Innovation is pushing the boundaries of what businesses can accomplish regarding efficiency and operational excellence. From software powered by artificial intelligence to low-code enterprise platforms, there are so many paths toward digital transformation that it can be hard to know what’s best for your organization. However, one thing is sure: if you aren’t ahead of the intelligent automation curve, you could soon fall behind.

Indeed, the saturation of buzz around generative AI and the constant upcropping of startups hoping to capitalize on the hottest IT trends can instill skepticism in some IT leaders. After all, it’s inadvisable to reflexively adopt every new enterprise tool you see purely for fear of accruing a technical debt. However, those entirely resistant to automation needlessly limit their businesses’ potential in the long run.

IT leaders and innovation officers should look honestly at the state of their organization’s processes and employees. If any of the following situations apply, it should be taken as a hint that you are already overdue for intelligent automation.

Your Team is Tired of Manual Entry

Are your employees feeling fed up with repetition and monotony? A high volume of their tasks could likely be expedited through intelligent automation.

This isn’t to say that their role can be replaced entirely by technology but rather augmented in a way that increases both productivity and fulfillment. Employees often spend hours of their days on arduous work – typically involving documents – instead of stimulating, challenging, and rewarding projects.

Intelligent Document Processing — High Processing Rates

Intelligent document processing (IDP) leverages artificial intelligence with optical character recognition to quickly read and extract key data from documents, classify data, and ingest it into other applications such as enterprise resource planning (ERP) or robotic process automation (RPA) platforms with staggering accuracy. IDP solutions can yield high straight-through processing rates, meaning documents like invoices can be processed without any manual intervention. Instead of spending hours on manual data entry, employees can instead monitor accuracy and intervene only when necessary.

Your IDP Never Gets Tired

IDP solutions are also immune to fatigue, reducing the likelihood of errors. Not only that, but AI-driven document skills can be plugged in easily into existing workflows and trained to yield better results by processing volumes of documents, increasing the value of IDP over time.

While these platforms don’t completely replace humans, they drastically improve document-centric processes, allowing employees’ time to be spent on more fulfilling work while also boosting an organization’s revenue by accelerating time-to-value in achieving business goals. If you’re detecting declining motivation or growing frustration from employees, consider adding intelligent document processing to your automation checklist.

You Experience High Customer Onboarding Abandonment — Needs Intelligent Automation

Consumers aren’t immune to repetition fatigue either. As they grow accustomed to the streamlined customer experience offered by many financial institutions and other entities, their tolerance for lengthy and tedious onboarding processes diminishes.

Research shows that the top three reasons behind onboarding abandonment are:

• Too many steps
• Lengthy identity proofing
• Excessive manual entry

Customers want to feel like a valued priority, and demanding excessive manual entry and invasive identity proofing contradicts that expectation.

Businesses can use intelligent identity proofing to ensure that their first point of contact with customers is a positive one. Instead of typing on a miniature keyboard and toggling between device screens, applications, and emails, identity proofing should be able to be completed from a single screen in under two minutes.

Streamlining onboarding with intelligent identity proofing allows people to automatically upload all pertinent information using their smartphone camera to capture and send trailing documents to populate form fields. This emphasizes that the customer’s experience is a priority and fortifies a reputable brand reputation, thus preventing abandonment, increasing customer acquisition and advocacy, and driving revenue. If your business faces frequent onboarding dropouts, intelligent identity proofing is the solution for you.

Only Your IT Department Can Use Your Tools

Consumers’ demand for speedy service is not exclusive to onboarding.

Many businesses, such as tax preparation companies, rely on agile internal processes to deliver value to customers in a timely manner. If legacy systems do not permit easy customization to fit unique circumstances, the back end can quickly become encumbered with support tickets and bureaucracy that delay the customer’s outcome.

Organizations should adopt low/no-code platforms with accessible interfaces that can be used outside the IT department. Rather than depending on employees with backgrounds in tech or computer science, businesses can empower the “citizen developer,” enabling a new standard of agility to help your business deliver value at the speed of thought.

You Have Bottlenecks in Your Processes — Automation Solves the Issue

Organizations experience workflow bottlenecks but lack the visibility they need to address pain points and make the appropriate changes accurately. Moreover, 70% of automation attempts fail because of unclear or misguided goals.

Process intelligence can scrutinize processes at a granular level every step of the way.

Process intelligence is the combination of task and process mining; task mining examines individual actions, such as keystrokes, while process mining is more concerned with steps in an entire workflow. Monitoring processes with these techniques yields data that helps businesses more accurately understand how to optimize their operations, whether it be through hiring, automating, or reallocating resources.

Sometimes, organizations attempt to automate the wrong stage of a workflow, which can have unintended consequences like shifting a bottleneck to later in a process where it becomes more visible to the consumer. This uncertainty can hinder digital transformation success. If your organization is considering intelligent automation and wants to ward off failure, process intelligence is key to ensuring that your automation initiatives succeed.

You Struggle with Scalability

Volatile economic and market factors shift businesses’ needs over time, but adapting processes to a shift in the status quo should not be difficult.

Intelligent automation solutions offer the scalability that enterprises need to adjust their operations however needed proactively. Whether it’s a change in the quantity of documents being processed, the number of employees delegated to a task, or onsite or remote, intelligent automation will give organizations visibility and flexibility when faced with growing or diminishing demand for their services.

The economy is cyclical, markets are fluid, and businesses should never expect to operate at the same volume and tempo for very long. Nonetheless, decision-makers should always be prepared to make the appropriate changes necessary to protect the long-term health of their employees and their organization. Intelligent automation ensures they can make these changes as quickly as their business landscape evolves.

Everything is On-Premise

Not everything has to be in the cloud, but organizations that embrace cloud-native platforms can reap the rewards of newfound efficiency and flexibility. The use of the cloud is a significant aspect of scalability that can — to an extent — future-proof business from unforeseen events.

Cloud-native platforms empower easier management of systems and solutions, drive collaboration, and ultimately result in a superior customer experience.

The cloud increases the potential for desirable business and customer outcomes, and a well-designed security strategy can reduce the risk of information security discrepancies relative to on-premises tech stacks.

If your business has the infrastructure necessary to use cloud-native solutions, consider adopting intelligent automation platforms that are built around cloud technology.

Intelligent Automation in Your Business

Automation can be a contentious topic, especially with the rise in conversation around artificial intelligence and its implications. However, when adopted with the right business goals and implementation strategies in mind — it can transform organizations that benefit employees, customers, and other stakeholders.

If your organization struggles with efficiency, front-facing experience, scalability, or any other facet of operational excellence, it’s time to put your information to work and start automating intelligently.

Featured Image Credit: Monster; Pexels; Thank you!

The post 6 Signs Your Business Needs Intelligent Automation appeared first on ReadWrite.

While the implications of AI-driven solutions can be complicated, certain opportunities exist for their use that offers objective and essential benefits. The public sector is one such area that is ripe – and perhaps long overdue – for a digital transformation.

Waiting in line at the DMV is an infamously painful experience shared by anyone who has had the unfortunate fate of needing federally issued documents in the United States. Considering that these documents are necessary to qualify for and benefit from many government services, it is vexing that the infrastructure in place is still slow enough to be parodied as an animated sloth in a children’s movie.

But for many, the archaic and inaccessible process of the DMV is no laughing matter. People in lower socioeconomic circumstances experience obstacles that, coupled with the notorious inefficiency of DMV offices, could render these essential documents a near impossibility.

In-person requirements for accessing documents and services restrict access to those without reliable transportation. Long wait times take away hours from work or childcare. Even if you reach the front of the line, the long list of required items to bring sometimes means you don’t have everything you need and will have to come back and repeat the grueling odyssey.

Government agencies aren’t exactly known for being ahead of the curve when it comes to adopting new technology. Still, as REAL ID requirements in 2025 inch closer, it is imperative for this infrastructure to improve. By leveraging new advancements in proving and affirming identities and leveraging the mobile capture of documents, government entities can drastically improve their efficiency and accessibility.

Existing Online Services are Unsatisfactory

Many state governments already offer online services, but like their in-person counterparts, these platforms are notorious for being tedious and providing a poor user experience.

The Nevada DMV eliminated most walk-in services in August of 2022, now requiring appointments in most cases apart from Saturdays, maintaining normal walk-in availability. Officials cited staff shortages and high customer demand as the primary factors behind this decision, aiming to encourage the use of online services that are often overlooked in favor of the brick-and-mortar office.

