strategies. Your Accounts Payable team plays a central role here, maintaining transactional integrity, ensuring sustainable cash flow, and powering your core business, often with limited and restricted resources.

Process modernization and optimization are key priorities for Accounts Payable teams that have already embarked on this transformational journey. According to the Impact of the COVID-19 Pandemic survey by the Association for Financial Professionals (AFP), 65% of businesses will move from paper payments to electronic formats, while 38% will rewire their internal procedures. Digitization will pave the way for smarter, more efficient processes, where employees need to spend far fewer person-hours to complete routine tasks, thus unlocking savings as well as ushering in an overall culture shift.

If your Accounts Payable team is already on this superfast transformation highway, here are five key takeaways for you:

1. Consolidate the digital forays of the previous year

The first step towards building a futuristic invoice processing strategy should be consolidating the fragmented digital transformation initiatives undertaken last year. In 2020, businesses had to adopt remote-friendly processes and support Accounts Payable teams as they started to work from home almost overnight. In some cases, this added to process complexity as simple in-person tasks (e.g., paper-based approvals) were no longer possible. Supplier/vendor network management also went digital, which has its own risks in the long term. At this point, it is vital to consolidate any point solutions you might have in place, take stock of vendor sentiment and any user experience bottlenecks they might be facing, and evaluate the projected total cost of ownership of your Accounts Payable systems beyond the pandemic.

2. Optimize cash flow to prepare for unexpected challenges

The pandemic left very little room for error in cash flow management, and this trend will continue in the second half of 2021 as economies recover and businesses return to their growth trajectory. A report by the International Labor Organization found that cash flow was the #1 problem faced by 4500+ companies in 45 countries worldwide. Improving Accounts Payable efficiency and modernizing your invoice processing strategy could help optimize cash flow. For instance, recommendations generated by cognitive technologies could suggest changes in the order of supplier payments that would maximize your cash on hand. These technologies can assign risk scores to every vendor and make sure that you gain from early payment discounts.

3. Upskill your AP team to perform and innovate

The year 2020 marked a tectonic shift in how we work, and this will have a lasting impact on workplace culture, how employees approach routine tasks, and their aspirations for the future. In the absence of a physical office and the physical presence of a professional community, inefficiencies in business processes became starker. Your employees are now less likely to be satisfied with repetitive, high-volume tasks in this ‘work from home’ season. There are two major action points for businesses through the year 2021. Eliminate mundane, iterative and non-fulfilling work wherever possible (this has typically been a chronic challenge for the Accounts Payable team). Employees who are freed up can be up-skilled to focus on more innovative work, such as in decision-making, the use of advanced technology systems, and discretionary problem-solving: essentially, tasks that machines cannot perform.

4. Adopt agile workflows to gain from dynamic economic weather

Through the rest of this year, businesses can look forward to a largely optimistic economic forecast, albeit with occasional regional curveballs on the way. In the last couple of quarters, we saw the International Monetary Fund revise its predictions several times, underscoring the need to stay agile and adaptive. In this context, rigid Accounts Payable workflows and monolithic processes will make it difficult to keep pace with fluctuating conditions. Instead, businesses must establish processes that are easy to configure – onboarding new suppliers with minimal risk or delays to support renewed demand, reconciling invoice exceptions and corrections seamlessly, and scaling up without adding complex approval red tape.

5. Leverage intelligent invoice processing automation to scale sustainably as you grow

The best-case scenario to look forward to this year is a rapid return to the original growth trajectories, aided by a resurging economy in 2021-2022. Businesses cannot afford to let speed-breakers such as inefficient processes, errors arising from human fatigue, and the risk of non-compliance, slow down this journey. The Accounts Payable function as a whole — and invoice processing, specifically — is part of the core of any organization. As the throughput of your Accounts Payable team increases, its invoice processing capability must focus on increasing straight through processing capacity. That way, it can scale in tandem to make profitability truly sustainable and mitigate the impacts of any further unprecedented disruptions. Strengthening this function using cutting-edge technology, helping your AP team and the supplier network, and the business as a whole should be a key agenda item in your strategy.

Your top strategic priority for the emerging future should be to remove the bottlenecks in the invoice processing function, and intelligent automation can play a key role here. Here are a few points to ponder:

• An intelligent automation solution can centralize the steps taken to digitize invoice processing in specific business units, regions, and teams amid the rushed switch to remote operations.
• It can equip your AP function with customizable supplier portals, AI/ML insights, and suggestions for decision-making based on your business rules, thus optimizing cash flow.
• It can ingest invoicing data from EDI file formats, XML/JSON files, mailbox attachments, and scanned images, making life simpler for your AP team working remotely; automated data extraction, validation, and exception handling further reduces repetitive manual work and probable errors.
• An end-to-end intelligent automation platform makes touchless processing a reality by supporting highly configurable workflows, where you can specify thresholds for manual approval, fraud signals, vendor prioritization and more, depending on changing market conditions.
• Invoice processing costs can be optimized as your business operations scale (thanks to a scalable solution architecture and volume-friendly pricing model), making the investment in digitalizing your Accounts Payable function truly sustainable for the long term.

Learn how cfo.jiffy.ai/’s intelligent Invoice Processing HyperApp has been enabling customers from various industries to prioritize these five capabilities. In fact, these are a part of our central value proposition to future-proof the Accounts Payable function. Drop an email to marketing@jiffy.ai today.

Even with all your enterprise-level digital adoption, accounts payable can still be one of the most paper-intensive departments in your organization. The team’s primary function, invoice processing, costs the company resources due to time-consuming and repetitive tasks, slow processing cycles and human-introduced errors. The longer you ignore the cost of manually processing invoices, the deeper the dents it tends to cause in your organization’s bottom line. Learn how the benefits of accounts payable automation can reverse that trend.

The True Cost of Your Invoice Processing Flow

The U.S. Institute of Finance & Management (IOFM) suggests that the cost of processing a single invoice can be anywhere between $1 and $21. Putting this into perspective, think of a mid-sized company that has approximately 1,000 invoices to process per month. They would lose significant money through the gaps caused by process inefficiency. AP automation benefits can help to solve those inefficiencies and reduce your invoice processing costs.

What Makes Invoice Processing Expensive?

Wondering how best to calculate the expense of processing invoices in your organization? The simplest way is to equate it with the costs of associated human effort. Typically, a member of your accounts payable team would take at least 30 minutes to process a single invoice. Considering the average salary of an accounts payable clerk in the U.S. is $43,917 (approximately $21 per hour), processing one invoice could cost $10.50.  For the mid-sized company mentioned earlier, this would add up to more than $10,000 every month.

And that’s not all! At this point, we’ve only discussed the base costs involved. But there’s more to it, such as:

• Cost of fixing manual errors: Invoice processing is highly susceptible to errors due to daily variances, volume-based pressure or sometimes even sheer human fatigue. To fix such errors on a paper invoice, you might have to spend a significant $53.50 to create a new document, communicate with different stakeholders and redact payments already made.
• Lost opportunity costs, such as discounts: Most vendors offer discounts for early payments, which can be as much as 2% to 5%. Manual invoice processing can create delays, causing the payment to miss the discount window.
• Strained vendor relationships: The inefficiencies related to manual invoice processing, such as delayed payments, payment redactions and multiple requests for the same information, can seriously damage your brand’s reputation in today’s vendor and supplier landscape. More severe mistakes could even harm long-term relationships, adding to your overall invoice processing costs.
• Physical costs, like storage and paper: Manual invoice processing goes together with paper-based processes, involving costs for physical file storage, stationery, etc. Unstructured hybrid systems can be even more expensive as the accounts payable team might have to switch between digital and paper formats, spawning duplication.
• Cost of efforts diverted from core functions: Finally, complex approval processes coupled with frequent exceptions call for measures by personnel outside the invoice processing team. Business leaders might have to intervene in invoice processing, and their valuable person-hours (which would otherwise be spent on higher-value functions) must be factored in.

What is Invoice Workflow Automation & STP?

Invoice automation and the benefits of accounts payable automation go beyond barebones e-invoicing, which only recreates paper processes in a digital format and replicates its inefficiencies. The intelligent automation of invoice processing leverages technology in a meaningful way to remove the bottlenecks in your accounts payable workflow, bringing human intervention down to near-zero. This enables straight-through processing, or STP, where automated technology manages the end-to-end invoice lifecycle, and the average handling time by humans is dramatically reduced.