A glance at Oregon’s online identity verification system might indicate why this is the case. The Oregon Employment Department previously required many people seeking jobless benefits to verify their identity through the ID.me system, which has been described as “cumbersome and invasive.”

The platform uses technology dating back to the 1990s, demonstrating not only that archaic practices are not exclusive to the DMV, but that many state governments actively rely on technology that is nearly a third of a century old.

While trudging through an arduous online process is still preferable to a DMV errand for many, those that aren’t tech-savvy enough to make sense of an unfriendly platform will likely opt for the benefits of face-to-face human assistance despite the inconvenience.

The ideal identity-proofing process should be limited to a single screen and take no longer than a few minutes. The previous practice of requiring users to toggle back and forth between multiple interfaces, such as using a printer or smartphone to copy documents and using a computer to email the attachments — reduces the odds of completing the process and increases the chances of user errors.

Citizens should be able to navigate the online portal with relative ease without feeling stuck or distracted. Likewise, staff should no longer be burdened with manually entering and verifying the information into processes. Making these online processes easy and pleasant to use with intelligent automation would represent a significant stride toward accessibility.

Fraud Concerns Stunt Online Services

The elephant in the room when addressing the need for online government services is the increased potential for fraud.

Concerns over fraudulently obtained learners permits through an online test in New York prompted state officials to call for the online program’s immediate suspension. The system showed individuals completing a 50-question test in four minutes. Photos taken throughout the test sometimes revealed that the test taker was not even present.

These obvious fraud cases further erode trust in online platforms and subdue the sense of urgency for their development. Still, federal and state governments can opt to bolster security measures instead of affecting legitimate users in the crossfire by removing online options.

New identity-proofing capabilities can incorporate technology like liveness detection, which verifies that the user is a living human instead of a digital or otherwise spoofed representation. Identity-proofing combats advanced fraud techniques like deepfakes, which use artificial intelligence to create representations of humans that can be eerily believable.

By using these defensive applications of intelligent identity affirmation and document verification, agencies can proactively defend against sophisticated attempts to exploit accessibility options for attaining new IDs or other government services.

Low-Code/No-Code Opens the Door

Government agencies like the DMV adding intelligent automation may sound too advanced for an industry known for being slow adopters of technology, but the democratization of AI has made this a possibility. Low-code/no-code platforms have made previously complex solutions accessible and actionable for those without extensive or formal backgrounds in AI or steep budgets to piecemeal solutions.

Despite their best efforts to create a welcoming end-user experience, software developers are prone to thinking like IT professionals rather than the lay user when designing platforms. This can result in tools with powerful capabilities but confusing interfaces, limited customizability, or other barriers to effective day-to-day use. This misalignment renders even the most advanced digital tools obsolete if the user can’t grasp how to use them.

Low-Code and No-Code Mitigates Discrepancies

Low-code/no-code mitigates these discrepancies through intuitive user experiences that require little to no coding proficiency. Applying LCNC solutions for uses like intelligent document processing (IDP) in the public sector would expedite the digital transformation of government agencies by modernizing outdated systems, streamlining consumer-facing processes (such as citizen onboarding), and maximizing staff resources.

Using LCNC in the context of digital onboarding and identity proofing implies not only an easy process for the citizen, but also for the state or federal employee on the back end that must verify submitted documents.

Replacing clunky, convoluted, and outdated processes with automated and customizable dashboards could drastically improve the speed of issuing identity cards. Low-code/no-code platforms not only encourage improved citizen experiences but make them profoundly achievable for even the most archaic government agencies.

A Word from the White House

Recent activity on Capitol Hill indicates that the federal government is turning its gaze toward tech and artificial intelligence. The recently passed White House Blueprint for AI Bill of Rights outlines how AI-driven technology must work for the benefit of the American public, considering privacy, algorithmic discrimination, safety and efficacy, human alternatives, and more.

While this indicates a cautious approach towards innovation that is characteristic of the public sector, this legislation provides the necessary framework for the responsible implementation of AI.

Furthermore, the White House AI task force has requested $2.6 billion from Congress to fund its effort to make federal AI resources more available to researchers, suggesting strong openness and intention to invest in AI from the federal government.

Innovation for Government Agencies to Consider

From huge strides in innovation to global pandemics, there have been many reasons in the past few years for government agencies to reevaluate their systems and processes. While intelligent automation is still expanding in capability and decentralization, it is already very usable — enough for the California DMV to successfully reduce their REAL ID transaction time from 28 minutes to only 10.

The same use case could be used to obtain benefits from Social Security Administration, Veteran Affairs, and education and healthcare institutions. Government agencies don’t need to wait anymore and should immediately develop literacy in AI-driven solutions, their responsible and ethical use, and the goals they want to accomplish with it.

The earlier the public sector embraces innovation and prioritizes welcoming user experiences, the more lives can be improved.

Featured Image Credit: Yolanda Suen; Unsplash; Thank you!

The post Intelligent Identity Proofing Can Help Government Agencies Go Digital appeared first on ReadWrite.

The majority of automation projects are successful, yet some still fail miserably. So, could personality have an impact? It turns out — it can.

Recent research by Sapio, commissioned by ABBYY, reveals that strategies for implementation and post-deployment actions if things go wrong can vary immensely depending on the personality of the CIO. The survey was conducted among 1,208 IT leaders across the US, UK, France, Germany, and Japan. It looks at where businesses have invested in automation projects, why they have adopted technologies, and how behavior has impacted the success of projects.

The study also looked at answers based on whether the person overseeing DX  described themselves as extroverted or introverted. Below are some common traits and differences between the two and how they impacted decision-making. I give my opinion on who does it best.

Reasons for Upgrading Your Automation Project

The decision to spend on new technology is never taken lightly, so the reason for instigating change must be solid, purposeful, and rewarding for the company. This was the first area where personality makes a difference.

When asked about the reasons behind digital transformation, introverts cited more human factors such as pressure from employees (32%), addressing staff burnout (44%), or supporting the neediest teams (47%).

Meanwhile, extroverts focused more on the type of tech and company goals, such as replacing old software (48%), achieving the most ROI (43%), and pressure from the market (47%).

A Listening Ear

The pandemic certainly pushed ahead transformation in a big way, with many organizations introducing employees to more intelligent automation.

Working from home required more cloud-based and user-friendly applications, and CIOs augmented staff with digital workers who could accomplish tedious tasks in a human-like manner. The pandemic resulted in many organizations accelerating digital technology adoption plans by three to seven years, with 45% of IT decision-makers implementing three to four automation projects over the last two years.

Listening and understanding employees’ needs, especially when there are several external factors causing fear, uncertainty, and doubt, are essential attributes to the success of automation projects. However, being pragmatic by understanding company goals and good ROI are also critical.

Winner: Introvert – Research shows that professionals with empathy perform 40% more in decision-making and coaching, and 90% of top-performing employees have emotional intelligence.

Great Expectations

Analyzing a digital transformation project’s success depends on expectations and anticipated ROI from the outset.

Are you looking for outcomes that are 2x the investment cost, just 1x or as much as 3x? Once again, this may depend on the personality of the automation leader. For example, only 19% of introverts expected 3x the ROI, compared to 25% of extroverts.

However, it seems the introvert leaders are more realistic, with 16% actually achieving 3x the ROI.

The survey also shows differences among the opposing personalities regarding the results delivered. For example, introducing AI improved business efficiency according to 53% of extroverts, while only 29% of introverts agreed. The same went for intelligent document processing (IDP), with almost half of extroverts boasting that it had helped grow revenue compared to only 27% of introverts. Also, more than double the number of extroverts attributed process mining for an increase in customers compared to introverts (33% v 13%). Perhaps this is due to changes in processes that make life easier for the customer. For example, by undertaking a deep analysis of the onboarding process, businesses can have more seamless applications with tools like Proof of Identity, speeding up the KYC practice and enabling companies to confirm that people are who they say they are.

Winner: Extrovert – Introverts may be slightly more realistic about numbers, but what about negative feedback on results? Overall, 95% of organizations participating in the survey said automation had improved performance, which is a very positive outcome. So my vote goes to the optimistic extrovert on this one.