6 AP Automation Benefits That Achieve STP and Help Reduce Invoice Processing Costs

According to McKinsey, intelligent automation can streamline 93% of tasks in payment processing. The stages of accounts payable automation include:

1. Extract Invoice Data Using Artificial Intelligence and Machine Learning

AI/ML-based technology such as object recognition and optical character recognition (OCR) can extract data from scanned images, PDF snapshots, etc. and automatically populate the fields in your accounts payable system. Intelligent invoice extraction is compatible with country-specific EDI formats, XML/JSON files, scanned images and even mailbox attachments.

2. Set up A Custom Supplier Portal

The worst long-term issue caused by inefficient invoice processing is probably the erosion of trust in vendor relationships. The smart UX of an automated solution allows you to set up a digital portal where vendors and suppliers can choose their relevant forms, make data entries and enjoy seamless interactions with your invoice processing team.

3. Configure Workflows to Handle Exceptions

Among the many benefits of accounts payable automation, automated exception handling lets your accounts payable staff tackle complex invoice scenarios without claiming the time of multiple business stakeholders. For example, they can set up workflows to handle exceptions such as potential signs of fraud, invalid vendor data, invalid file formats and specific PO detail mismatches. Configurable rules like these for invoice validation reduce an agent’s time to manually process an invoice by 80%.

4. Integrate with Your ERP

An AP automation workflow can connect with your existing systems like SAP, Oracle, Pegasus, Microsoft Dynamics, Salesforce, Infor, Sage or homegrown applications to enable bi-directional data flow. Your ERP can act as the reference for validating extracted invoice data (which otherwise needs to be performed by an AP staff member) and document the workflow information.

5. Gain from Analytics and Data Insights

Over and above AP automation benefits like lower invoice processing costs, automation becomes a true value generator here. First, it uses validation rules to assign a risk assessment score to every invoice. It also prioritizes tasks automatically based on load, productivity or your unique segmentation rules. Next, it uncovers vital data from your invoice processes to highlight productivity trends, KPIs and improvement areas, creating real-time visibility into invoices pending approval.

6. Consider Hosting on the Cloud

Cloud-based workflow automation software significantly lowers your upfront costs and ongoing maintenance overhead, while reducing your overall TCO. On-premises partly managed hosting is also an option in areas where there are critical regulatory requirements.

Save More as You Grow. Make Accounts Payable a Profit Center.

While traditional invoice processing methods become more expensive with scale (as volume and costs are directly related), intelligent automation and STP allow you to reduce costs as you grow. As the solution architecture is inherently scalable, your automation partner can offer volume-based efficiencies — for example, incrementally reduced pricing for volume tiers above 5,000 invoices per month.

cfo.jiffy.ai/ delivers invoice processing and accounts payable automation benefits for small businesses, large finance and accounting teams and every organization in between. We can help them achieve 80% STP and reduce the human efforts needed to process invoices from a new supplier to 0%. Sophisticated AI and ML-based workflows allow you to look beyond just replicating age-old manual processes in a digital wireframe. Leveraging our intelligent and scalable automation HyperApps, we are committed to helping future-oriented enterprises derive business value across critical functions like accounts payable.

Get the Benefits of Accounts Payable Automation with cfo.jiffy.ai/

If you want to iron out bottlenecks or inefficiencies in your business processes through sustainable, intelligent invoice processing automation, please email us at marketing@jiffy.ai. Our HyperApps experts will be happy to help you accelerate!

In an ideal world, invoice processing would look like this: 

But this is rarely the case. Straight-through-processing or STP of invoices remains out of reach for most businesses, despite advancements in automation over the last decade. Legacy processes, complex workflows, and a chronic lack of agility are commonplace for Account Processing (AP) teams, leading to seven accounts payable challenges: 

1. High manual dependency – Research reveals that 51% of companies use manual efforts for something as simple as data entry. You could be losing out on thousands of dollars in efficiency gains, not to mention added efforts in correcting the 3.6% error rate.

2. Convoluted routes for invoice approval – As 37% of companies still route their invoices manually, unexpected delays prevent timely payments to vendors. In drastic scenarios, the invoice could hit a brick wall and require a fresh billing cycle from scratch. 

3. Mounting liabilities – In the face of delayed approvals and manual errors, invoices could sit unactioned for months. This is a challenge for 27% of companies, leading to accumulated liabilities over time, mounting pressure at EOM/EOQ, and the risk of non-compliance. 