Recipe for Success

It’s encouraging to see respondents to the survey felt digital transformation projects turned out well. A healthy 96% of respondents reported that their project had been ‘very or somewhat successful, with ‘easy to use technology is the main reason for success (44%). This may be down to the huge increase in the amount of low-code/no-code technologies now being implemented across the enterprise – which gives employees the chance to use ‘drag and drop’ or out-of-the-box tools to perform upgrades and instigate their changes without the need to involve IT in a long-drawn-out process.

The most popular tech introduced was document-centric process automation (54%), process automation (54%) machine learning (48%), while the least implemented was RPA (39%). The low introduction of RPA is likely because many companies have already deployed RPA and are now augmenting it with AI-enabling technologies.

In terms of which departments see the most success, it is IT (69%), Accounts/Finance (44%), and Operations (32%).

What happens when things go wrong?

What about the projects that didn’t work? If you have an introvert leading your team, you’ll find out sooner rather than later if things go wrong. The survey revealed that introverts are twice as likely to spot a failure in the early days of deployment – 50% v 25%. More worryingly, however, is what they do about it. All (100%) of introverts said they would replace it with new technology, compared to only 38% of extroverts.

This suggests stereotypical extroverts have more tenacity in not giving up on investment and will fight for a solution to fix the problem.

Also, when citing reasons for failure, introverts blamed it on too hasty a deployment (50%), double the number of extroverts. Both, however, agreed equally that automation goals being too vague was a significant reason for the disaster. Again, this highlights the importance of CIOs understanding their processes and how employees interact with systems before starting an automation project to set their workforce and business up for success. I was also interested to learn that 100% of introverts blamed remote working for contributing to failure, compared to only 13% of extroverts. This surprised me, mainly because most of the changes addressed WFH challenges.

Winner: Extrovert. We’re glad to see introverts spot problems early on, showing actual attention to detail and analytical skills. However, it’s not a welcome move to want to rip the whole thing out and start again with new technology – a waste of money. This time my vote goes to the extrovert.

A People-First Approach

There are many factors influencing the success or failure of digital transformation projects, but undoubtedly the study showed the personality of automation leaders plays a key role in the outcome. But, more importantly, with the number one reason for successful deployment being an easy-to-use system, business leaders must take a people-first approach to automation to be a true overall winner.

For employees, empower IT and business users with low-code/no-code tools to make data from documents more accessible to serve customers better. In addition, it makes processes more streamlined by understanding more clearly how employees complete tasks by interacting with systems.

Indeed, McKinsey reports that investing in digital skills for people has become a clear priority, indicating that employee skills need to match a company’s technology investments. So much so that attracting and retaining customers and employees took a backseat in priorities for IT decision-makers; according to the survey, an unusual result shows that employee retention could be at the heart of decisions above all else.

An easy-to-use system applies to the customer, too. Make interacting with your company more enjoyable. Onboarding for new services, for example, should be quick and easy when they need to provide proof of identity information. Enable customers to tap and click documents and biometrically match their faces in a one-step process. Also, make the chatbots they interact with online more innovative by giving those bots intelligent automation.

Digital transformation is an ongoing cycle involving embedding a culture of innovation to empower your teams and encourage and support change across all business departments.

Featured Image Credit: Provided by the Author; AdobeStock; Thank you!

The post Does Your Personality Determine Intelligent Automation Project Success? appeared first on ReadWrite.

This past year, many businesses completed mergers and acquisitions (M&A). In fact, between May and August, there were nearly 30 mega M&As – Microsoft acquired Nuance Communications, Apollo Funds acquired Verizon Media, Amazon acquired MGM, Celonis acquired Integromat, and many more.

Globally, M&A volumes have surpassed $4.3 trillion this year so far, for several reasons: larger businesses tend to acquire smaller competitors that aren’t performing well during challenging times, companies want to expand or augment their current product portfolio, or a company may want to enter new markets.

Process Mining: The Key to Successful M&A

No matter the reason, M&As are a complex project for everyone involved: lawyers, HR, accounting, IT services, employees, and many other stakeholders.

But the most difficult thing lies with managers; connecting two companies with different cultures and established business processes is not easy.

Over the past few years, ABBYY has acquired several companies around the world, most recently Timeline PI in the United States and Pericom Singapore in Southeast Asia. Here, we’ll dive into three groups: resources, processes, and people, and discuss how process mining can integrate businesses successfully that won’t result in profit losses, process bottlenecks, or employee attrition.

Resources

It’s not just legal entities that are acquired when it comes to M&As. Inherited buildings and equipment come into the possession of IT systems, and the parent company will typically audit everything to decide which resources should remain and which are better to offload.

Evaluation technologies

However, when evaluating different technologies and generations of systems, IT leaders need to ensure business continuity of end-to-end business processes while integrating processes. And the sooner they start doing so, the better.

The common way is to meet with stakeholders and manually map out the systems, applications, and known processes. But it’s a time-consuming and costly process that takes months. Another way is to automate the integration with robotic process automation (RPA) software robots. Software robots copy human actions in a computer interface and transfer data from one system to another.

However, robots work effectively only in well-structured processes, and don’t understand which systems have been optimized for integration. If the company needs the integration to be optimized faster, process mining and discovery tools are the key accelerants.

Process mining platforms duplicate information about the execution of processes (digital traces) from corporate systems and build a model of the company’s processes, calculate metrics, help find optimization methods, and help with analytics for starting digital integration and transformation. This ultimately helps streamline processes, identify bottlenecks, and improve operational efficiency.

Enterprise Management System

Another use for process mining is as an Enterprise Management System (EMS), which does not require large-scale work related to setting up or writing code. In this case, each of the linked systems loads its audit logs (or the data could come from databases, custom data extracts, etc.) into the analytics platform.

The platform, based on the actions recorded in them, will register the occurrence of a business event that corresponds to a scenario, a set of conditions, and causes.

This is what it looks like: Imagine that a chain of events of one end-to-end process goes through two non-integrated systems of different companies, and the onset of a certain business situation requires turning to another system. Process mining provides visibility and alerting across a distributed system, allowing you to quickly establish interaction between the IT landscapes of different companies and ensure business continuity.

How the Enterprise Management System Works

Here’s how it might work at a car dealership that has acquired a carrier company with its own fleet of car carriers. Maybe the dealership is now offering a new service to customers where they can transport cars to any part of the world, but there are several different companies that work together and follow several steps to make this happen. Below are examples of what steps might be taken:

• To start with, each company has its own separate IT system, and each of them transmits digital traces of transactions in different formats to a process mining platform. When a car dealer signs a preliminary contract with the client, they determine the date of sale and shipment of the car to the buyer.
• For the analytical platform, a sequence of events occurs in the accounting system, including determining a preliminary contract and completing an advance payment.
• Then, in the dealer’s system, it’s noted that the service of transporting the car to the destination is required and, in the carrier’s system, the process of booking a car carrier for the desired delivery date range begins.
• If payments are complete, a trigger occurs. In the carrier’s IT system, the process mining platform can see the warehouse’s attributed address where the car is located, along with a waybill for the driver.

Although none of the systems communicate with each other directly in this example, the task is still accomplished. All of this occurs at a stage when companies have yet to establish work in different delineations and businesses.

Processes

After integrating resources, it’s important to understand how the merged businesses’ processes are flowing. This is only possible when you have a complete, detailed understanding of the data and business workflows in the organizations.

This transparency can be achieved through intelligent analysis of business processes. Process mining allows you to see what a typical sequence of actions looks like in real-time when performing a particular task, such as agreeing to a contract with a supplier or responding to a customer request within a call center.

With these decisions, you can find deviations from the norm, who is doing them, and how the process can be streamlined and improved.

ERP system, a process common with M&As

For example, many companies have integrated all their branches to a single ERP system, a process common with M&As, while other companies operate in several dozen countries around the world and use multiple ERPs of different generations and manufacturers. This can make it difficult for equipment and assets to have consistent data reporting, which makes it difficult to prepare financial statements.

By applying process intelligence to collect and correlate data from disparate systems, companies can explore different options for the same process and identify any deviations.

People

There are several approaches to merging company cultures during an M&A. Autonomy is used most often if the new business is engaged in activities that are radically different from the parent company and when the acquired enterprise’s processes are fully preserved. But this option contradicts the notion of merging businesses. Often, customers don’t suspect that two companies are part of the same brand.