4. Difficulties in handling exceptions – The cause for an exception could range from incorrect price, quantity, or volume, to missing taxation details, PO number, or other information. They derail invoices from a straightforward path, requiring even more manual interventions. 

5. Failure to gain from timebound discounts – A business might negotiate more favorable terms and discounted rates if invoices are processed on time. Unfortunately, nearly 1 in 5 companies cannot realize these benefits due to delayed vendor payments. 

6. Lost invoices and effort duplication – As the saying goes, “too many cooks spoil the broth” – and this is certainly true for AP. In 33% of companies, manual dependencies, ineffective exception handling, approval complexities, and decentralization cause invoices to get lost. 

7. Decentralized AP – With invoices pouring in from multiple business units, and no consistent or cohesive workflow, AP teams’ work can be fragmented. This hinders centralized visibility and governance, which becomes a problem when it is time for the business to scale. 

Automation has long been touted as a silver bullet to these accounts payable challenges, helping companies achieve 100% STP. Research from Ardent Partners suggests that top-performing companies have 2.5 times higher STP rate than their laggard counterparts – clearly, there is a yawning gap to fill. Most companies cite the cost of ownership, a high degree of technical involvement, and a lack of cognitive capabilities as reasons to put off automation. As a result, they fall to the bottom of the pack, lagging far behind industry leaders. 

How HyperApps Can Solve All of Your AP Problems

Instead of a rigid, sweeping automation landscape, a HyperApp offers near-surgical precision when it comes to handling complex processes. A self-contained, ready-to-use, and integration-friendly invoice approval software can transform invoice processing in as little as four weeks. Its architecture is designed from the ground up to give business users the ability to configure a business workflow to their unique needs without any support required from IT.

This can lead to massive effort savings in the long-term, while also making businesses more agile for emerging invoicing needs and handling, or changes to business processes. 

For example, a company with HyperApp-led business process automation software will find it significantly easier to adapt to the touchless needs of the ongoing COVID-19 pandemic, automatically “learning” new template structures through ML.

Transform Your Invoice Processing With Our Accounts Payable Solution

To learn more about our accounts payable solution and how it answers the most pressing challenges in invoice processing today, download our e-book or request a demo of our HyperApp solution.

Have you ever said, “Let’s start small and then build it up based on how it goes,”? You sure have. So have most of us. In our world, this is typically how all automation begins.

During the initial days of robotic process automation (RPA), organizations were mostly skeptical. They saw potential but were unsure of real impact.

So, they tried it out for small non-critical functions — they wanted to minimize risks. Understandably. Say, the finance department would automate one task in the Accounts Payable first such as reading data from a file and transferring that to the ERP system. However, other aspects of the Accounts Payable process would continue to remain manual. Also, understandable.

This is what is called partial automation — quite literally, automating just a part of something much bigger.

But why would anyone do that?

In fact, there are plenty of reasons for handling automation this way.

For one, the earliest automation systems could only automate basic screen capture – in other words, anything that couldn’t be seen on a screen would break the process and need manual intervention.

Some of them are financial — end-to-end automation is more expensive and incurs higher opportunity costs to run business-as-usual in the interim because every sub-task would need investment in a bot. Partial automation, on the other hand, was cheaper. Organizations could pick a few bots for shorter processes and pay-as-they-go. This also helped them understand the effectiveness of automating and calculate ROI in the longer term.

Some industries worried about security. A bank would use RPA tools to move data from a front-end system to a legacy back-end system but wouldn’t let bots analyze their customer data. Even to this day, security remains an important reason companies choose partial automation. Why risk exposing critical data while their mandate – bolstered by regulatory requirements – is to protect it and keep it confidential?

Some others just weren’t ready for end-to-end RPA — automating a process end-to-end would necessitate standardization of formats, fields and rights, and that requires an investment of finances, as well as time and energy from their internal teams.

It also didn’t help that monitoring each automated process or bot was not easy. So, there was greater risk of broken automation if the scope was end-to end.

The initial RPA landscape had its limitations, lacking seamless integration with the human input when the time came for decision-making and without a human-in-the loop concept.

Most also feared that they might not have the people trained and equipped to intervene and improve the end-to-end RPA, making it a bigger risk. Partial automation is less demanding.

To be clear, in all these cases organizations certainly understood the value of RPA, invested in partial automation and derived value from it. Most of them are “somewhat happy” with the results their RPA systems are delivering.

Partial automation only provides partial success. Why?