Fully integrate the platform

The “roller method” approach fully integrates the platforms, processes, and corporate culture of the parent company. This is a fairly common and successful method when the acquired company is much smaller than the parent, but it sometimes does not always lead to good results.

There are many examples of unsuccessful M&As — from Microsoft and Nokia to Google and Motorola to Daimler and Chrysler. Each case has different specifics, but one thing united them: the new owner sought to bring “his charter to someone else’s monastery” and very quickly introduced his corporate culture, KPIs, and processes into the business.

A New Business Model for Better Benefits

The third (and less common) method brings the best of both worlds: a new business is built from elements of both buyer and seller. It may seem more labor-consuming at first, but it can provide both companies with more benefits.

Additionally, with both methods, HR plays an important role. It’s important to maintain communication as employees become part of the new system, sharing what opportunities and tasks await them and what limitations exist.

Best Practices

From the perspective of managers during an M&A, it’s useful to identify best practices and determine which employees are the most productive. This is where task mining can be useful. Task mining maps out how staff accomplish steps within a process and allows companies to understand how people are using and interacting with systems to improve their productivity and optimize workflows.

Modern technologies like this allow you to identify the real picture of what’s happening, including the conditions when the task is performed, the cost of the process, the opportunities for improvement.

Conclusion

As companies continue to find opportunities to stay competitive in 2022, many analysts agree that M&A transactions will continue to increase. The winners will be those who acquire companies wisely based on understanding and carefully integrating resources, processes, and people.

Image Credit: Gabrielle Henderson; Unsplash; Thank you!

The post Process Mining: The Key to Successful M and A appeared first on ReadWrite.

Elon Musk was recently interviewed about SpaceX’s five-step design and manufacturing process when he echoed what every process excellence analyst has thought: “The most common error is to optimize a thing that should not exist.”

His words are highly relevant when it comes to digital transformation. So many innovation teams and centers of excellence are trying to optimize business processes when they should be looking at which processes shouldn’t even exist or eliminate parts of them. Or they make the same mistake that Musk admits he has done – automate first.

Automating Processes When You Don’t “Get it.”

Automating processes without fully understanding them has costly consequences, with new research showing 1-in-5 decision makers abandoned their automation project completely, and 1-in-3 either didn’t use the technology as planned or found it didn’t work as intended.

Unfortunately, there are waves of vendors who push that you should automate first, then optimize. Musk’s perspectives beg the question, “Can process mining add value to my automation projects?” With the massive growth of this sophisticated technology in recent years, many organizations seem to think so.

Strategies to Achieve Process Excellence

According to recent statistics, the process mining software market will grow by an incredible 42% to almost $7 billion by 2028. But, despite its promises, the technology comes with challenges, and organizations must be aware of the opportunities presented by the software to gain maximum value from it.

Here, we provide strategies for success with process mining and its next-generation approach: process intelligence.

Success Strategy #1: Create a Digital Twin to Understand Process Behavior

An underused capability of process intelligence in process behavior. Process behaviors can be defined as steps occurring or not occurring during any procedure or where steps are repeated. The sequencing of steps is also significant.

Does one step happen before or after another? Do steps that occur before another occur at any time or directly after the other? For example, it’s common to use various fields such as a department or customer when filtering process data.

While these are critical, there’s much more that can be known when you have a duplicate of your processes in the form of a digital twin, where are created from the events that define them.

When the raw data from process steps are used to build a model of what’s been done, you can define process behavior and queries against the behaviors to separate process instances into those that do and do not exhibit specific behaviors.

Having a digital twin also allows you to also consider the timing between steps.

Does a step take a certain amount of time, or does it take longer than a set threshold? For example, for a given category of product, you could set the threshold that it should never take more than one hour from when a stock check is initiated to when it is completed, then investigate the inefficient steps that made it take longer.

While this process may sound simple, all the data needed to evaluate behaviors is not available in any one record system.

And we still wouldn’t be able to answer behavior and time-related questions without the data being organized and understood as a series of steps unless you have the right tools to query this process model as to behaviors.

Tools and Behaviors You’ll Want

However, advanced process intelligence generates the process model from the data, provides the tools to specify the behaviors, and evaluates all process instances against these behaviors.

Success Strategy #2: Use Constant Visibility to Take Control

Process excellence analysts wish a control plane could monitor distributed operations and automatically act as needed. However, until there is such an external system, process intelligence can give you a data-driven bird’s eye view of your entire operations to gain a true understanding of how processes are working.

Taking a non-bias approach based on facts helps industry leaders make better, in-the-moment decisions.

With this visibility into your processes, you can understand exactly how your processes execute and answer questions like: How can automation improve customer experience? Which employees are the most efficient and consistent?

Where are your bottlenecks, and how do they affect compliance and service delivery? For example, you can optimize supply chain efficiency and improve the purchasing and sourcing process. And by discovering, analyzing, and monitoring how your procurement process really works.

“You can uncover delays that cost time and money, and discover the most efficient processes paths for positive business outcomes.”

Success Strategy #3: Add Analytic Dimensions

Another way to ensure process execution success is to use process behavior as an analytic dimension. It’s common to use various data fields, such as customer or state, as analytical dimensions. This enables us to look at process metrics broken down by one or more dimensions, such as a customer or set of customers of interest, or look at bottlenecks broken down by product type to see what product correlates to the longest delay.

This type of dimensional analysis is great for reporting and can help with root cause analysis. But there are limits to how useful this is for providing actionable insights. For example, knowing how process performance differs from one customer to another is great for reporting, but there is the question of how much it helps make changes to optimize a process.

The Process Behavior

When business analysts or process excellence experts can define any process behavior of interest to them and see how metric results vary with the presence or absence of this behavior, they then get actionable information that can help make optimizations decisions.

They can answer common questions such as, “How does customer satisfaction differ when we follow the old protocols or timing guidelines vs. instances when we followed the newer recommended policies?”

Conclusion

Today’s information systems generate a remarkable amount of data from both digital and physical sources. When properly ingested, merged, and analyzed, this wealth of data can be used to discover patterns and insights that illuminate paths to better customer experiences and new operational efficiencies.

You can better discover, understand, and manage business process execution more effectively by seeking process intelligence.

Image Credit: thisisengineering; Unsplash Thank you!

The post Three Strategies to Achieve Process Excellence appeared first on ReadWrite.

Software developers have been one of the most challenging jobs to fill in the U.S. for nearly ten years, so it’s no surprise that the developer shortage is set to escalate, with new figures showing a 35% shortfall by 2025.

With analysts predicting that as much as 90% of organizations will be going digital and deploying robotic process automation (RPA) by the end of 2022, this talent gap can significantly impact operational efforts, hiring processes, and growth efforts in every industry.

According to one study, it takes 50% longer to hire talent for tech roles than other positions, and, on average, it takes 66 days to hire the right fit.

IT leaders must figure out how to handle developer talent challenges to ensure their intelligent automation initiatives are not stalled or derailed.

What are software developers, and why is there a shortage?

Software developers are the masterminds behind computer programs and systems. In the realm of intelligent automation, they integrate and manage capture solutions. The solution then gets direct business-critical data from customer communications. Automation then automatically classifies, extracts, validates, and directs business solutions.

Other automation then is focused on identifying, creating, and improving operational processes.

Most of their work focuses on writing code and overseeing and monitoring systems and applications.

Business leadership and knowledge workers depend on the work software engineers do to have access to the large amounts of data within content and processes to be able to discover patterns and insights that can improve customer experiences and better business outcomes.

Technology constantly evolves, which usually leads to increased demand for software developers, but there currently isn’t enough talent.

The Shortage

The widely reported software developer shortage has a considerable impact on enterprises – ranging from overwhelming workloads and halting innovation to not keeping pace with competitors.

Additionally, building intelligent automation projects takes time, often several months to more than a year. While it varies from workflow and complexity of the business process, the time it takes to build and monitor after implementation can be resource-consuming.

One telecommunications company we recently engaged with had 80 bots running continuously, with 45 people managing them. It is quite possible to reduce that to one person.

Automating the automated

Learning to code is similar to learning new languages, but what if you could add code within the enterprise as fast and easy as adding a skill to Alexa to turn on the lights? What if your automation could create and improve other automation?

RPA bots could be the best area to start with this concept, but automating automation can be applicable to almost everything.