Process measurement issues: Partial automation meant that a major part of the processes still had to be done manually, so there was no way to measure the ROI per process or per team/department. In other words, there was no way to make a strong case for automation because the results couldn’t be measured objectively.

Efficiency deficit: The improvement in overall process efficiency, while automating only a part of it, can often be so minimal it doesn’t seem worth the effort.

Savings deficit: As efficiency is only marginally improved, cost savings also end up being marginal.

Stagnation: Partial automation can be a dead investment without the bot’s ability to learn, adapt or grow with the needs of the organization. Likewise, it can be a dead investment if the organization doesn’t have the ability to see and manage how automation is being applied across the enterprise.

Resource blocking: Without the ability to improve intelligently, partial automation still needs people to fill its gaps. This means that people continue to work on mundane tasks, leading to low productivity, fatigue and dissatisfaction.

Right, so is Intelligent Automation a possible end-to-end solution?

Intelligent or Cognitive Automation in its simplest form, is an intelligent version of RPA — one that can learn from the data and apply it to present needs. Automation can become limiting when not supported by the learning capabilities of AI, which is where intelligent automation comes into the picture. It is flexible enough to understand and adapt to non-templatized data inputs. It can process structured, semi-structured and unstructured information with ease.

Take cfo.jiffy.ai/’s cognitive automation tool, for instance. It is able to read and extract non-templatized information. Even in cases where cfo.jiffy.ai/ doesn’t understand or cannot read certain parts of the document, it will extract all the other parts and reduce manual intervention to a bare minimum. This way, with cognitive RPA, you can automate the entire process, not just a part of it.

With its ability to learn, cognitive RPA is also scalable. As a business becomes more complex and processes more intricate, cognitive RPA can learn and grow along, making the ROI significant in the long term. For instance, intelligent automation systems that trigger alerts to floor supervisors in a manufacturing unit can learn to spot newer anomalies over time, making all aspects of productivity, quality and capacity predictable. Enterprises are addressing their requirement for end-to end automation using a combination of RPA tools (for repetitive tasks), BPM tools (for process management), OCR , IDP tools (for document extraction), Data platforms for data streaming and beyond.

Instead, a platform that makes all of these features available in a single stack can help save costs and time, and also translate to easily calculable returns over a period of time. This way, they can adopt cognitive RPA for all processes, interconnect them and enable them to work in tandem.

Cognitive RPA also comes with basic skills. Pre-built RPA systems, customized for industries and functions, are now available with the ability to hit the ground running immediately. Once installed, they are in auto-pilot mode needing very little help from people, even for setup, training or maintenance.

With prior knowledge, pre-built cognitive RPA solutions can automate end-to-end with a more meaningful understanding of the process landscape.

With cognitive RPA, the solution is no longer piecemeal. Unlike partial automation, cognitive automation impacts the entire value chain.

Today’s context

The global situation businesses face today is a reason for organizations to take seriously how end-to-end automation can help them to be more resilient in the face of crisis.

As an example, a large automaker based out of Europe has worked with cfo.jiffy.ai/ in automating their financial processes. This truly helped them recently when there was no business shutdown in their country, and they continued to send in their documentation to cfo.jiffy.ai/’s offices where physical offices were shut down. Thanks to automation, backend support continued seamlessly while production continued as planned.

It is completely understandable if you have a partially automated system now. It made sense in its day. But today, to see the real value of automation, end-to-end cognitive automation is the way to go. With a clear view of the entire system, end-to-end RPA will be able to bring together various processes into a smoother journey, be it for your customers, vendors or employees. It will also future-proof you as the system understands your existing processes and can expand to accommodate newer ones.

If you have adopted partial automation and aren’t fully realizing its potential, speak to one of our consultants to explore newer avenues. We understand where you are and we’re happy to help.

There are now increasingly mixed feelings about business process automation, and rightly so. While initially benefits lived up to the early hype (implementations achieve 30% to 200% ROI in the short term, reports McKinsey), mature projects are more disillusioned and typically run into a slew of challenges, particularly scaling. As automation comes of age, traditional approaches like robotic process automation (RPA) or point solutions software for Business Process Management run into roadblocks around scalability, adaptability, and ease of use. The number of companies scaling RPA is growing at snail’s pace, found Deloitte, with just 4% of companies successfully moving into implementations involving 50+ bots ¹. According to another report by IDG and Appian, automation was only “somewhat effective” (at best) for 65% of business users.²

As your company gears up for a speedy recovery post-COVID-19 – taking advantage of a bullish market – can you afford to be held back by stumbling automation projects?