For example — automatically capturing, classifying, and distributing customer content during onboarding or account opening ensures error-free. Think verification of data, making it available for business processes.

We’ve heard of building code that can code, and the same concept could be applied to automation that can monitor, understand, and create another automation within a business process.

Self-Healing Automation

Then, imagine taking a step further and implementing self-healing automation. Once you create automation, you can continuously monitor it to see how it’s working with process intelligence.

If it’s not working well, you can create alerts that take action and trigger another automation to fix the broken automation. Ultimately, you would make automation that can repair itself.

The self-healing solution can create a cycle where developers are no longer delegated to mundane tasks and have more time to use their creativity to identify new innovation opportunities within the company.

The future of developers demands a new strategy

.Digital transformation has always focused on making processes easier for the business side. IT professionals have been used to manage new, complex technologies and keep them running.

No, and low code

To address the developer scarcity while meeting innovation demands, leaders need to turn to low-code and no-code (LCNC) platforms to make it easier for business users to become citizen developers and be empowered to quickly design, train, and deploy skills to intelligent automation platforms.

In fact, Gartner estimates that by 2024, 75% of large enterprises will have four or more low-code development tools for IT application development and citizen development initiatives.

A growing area within LCNC platforms is adding content intelligence skills to RPA.

The content intelligence skills are added to other automation platforms that enable it to understand, extract and classify content without needing an expert in machine learning.

For example, an accounts payable analyst could add a pre-trained invoice processing skill to enable the bot to read and understand fields within invoices. In addition, pre-trained skills for different document types are now becoming easily accessible from digital marketplaces and can be trained and deployed within days vs. months.

Knowledge workers can be more hands-on with LCNC platforms and get insights from documents to increase productivity and improve operational efficiency.

To illustrate this concept, picture an office worker who uses copy-and-paste from one document or system to another or clicks the same area on a screen dozens and maybe even hundreds of times a day. Copy and paste is a repetitive, mundane routine that is ripe for mistakes.

Imagine a message pops up on the screen from a bot that recommends automating that task? Then an alert would tell the worker when a bottleneck occurs. When automation is on board, the bot will recommend a different workflow to avoid future delays or deviations.

Automated automation and self-healing automation work in tandem to keep the worker’s tasks and overall business processes operating efficiently.

Automation is usually implemented when the business user initiates the automation — not a developer.

As the developer shortage continues and organizations seek to keep a competitive edge in an ever-growing digital world, they must embrace more accessible and more innovative ways of achieving intelligent automation.

Adapt quickly for the digital transformation

Leveraging low-code/no-code platforms with the necessary cognitive skills will help you achieve automating the automated and adapt quickly to meet the rapid, continuous changes in digital transformation.

Image Credit: Christina Wocintechchat; Unsplash; Thank you!

The post The Future of the Software Developer Role appeared first on ReadWrite.

The idea of a four-day workweek has once again been gaining momentum as the pandemic forced companies and employees to revise their working patterns and become more flexible.

Several countries in Europe are working to make it a reality, including Spain, the UK, Finland, and Russia. Microsoft’s Japan location has even tested shutting its offices down every Friday for a month and saw a 40% increase in productivity.

The Four-Day Work Week: A Near Future or a Utopia?

While there are certainly benefits to compressed hours, there are also a few disadvantages and challenges. Implementing a four-day workweek can be difficult as it requires the right support, technology, and workplace culture.

Is a four-day workweek a realistic prospect without compromising business? Let’s try to understand what prevents this initiative from being implemented, whether it is possible at all in the foreseeable future, and what role technology will play in this process.

With technological progress, people don’t work less

With increasing operational efficiency and automation in general, people’s roles are becoming more difficult, requiring more knowledge, non-standard thinking, and new skills.

Worldwide unemployment, with the exception of periods of acute crisis, remains roughly the same.

New Tech in work

With new technologies, business processes are accelerating and employee requirements are increasing. Take the example of a customer service representative in a bank branch.

Ten years ago, operators spent at least one-quarter of their working day reprinting data from passports, photocopying driving licenses and other documents needed to open an account, approving a loan, verifying a new corporate client based on their Federal Income Tax, and so on.

Today, almost all of these tech operations are automated at work.

Does this mean that employees are sitting and twiddling their thumbs on an office chair? No, of course not. Just through intelligent solutions, they manage to serve more people and simultaneously do something else: analyze data, respond to customer requests, and offer them new banking products. There’s still a lot to do Monday through Friday.

Just a couple of years ago, remote work was seen as a response to the public’s request for more free time.

Indeed, with the development of corporate mobility technologies, we are no longer tied to the office. We can work anywhere in the world with an Internet connection, constantly check mail, and respond to requests from partners and colleagues.

The pandemic has shattered the myth that we will work less when working remotely.

First of all, it turned out that not all companies were ready to switch to this format.

According to an ABBYY survey conducted at the end of 2020, 64% of companies had to adopt new technologies and processes, while 74% of employees said they faced challenges with switching to remote working.

Most of them found it difficult to set up a home office regarding technology and restructuring business methods. When identifying the cause of their biggest challenges, 40% of workers blamed a lack of information or solutions for completing tasks, while 32% blamed not having the right IT tools.

The global economy is holding on for two weekends

Businesses, as well as the model of consumption of goods and services, tend to adjust to the way of life of the people.

The U.S. officially adopted the five-day workweek in 1932, in a bid to counter the unemployment caused by the Great Depression. But Henry Ford, the legendary carmaker, made Saturday and Sunday days off for his staff as early as 1926 and he was also keen to establish a 40-hour working week.

An altruistic move in part also gave his workers the opportunity to spend their downtime buying consumer products and keeping cash circulating through the economy.

Entire industries have grown around free time.

It is safe to say that theatres, video games, the fashion industry, beauty and health, and restaurants and bars would not have received such development without two days off.

The share of services in the structure of the world economy is growing steadily. According to the latest data from The Global Economy, it is already approaching 60% of GDP. Experts predict that it will continue to increase.

Financial loss with a four, working day week

With that said, it could be difficult to move to four working days without significant financial losses and impact on productivity.

If you look at the current five-day program, the peak of employee efficiency tends to fall on Tuesday, Wednesday, and Thursday. Most Mondays are when you’re ‘getting into working mode,’ and on Friday, work activity goes down.

On the other side, a four-day week could give employees plenty of time to rest and recover and return to work feeling ready to take on new challenges.

Perhaps this could even relieve the dreaded ‘Sunday Scaries’ feeling. For example, from 2015 to 2017, Sweden conducted a trial study into a shorter workweek. “Nurses at a care home worked only six hours for five days a week. Results were largely positive with nurses logging fewer sick hours, reporting better health and mental wellbeing, and greater engagement as they arranged 85% more activities for patients in their care.”

The “nurse study”  shows that another day off could be feasible if approached correctly.

Just like when we have to adapt over a certain amount of time when changing to a new schedule, businesses should consider a gradual approach for employees. This could be accomplished by introducing programs and systems at the beginning of the day, sharing reminders of new and incomplete tasks, and encouraging open conversations to make the new schedule function well.

Work less but more efficiently

The battle for efficiency has been ongoing since the 20th century. Productivity growth is the only factor that can really help reduce the working week for the foreseeable future.

No company will entertain giving an extra day off unless they’re sure the job will still get done, whether it’s by an employee or a digital doppelganger. If we want to have more free time, we’ll be expected to, at least, do the same amount of work in less time.

Tech’s role — AI and business process at work

Technology has helped give away routine tasks to machines such as entering data from documents, comparing their versions, searching for information in corporate systems, and more.

The very optimization of business processes can be managed through automation. Now, systems with AI elements can automatically calculate employee performance standards.

In addition, these solutions allow you to identify repetitive tasks in the overall workflow that can be transferred to robots.

While robots don’t do all the work for employees, they can help them free up more time and avoid boring, monotonous work. In the future, AI is expected to make even more global advances. Analysts predict that by 2022 AI will create 133 million new jobs, and by 2030, it will increase the world GDP by $15 trillion.

Although AI gives a competitive advantage to businesses, there are no revolutionary changes yet. In general, the level of productivity in different countries is not the same. For example, the most productive countries globally are in Scandinavia – Luxemburg, Norway, and Switzerland, with the U.S. listed at seventh place, followed by Ireland and Australia.

Productivity at work is not always associated with technology

Productivity is not always associated with technology. For example, it’s not customary in Germany to talk about personal matters or non-working issues, except for during lunch breaks. On a large scale, this is a significant time-saver.

Motivation and non-conformity to business procedures also play a role. However, the processes themselves can often be blamed for this. We still spend a lot of time on unnecessary stages, slow collaboration, searching for information inside the company and beyond, and duplication of tasks.

IDC estimates that up to 20% of companies’ profits are a problem each year. In this regard, the concept of digital intelligence is gradually gaining popularity across larger, well-known companies. A company that wants to improve its digital intelligence and get a sharp jump in productivity needs to fully understand the deepest aspects of its processes.

What about mining?

According to research, in the next two years, the demand for process mining solutions will grow 8-fold to $1.4bn by 2023. This is because these technologies allow you to better understand what is happening in your company at all stages and levels of processes.

Digital analysis of everything you do at work in your company

It’s a digital analysis of everything that happens in the company. Accounts, credit agreements, tax forms, payrolls, and delivery reports are all fragments of the processes on which the business is built.

Companies that have the tools to analyze and use this data correctly gain an undeniable competitive advantage. They can map processes and see where technological innovation is most appropriate and where automation will, or will not, bring significant savings in time and money.

Conclusion

I’m confident that using machine learning and predictive analytics will one day help change company formats and allow employees to do a week’s worth of work in less than 40 hours. Until then, I guess I better keep that golf slot for Saturday.

Image Credit: evan wise; unsplash; thank you!

The post The Four-Day Work Week: A Near Future or a Utopia? appeared first on ReadWrite.

Digital transformation has become a buzzword that can be an overwhelming concept. Most companies know they need to do it, but they are not sure where to start. With so many different acronyms and terms in the world of intelligent automation, it can be challenging to know what it all means.

Understanding the Tools that Transform Your Business — Digital Transformation

According to Gartner, 91% of organizations are engaged in digital initiatives, and 87% of senior business leaders say digitalization is a priority.

Whether it is a digital front-end platform that allows insurance companies to deliver a better customer experience or major healthcare providers trying to reduce underpayments, initiatives like this are all under the digital transformation umbrella.

Highly automated

The future of work will be highly automated, and for executives responsible for driving digital transformation, success will depend on getting the right combination of tools. They must also deliver innovation that enables them to disrupt their industry without disrupting its day-to-day operations.

So, how do you navigate this ever-evolving intelligent automation journey?

Understanding intelligent automation

Imagine that every morning you grab your phone right before you leave for work. It’s so routine that it’s become automatic, and you almost do it without thinking. But one day, you walk out the door, and it feels like something is missing – you realize you’ve misplaced your phone, so you go back and find it.

You just imitated intelligent automation.

Intelligent Automation

Intelligent automation involves taking a machine taught to do simple, repetitive tasks (aka automation). They teach the machine to adapt or correct its performance based on changing variables at unbelievable speed and accuracy.

Some of the top benefits of intelligent automation include greater accuracy, cost reduction, and improved customer experience.

In finance

In finance and accounting, intelligent automation solutions can interface with existing ERP systems and data from invoices and purchase orders just like humans but complete them in minutes instead of days.

In healthcare

In healthcare, for example, finance leaders can use intelligent automation within accounts payables to consolidate insurance and patient payment data. The data comes from various sources and conducts a comprehensive risk analysis of patients and payers to reduce debt and total days outstanding.

Similar risk analysis is common in F&A departments but requires access to data stuck within unstructured documents. With intelligent automation, that data is accessible, enabling data-driven decision-making at scale and on-demand.

AI usage in automation

Intelligent automation uses several AI-enabled technologies to move beyond the basic digitization of processes and truly digitally transform the way work is completed. The objective is to automate more end-to-end processes and decisions while keeping humans in the loop.

Solutions used to enable intelligent automation are not mutually exclusive and are more often than not complementary.

But what do all of these tools mean and what are their real-world benefits?

Common Terms:

Robotic Process Automation (RPA)

RPA uses software robots, also referred to as digital workers, to automate manual processes that are repetitive, prone to error, and rules-based.

RPA has been a popular, tactical tool to automate mundane tasks to initiate business processes, such as data entry between software applications. Still, many users have been dissatisfied with how RPA vendors overpromise and under-deliver on being able to truly digitally transform operations.

According to a Deloitte survey, 58% of executives reported that they had started their intelligent automation journey, showing that organizations are using RPA but are moving beyond it to ramp up deployment of more intelligent automation.

Artificial Intelligence

AI has become an umbrella term that describes several types of technologies, such as machine learning (ML), natural language processing (NLP), and optical character recognition (OCR).

They perform tasks that previously required human intelligence, such as extracting meaning from images, text, or speech, detecting patterns and anomalies, and making recommendations, predictions, or decisions. Combined, they form the foundation for the most widely used application of AI within the enterprise – content intelligence.

Content intelligence helps software bots understand and create meaning from enterprise content. It delivers cognitive skills that the digital workforce can harness to turn unstructured content into structured, actionable information to make processes run more efficiently.

NLP

NLP is a way for computers to understand human languages. It does this by processing the language data and breaking it down by context and syntax to identify what words are being used and how they’re being used.

OCR

OCR is the process of mechanically or electronically taking scanned images of handwritten or printed text and converting them digitally into machine-encoded text.

OCR works by using character recognition to identify text and numbers to extract or analyze information from documents and forms. One example is using it within the banking industry to verify checks delivered over an app when a client submits a photo of it.

ML

ML is defined as a tool where a computer can learn from data by looking at similar patterns. It can help the automation process by being able to predict a decision a human would make from repeated patterns.

For example, in the manufacturing industry, with enough data, ML could be used to identify errors and irregularities within the manufacturing processes to ensure product quality.

Intelligent Document Processing (IDP)

IDP leverages OCR, machine learning, and natural language processing technologies to digitize and understand the most inconvenient forms. Then it and adds AI skills to RPA bots so they can learn, reason, and understand the content within various documents, and categorize these. Lastly, it extracts relevant data for further processing.

According to Everest Group, the IDP market grew 25-50% in 2020, with finance and accounting processes and banking industry-specific use cases having the most penetration. IDP solutions help enterprises achieve cost savings while improving their workforce productivity and employee and customer experience.

They are typically integrated with internal applications, systems, and other automation platforms.

Intelligent automation requires monitoring

With so many tools available for your organization to automate, initiate, and drive processes forward, it’s imperative to monitor their performance. This should include the ability to identify and rectify bottlenecks and have insights into how digitally transformed processes are impacting overall operations and the customer experience.

Process intelligence, business intelligence, and data science and analytics tools can be used alone or together to help managers and C-suite leaders know how their departments are working.

Process and task mining

The most common and expensive mistakes businesses make when implementing intelligent automation initiatives fail to properly understand how their processes are performing and then choose the wrong processes to automate.

Leveraging actual business process data is critical to the long-term success of any automation project. Powered by AI and ML technologies, process intelligence enables organizations to discover, assess, visualize, analyze, and monitor process flows.

Related to process mining, task mining can also monitor how individual employees interact with systems to determine if you need to add more training, re-evaluate any steps, or set a new best practice procedure.

Analytics

Augmenting intelligent automation with analytics solves most organizations’ problems with being data-rich and information and insight poor. Analytics software can leverage data from processes to find time savings, added productivity, and opportunities for innovation.

More advanced analytics automation platforms blend analytics, data science, and business process automation into a single end-to-end platform. This helps obtain efficiency gains, topline growth, bottom-line return, risk reduction, and upskilling for your workforce.

Digital Intelligence

Digital intelligence is being able to fully see, analyze, and understand the processes and content that keep your organization moving. It enables leaders to identify shortcomings, bottlenecks, and cost drivers to pinpoint the most impactful way to automate processes.

It also allows you to resolve issues causing stagnation and elevate your automation initiatives to the next level.

While the term “sweet spot” is often used in sports, it has its place in automation, too. In the world of automation, it can be the right combination of tools that deliver a good balance of cost and benefits and automation and intelligence.

Intelligent automation is necessary to transform your workplace to empower employees, enhance customer experiences, increase ROI, and gain a competitive edge. It must be part of your organization’s overall strategic digital transformation initiative.

Image Credit; fanki chamaki; unsplash; thank you!

The post Intelligent Automation: Understanding the Tools that Transform Your Business appeared first on ReadWrite.