What is RPA?

Robotic process automation (RPA) uses technology governed by business logic and structured inputs to perform high-volume repetitive tasks in enterprise productivity applications. Using RPA tools, you can configure software, or a “bot” (robot), to process a transaction, manipulate data, trigger responses and communicate with other digital systems. By combining APIs and user interface (UI) interactions, RPA bots can emulate human processes and complete autonomous execution of various business activities.

How to Move Beyond RPA Technology: Is Hyper Automation the Answer?

Over the last few years, RPA has emerged as almost an industry default for automation.

Nearly 1 in 3 companies use RPA technology despite its numerous shortfalls. Robotic process automation is mostly inflexible, with additional configurations needed for any change or extension to the system. You have to put in a lot of development effort, and even when using low-code platforms, there is significant effort duplication.

For example, if the RPA-automated invoice processing in your organization runs into an exception, it has to be manually configured into the script or might even require individual processing into your ERP.

As an enhancement to this, enterprises can choose hyper automation that uses intelligent, cognitive technologies like AI-based process mining, machine learning algorithms, optical character recognition, etc., to make automations more intuitive and efficient. Gartner named hyper automation among the top ten strategic technology trends for last year, anticipating its widespread potential.

But hyper automation is far from reaching maturity. Unless you are a massive organization with a dedicated RPA budget to throw at promising experiments, hyper automation remains out of reach, barring a few one-off projects.

A much more common approach to automating business processes is through SaaS-based point solutions software.

Point solutions introduces a significant degree of automation without most business leaders even realizing it – for instance, a simple scheduling feature on email, automated “nudges” for communication follow-ups, or a copywriting tool automatically checking documents against a style guide. In the wake of COVID-19, point solutions have exploded in popularity as employees/individual business units choose their favorite automation aids without always facing IT intervention.

But, for the organization, this means mounting shadow IT, the risk of fragmentation, and growing dependency on external providers to support dynamic business processes.

What Point Solutions Software Get Right (and What They Do Not)

There is an argument to be made for SaaS-based point solutions software. They are turnkey, easy to use, and – on the surface – involve minimal investments. It was only a matter of time before the “app-ification” of digital activity in the consumer world percolated into business processes, helped by a massive boom in B2B SaaS solutions.

However, the biggest USP of point solutions is their ready-to-use nature, which inherently makes them inflexible. As they target the widest possible user segment (without cognizance of the specific business use case), it is impossible to configure their automation capabilities as per your precise requirements. Or, if deeper configurations are available, you need an in-house expert with knowledge of that point solution.

As your business – and process map – evolves, you will find yourself reaching out to SaaS providers repeatedly to introduce the necessary features. In the long-term, this is an unsustainable model.

How HyperApps Help to Automate Enterprise Business Processes End-to-end

In addition to the three commonly discussed options (RPA, hyper automation, and point solutions), companies can also consider the HyperApp approach when automating business processes. cfo.jiffy.ai/’s HyperApps can combine the simplicity of low code with the power of intelligent automation and the cost convenience of SaaS to provide a comprehensive solution that truly empowers your business users.

Here’s a simple example from probably one of the most critical areas of your business, accounts payable processing in enterprise accounting: Let’s suppose as part of a new regulatory requirement, your accounts payable team must report all invoices in a specific currency and upload them into an e-invoicing portal. In the point solution scenario, your team will have to rely on the SaaS vendor to enable this change, who will charge an extra fee for that feature. However, with a HyperApp framework, your invoice processing group can configure that change themselves on the automation platform and make it available not just for the enterprise accounting function, but roll it out across the organization.

Unlike point solutions used for accounts payable automation, you can scale HyperApps to process any volume of invoices (as per our example – it is applicable to virtually any business process) and integrate with new/existing workflows.

Further, HyperApps bring in the flexibility you need in a dynamic business environment. Adapting your enterprise automation solutions to new business process requirements is made simple with a point-and-click interface, while integrations are available natively for use by business stakeholders, with little or no intervention from IT.

This could be a game-changer for companies as they enter a new era of digital transformation through end-to-end enterprise automation post-COVID-19.