Throughout the year, 2020, companies everywhere had to reimagine their businesses and the future of work. It made us realize that digital transformation was not a fad or incremental project to roll out by department; it’s imperative to be agile and remain competitive during disruptive times.

Digital transformation will continue to be a top priority for CIOs in 2021, according to new research by Constellation Research. Here is how to reimagine digital transformation in 2021.

The Constellation Research surveyed Fortune 500 CIOs and found that 77.3% prioritized digital transformation for their 2021 budgets over any other business activity. It will undoubtedly affect the entire business – from customers to employees to management.

There are several lessons learned that emerged from the year 2020 business.

Businesses should take into consideration with future digital transformation initiatives. You’re likely launching or scaling a robotic process automation (RPA). Maybe you are implementing or looking to fix or optimize some other intelligent automation transformation.

Understand that any automation speeds up the value of business and improves customer experiences. Here are the top five revelations that will help leaders reimagine how they digitally transform their organizations in 2021 and beyond.

1. RPA is not a strategic initiative

RPA has proven to be a useful tool for automating desktop manual tasks to increase speed and productivity, and there is an expected continued uptick for it in 2021. However, enterprises adopted it too quickly and added it to several projects that didn’t deliver the value they expected.

One of the most challenging aspects of RPA is that it isn’t smart; bots will repeat broken processes and cannot process unstructured content, which makes up 70% of enterprise content.

Transformation leaders are now realizing that in order to generate the most value from RPA, they need to take a more strategic approach and have a complete understanding of how their processes work and how employees interact with them overall.

Using process intelligence to back their decisions will validate the value it will deliver before starting any initiative. Additionally, RPA software bots need cognitive skills equipped that enable comprehension of any form of content and automate repetitive tasks to minimize human intervention.

2. The difference between desktop automation and true enterprise transformation

Automating tasks that workers used to perform from their desk was often the beginning of digital transformation initiatives. However, the disruptions enterprises encountered during COVID highlighted that there’s a big difference between automating manual data entry and digitally changing how entire processes are executed.

In 2021, more companies will boost automation and enhance human intelligence with AI to help with workplace disruption for location-based, physical, or human-touch workers who are working from home.

According to research firm Forrester, this includes applying AI for intelligent document extraction, customer service agent augmentation, return-to-work health tracking, or semiautonomous robots for social separation.

True enterprise transformation involves not just automating tasks and processes for the sake of automation, but using advanced technologies to understand how people, processes, and content interact together, and completely re-engineering how they work together.

3. Leaders need to better understand and optimize their workforce

There has been a myriad of productivity and collaboration tools introduced to help employees conduct their work faster and more efficiently. But is it really improving their workflow? Most employees say they deviate from set processes to successfully complete their tasks. One in four get so frustrated they want to quit their jobs.

It’s not just about tweaking processes in order to make them digital; it’s reimagining them to meet changing environments and expectations. One way of doing this is by understanding how employees complete their tasks within the programs and systems they use, and how it impacts other workflows and business outcomes.

Introducing workforce optimization tools, like task mining, monitors how tasks are done – not to be confused with monitoring employee actions as part of their performance. Its goal is to find optimal patterns of task completions so that organizations can shift away from highly repetitive tasks and empower employees to focus on higher value tasks.

It can also be effectively used as a personal productivity tool for employees to see how they’re working, how they can improve, and identify areas where additional automation can assist them. For example, if an employee doesn’t see the benefit from a program in place, they can show their employer how many hours they lose with the current program or how it’s negatively impacting their productivity.

4. Workers are capable of working with AI

Now that organizations have introduced RPA digital workers to their human workforce, management and workers alike realize the benefits of having a digital colleague. More companies will equip staff with their own software robot to augment their daily work for tasks with invoicing, onboarding, loan processing, and more.

Knowledge workers will be able to easily train, set up, and monitor their digital coworker with a new breed of low-code/no-code software solutions and infuse them with specific AI enabling skills such as reading, understanding, and reasoning documents specific to their jobs.

Robots that do these tiresome tasks – from replying to emails to sorting through documents for relevant data – will give employees more time for higher-value work like handling exceptions or nurturing customer relationships, which, in the age of social distancing, allows for more personal connection.

5. Data can do more than you think

Data used to be the last step of a business process – filed away after a transaction was complete. With customers’ growing expectation-of-now, leaders realize that rather than extracting then inputting data at the end of processes or on an as-needed basis, workers (human and digital) need access to relevant information in real time.

Content needs to be an active stream of critical information fueling processes and decisions in real time without intervention from the team that implemented it.

Making data work smarter for organizations will be big in 2021 and will make content intelligence and document processing solutions more popular than ever. From digitizing documents, structuring dynamic data like emails, images and PDFs and streamlining the intake by multiple systems.

By combining data with business analytics and process automation platforms, leaders will have an end-to-end view of their interconnected processes and a greater understanding of the health of their organization.

While digital transformation isn’t new, the current COVID-19 pandemic has driven companies to rethink their entire business models, with many launching DX initiatives in a short amount of time.

With businesses accelerating their transformations, others cannot afford to delay digitalization; new disruptors will continue to appear and more enterprises will push their CIOs to plan strategies that will establish the best technology in order to meet new needs and standards and customer experience demands.

Solutions like automation and AI will continue to gain relevance and remain even when the pandemic ends. While the ongoing digital revolution may bring serious challenges to many businesses, it also provides them with the opportunity to reimagine what a better way of doing business could look like and will only enable those prepared to embrace DX to succeed.

Image Credit: fauxels; pexels

The post Reimagine Digital Transformation in 2021 appeared first on ReadWrite.

There may have been a time when an organization’s automation strategy was defined primarily by siloed, ad hoc, and task-based workflows. Now, however, the most effective and impactful initiatives require business leaders to ask bigger, more challenging questions beyond simply what tasks can be automated and the ROI on cost reduction. Here is how to question everything you know about your business processes.

Successful digital transformation in today’s landscape necessitates leaders having a better picture of how things are working interconnectedly and how users are truly operating within the process boundaries to be enhanced and improved universally to improve customer outcomes.

True digital transformation does not simply digitize analog processes. It’s about integrating intelligence into business-critical processes across every facet of your business and engagement. As more companies realize they need to become digitally intelligent in a new era of digital-first consumers, accelerated automation adoption, and advancements in technology, organizations will benefit from adopting a more holistic approach to transforming their business.

Question the Status Quo

Questioning how things have always been done enables business leaders to find more effective ways to drive results.

Every business process within your organization contains an opportunity to improve outcomes, revitalize customer experiences, fix inefficiencies, or find new service opportunities for revenue generation. Here are three questions that business leaders need to ask to unlock opportunity and advance digital transformation initiatives that have the greatest impact.

1. Do you really know your process workflows?

By their very nature, highly manual processes, such as inputting invoice data or new customer information, are prone to human error and oversight. In highly regulated industries, such as financial services and insurance, this can be problematic and can contribute to increased risk and decreased compliance. Likewise, in healthcare, inefficient processes can lead to negative patient outcomes.

Understand processes.

Understanding your processes and pinpointing potential vulnerabilities is a good first step to take before deploying automation initiatives. Then, leveraging the right solutions to automate important processes intelligently.

Negotiations

These processes include all such negotiations as mortgage and credit card applications, account opening, and business loan applications helps organizations minimize inefficiencies and inaccuracies, therefore helping facilitate improved internal and regulatory compliance.

Machine Learning

With advances in machine learning and predictive analytics technology, you can understand exactly which processes are ripe for transformation, not just automated, to drive real change. Process Intelligence is a form of process mining and discovery that provides granular insight into an organization’s ecosystem of processes and behaviors, enabling you to pinpoint opportunities for operational improvement.

Understanding how your processes are truly performing — down to knowing each worker’s performance – is indispensable to successfully deploy automation initiatives that deliver business results and accelerate tangible improvements.

2. Are you accessing business-critical information?

You’d be surprised if you look close enough to how much paper (and fax) still exists in some processes. Those that are heavily paper-based can slow mission-critical workflows and negatively impact customer experience.

Likewise, valuable information is locked away in siloed systems. Various digital formats such as email correspondence, PDF, fax, and EDI can prevent you from having the right informatito make informed business decisions quicklyons.

Supercharge Growth

To supercharge growth and enhance profitability, organizations need to digitize and streamline content-heavy processes.