Road to Recovery: HyperApps Can be the Pivot for Meaningful Digital Transformation

As companies gear up for what could be the world’s steepest recovery period to date, digitalization could either cripple growth or push it to new heights.

It is estimated that business process automation and an even greater reliance on digital channels will be vital in the emerging future. For example, the number of public sector organizations citing automation as their top 3 priority grew from 23% pre-COVID to 35% in the post-COVID period. HyperApps enable predictable wins in the short term, low effort overheads and greater democratization in the mid-term, and radical advantages in the long term – addressing the challenges of using point solutions for automating business processes.

There’s something to be said for doing the right thing in the right way. The benefits of process automation beyond robotic process automation or point solutions software are undeniable, especially in our new contactless and low-touch world. HyperApps help companies strike the right balance, enabling them to achieve immediate growth targets and paving the way for more opportunities in the future.

Accelerate your automation journey with cfo.jiffy.ai/'s low-code platform.

Achieve end-to-end business process automation. Accurately. Easily. Quickly.
Email us at marketing@jiffy.ai

References

¹https://www2.deloitte.com/content/dam/Deloitte/bg/Documents/technology-media-telecommunications/Deloitte-us-cons-global-rpa-survey.pdf

²https://assets.appian.com/uploads/2020/05/Business-Automation-Technologies-and-the-Customer-Experience_May-2020.pdf

In the early days of automation, robotic process automation or RPA brought the promise of radical transformation and improvement. Organizations could automate mundane, repetitive tasks, potentially giving back thousands of work hours to the business and reducing FTE efforts. Hyper automation will eventually transform traditional automation capabilities into impactful automated processes.

The original types of automations were not integrated or even necessarily connected to automate end-to-end tasks or processes – leading to fragmentation. A decentralized approach and focus on “a bot per user” have increased technical debt for enterprises, putting true digital transformation out of reach.

Over time, enterprises cobbled together disparate automation technologies to protect their original investments in RPA and were forced to assume the risks involved in integrating them.

What is Hyper Automation?

Gartner coined the term “hyper automation” to define this integration of technologies, encompassing RPA, machine learning, artificial intelligence, and these technologies’ growing sophistication. Despite RPA’s massive market share, it was fast becoming apparent that RPA alone could not keep pace with today’s digital transformation requirements, necessitating hyper automation – but this had its own share of issues.

Organizations choosing to automate via RPA as well as those venturing into hyper automation report a significant trade-off in terms of growing complexity, mounting technical debt, and a snowballing total cost of ownership (TCO) – which does not make sense in the long-term.

As we enter a new era in digital transformation, it is time to revisit our automation approaches and level up.

Traditional RPA is more of a white elephant for enterprise automation.

RPA vs Hyper Automation

During COVID-19, we saw several years’ worth of digital transformation (3-7 years, according to McKinsey) take place in a matter of months. As we enter the next phase marked by consolidation, maturity, and long-term sustainability, organizations should rethink one of the core tenets of digital transformation – automating business processes.

Robotic process automation (RPA) is entirely task-based, where you define precise rules to guide workflows in business process automation. Let’s say you are setting up an RPA software for invoice automation. At the invoice registration step, you can configure RPA to read from a file/folder, but every new source has to be manually configured. As you receive invoice submissions from multiple sources like cloud-drives, email, etc., the RPA script has to be updated and managed accordingly.

Over time, this leads to RPA becoming more of a white elephant than a genuine value generator, as you will be spending outsized efforts on updating, cleaning, and maintaining your automation scripts as your enterprise grows into diverse functions/areas.

A survey found that over 4 in 10 enterprises are having to spend more time and resources to maintain RPA than originally expected.

Another issue is deployment timelines. Enterprise leaders start with the best of intentions but adapting RPA to a typical enterprise’s scale, and process complexity takes time – often up to three years. More than two-thirds of deployments take anywhere between 1 and 3 years, delaying your time-to-value. And once RPA is in place, just 4% are able to scale, mainly due to the complexity of projects (57%).

This leaves you with mounting technical debt and sunk costs, further increasing your TCO.

The Hyper Automation Journey

Improving on this approach, Gartner introduced hyper automation as the next phase of maturity, which would take advantage of AI/ML to cut down some of the inefficiencies of traditional RPA.

The rise of hyper automation, the no. 1 strategic technology trend from 2020

Gartner calls hyper automation “the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans,” with the ultimate goal of enabling AI-driven decision making.

It was the no.1 technology trend from 2020, poised to simplify several of the complex scenarios that would stymie traditional RPA.

Here’s a simple AP automation example: If you are using automation to extract invoices, RPA would require you to pre-train the engine and create separate templates for each supplier. Hyper automation improves this through ML so that the data extraction isn’t template dependent. Similarly, when it comes to validating invoices, hyper intelligent automation can crosscheck via intelligent OCR, in contrast to RPA, which only reads specific ERP fields or structured information.

But even hyper automation does not match up to the promise of true digital transformation. Breaking down the above scenario, you will find frequent human involvement (often at preventable intervention points). For example, hyper automation-based invoice extraction still lacks continuous learning capabilities. ML models are mostly a “black box” that cannot be adapted to business user behavior. For invoice validation, you still have to write complex scripts – only now, it is compatible with both structured and unstructured information.

For this reason, hyper automation remains confined to the “promising trend” segment, with limited real-world usability. Research names only Amazon and Google as key players, owing to their rich AI/ML capabilities.

Does this mean enterprises who need immediate and effective outcomes from automation are left in the lurch unless they are willing to spend on a 5-year-long ROI generation roadmap?

This is where HyperApps come in.

Progressing to HyperApps – a pragmatic model with human-in-the-loop

HyperApps combine the functional principles of RPA, the intelligence/cognitive capabilities of hyper automation, and the self-service convenience of SaaS apps to enable automations that show value in months and last for decades. 

Continuing with the scenario of invoice automation, here is how a HyperApp would do it: 

• Invoice registration – Business users can integrate their preferred invoice source through a simple, point-and-click UI.
• Invoice extraction – Any exception not covered by existing formats is routed to the business user. The user’s behavior is taken as a learning point, and the ML will adapt its future actions accordingly. 
• Invoice validation – All validation rules are pre-configured; business users can toggle a rule on/off for a specific supplier when validating. 
• True cloud native – Pushing new configurations to existing automation implementations is easy, allowing for constant upgrades of the HyperApp’s business process automation capability. 

HyperApps introduce a few important changes to the RPA-to-hyperautomation maturity curve. 

First, HyperApps rely on self-service, empowering business users to set up automated workflows and configurable business rules. What the HyperApp eliminates is the dependency on technical resources to make business configuration enhancements and changes. HyperApp designers can also add new functionality to the app and business users can turn them on based on their needs.

Second, HyperApps are modular, with their components reusable as you grow, by applying the same components to multiple scenarios. This brings down the total cost of ownership and generates cost savings, while also shrinking time to value because of its turnkey nature.

Finally, the human-in-the-loop user interface can replace the bulk training ML approach in cases where it is not possible to create a pre-trained ML model. This business user-led approach allows enterprises to build or enhance ML capabilities with their own business data.

As you can see, HyperApps address the key impediments to traditional RPA and hyper automation. They ensure fast deployment and low maintenance, adapting to complex processes during business growth. They also keep a human in the loop to power continuous learning, reducing your efforts for manually configuring AI/ML models. Importantly, HyperApps are already in action at several enterprises, enabling long-term digital transformation without having to wait for technology or infrastructure maturity.

Learn from the frontlines and level up today with Hyper Automation

Demonstrating a remarkable improvement over RPA alone, one of the world’s largest automobile manufacturers was able to achieve 85% straight-through processing (STP) for invoicing processes in just a 12-week period. The company first tried RPA in their AP automation journey to replace manual execution. But it was too rigid and rules-based, unable to handle frequent changes in invoice templates as the manufacturer added new vendors, new invoice formats, new types of suppliers, etc., as part of its growth journey.

RPA solutions couldn’t keep pace with the company’s 5000-strong supplier network, processing 150,000 invoices per month.

An Invoice Processing HyperApp successfully addressed this by learning from 12 months’ worth of historical invoices and continually updating itself whenever it encountered an exception. Using a HyperApp, the manufacturer can process one invoice in three minutes vs. the pre-automation 24-hour turnaround. And unlike most implementations, it saw measurable ROI in six months.

At cfo.jiffy.ai/, we help organizations around the world with their digital transformation roadmaps by making it possible to level up their automation projects. This pragmatic progress from RPA to hyper automation and finally, to HyperApps has proven to bring about battle-tested outcomes.

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