Digital

Digitizing, transforming, and automating customer forms, invoices, receipts, onboarding documents, application forms, claim submissions, and account documents can help lower administrative costs, reduce time to invoice and provide customers quicker service.

Data

When it comes to transformation projects, leveraging the right data and then sharing that data with key systems and stakeholders can be the difference between failure or success for meeting KPIs, service-level agreements, and other business outcomes.

3. Are you getting the most out of your automation investment?

Optimizing and automating the right processes can significantly reduce costs and strengthen competitive advantage.

However, by themselves, automation platforms can only do so much, and in fact, many projects stall or fail. That’s because most automation platforms now employ software robots, which have a hard time understanding unstructured data and will repeat poorly designed workflows.

Intelligence Leveraging

Leveraging intelligence capabilities driven by OCR, natural language processing, and machine learning technologies can turn hard to process unstructured data into actionable information.

The knowledge gained is then ready for automation platforms such as robotic process automation (RPA), business process management (BPM), customer relationship management (CRM), and electronic resource planning (ERP).

Process intelligence capabilities can identify process bottlenecks or variances and recommend the best workflows for optimal efficiency.

Raising Your Organization’s Digital Intelligence

When organizations re-think the way they have traditionally approached digital transformation projects, they unlock opportunities to strengthen and revitalize their business.

Asking the right questions and leveraging the right technology enables organizations to transform critical operations and turn the vast amount of data into a wealth of meaningful, actionable information.

Automation isn’t the end goal but rather a vehicle for achieving better business outcomes.

The post Question Everything You Know about Your Business Processes appeared first on ReadWrite.

It’s no secret that there’s substantial competition in the tech industry for great talent. Understanding what motivates employees and what type of work environments they prefer can go a long way in attracting the best tech talent.

As a result of the pandemic impacting the future of work, major tech companies are taking note and implementing policies that allow for greater flexibility and are now bolstering their Work from Home options. For example, Twitter recently announced a new policy allowing employees to work from home forever. Facebook and Google also extended their remote opportunities for employees through the end of the year and summer 2021, respectively.

When organizations listen to and understand their workforce’s preferences about what type of work environment drives motivation, productivity and work satisfaction, it enables them to create a work culture in which employees are engaged, which is especially vital during times of disruption and fundamental change.

New trends in WFH preferences

According to a Gallup poll, 62% of employed Americans say they have worked from home during the COVID-19 crisis. Of those, three in five would prefer to continue working remotely even once current health restrictions are lifted.

In a recent global survey from ABBYY evaluates the ways that quarantine has changed the way employees work. Respondents (53%) said that going forward, they would prefer an arrangement that enables flexibility between working from home and working in the office. Many indicated they prefer either splitting their time 50/50 or working mostly from home with some days in the office.

Employees cite greater productivity working from home

The ABBYY survey found that 43% of respondents noted they were more productive working from home than in an office. Other studies have also found increased employee productivity in remote environments. A Stanford study found gains of up to 22% when it came to employee performance and productivity while working from home.

Reducing employee attrition rates

In the Stanford research, employees who worked from home noted improved work satisfaction, and their attrition rate halved. Employee motivation can play a key role in overall work satisfaction levels. In the ABBYY study, 35% of respondents said they felt more motivated working from home than in an office. Furthermore, almost half (44%) of respondents said that working from home has decreased their overall stress levels. Understanding what motivates employees helps organizations to effectively develop work cultures, policies, and structures that enhance employee retention rates and can also help attract the best talent.

Enhanced work-life balance

Work-life balance has always been a prime concern for employees. Even more so now as the lines between professional life and personal life become blurred with many employees balancing homeschooling their children and managing new household responsibilities all while learning to work in, what is for many, a new type of environment.

One of the most significant advantages for employees in being able to work from home is increased time with family and loved ones. In the ABBYY survey, half of the respondents (50%) noted that spending more time with their families was one of the most significant advantages of being able to work from home. The majority of respondents (56%) also noted that working from home has impacted their work-life balance positively.

Improving the employee experience

The recent disruption in traditional office structures has led many organizations to re-evaluate many longstanding notions of standard work structures and consider new ways to enhance the employee experience and productivity.

Organizations that motivate their employees and create a desirable work environment empower employees to contribute at their highest level. In some organizations, business leaders have accomplished this by reducing or eliminating mundane, repetitive tasks from employee workflows by leveraging automation.

For example, many banks have recently accelerated the adoption of automation tools such as robotic process automation (RPA) and content intelligence to free their employees from paperwork-heavy and time-consuming tasks of data entry, sifting through paperwork, preparing loan applications and processing supporting documentation. This has freed a significant degree of employee time and employer resources.

Recent research from IDC reveals that in the next two years, 18% of administrative tasks will be performed by software robots. Leveraging automation tools to automate repetitive, mundane tasks can go a long way in enabling employees to focus on creative, engaging and meaningful responsibilities.

In addition to freeing employees from tedious administrative responsibilities, automation tools can also help employees make better decisions. The IDC research also found that technology evaluating information will grow by 28% in two years.

Automation can also help provide employees with new capabilities. Equipping employees with new skills via easy-to-use low-code automation solutions strengthen their role as citizen developers and empowers them to assume a greater role in enterprise digital transformation initiatives.

Thriving in the new era of work

The overnight shift to WFH highlighted the many inefficiencies with internal workflows and business processes, and that most staff do not follow processes very often. To identify which processes would be the best fit for automation opportunities, and how the staff interacts with them, it’s valuable to have visibility into all operations across the organization.

However, trying to do so manually or with standalone systems is often insufficient. Innovative technology has emerged, such as process intelligence tools, that leverage an organization’s real-time data to provide a bird’s eye view into its ecosystem of processes. This enables leaders to enhance process efficiencies and choose the best processes for automation that free employees from repetitive tasks and enhance the employee experience.

The future of work is changing rapidly. Organizations that are agile, able to adapt quickly, and create engaging work environments that motivate their employees and attract the best talent will be well-positioned to lead in the new era of work.

Try Out Productivity Tools We Are Using

The post Knowing WFH Preferences Key to Employee Recruitment and Retention appeared first on ReadWrite.

The Coronavirus pandemic has brought about disruptive technology solutions to slow the spread of the virus and minimize its impact. Contact tracing utilizing mobile technology is one promising but controversial solution that has been tested in some countries and proposed in the United States.

The Washington Post reports that millions of people around the globe have already been placed under some form of surveillance in an effort to monitor people’s movements and attempt to trace the spread of COVID-19.

Of particular note, at least 27 countries have already started using data from cell phones to track the movements of their citizens. While this approach has a great potential to benefit the public good, the implementation and adoption of such technology raise important questions about transparency, AI ethics, and data privacy.

Fighting the spread of COVID-19 with smart technology.

Contact tracing can be one of the most effective ways to contain an outbreak. However, COVID-19 is not a typical outbreak. The virus is often transmitted by individuals who display no symptoms of the infection and may not even realize that they are carrying the virus.

Standard contact tracing usually involves individuals who are symptomatic and are aware they are carrying the infection in question. Because of this, traditional contact tracing methods are challenging and problematic.

The Big Data Institute at Oxford University has proposed a solution for a mobile contact tracing application that is much more agile, efficient, and scalable than traditional manual contact tracing methods. The team developed a mathematical model designed to stop the epidemic if implemented on mobile devices by a substantial portion of the population. It’s poised to reduce manual contact tracing from 72 hours to four hours. By replacing weeks worth of manual work performing contact tracing, the mobile application can slow the spread much more quickly than traditional methods.

For the proposed mobile tracing method to be effective, quite a few hurdles must be overcome.

First, the majority of the population – including symptomatic and asymptomatic individuals – must voluntarily opt-in and adopt the application. The research team at Oxford estimates that about 60% of the population would have to utilize the application for mobile tracing to reach enough new virus cases to make an impact on the spread of the virus.

Another challenge lies in widespread and accessible COVID-19 testing. For the application to work, the majority of the population would need to have access to reliable testing in order for the application to properly and fully survey potential outbreaks.

There is much evidence suggesting that the application of rigorous wide-scale testing coupled with the application of mobile technology can blunt COVID-19 infection and mortality rates.

Taiwan was able to contain the COVID-19 outbreak better. Why?

A recent Stanford report demonstrates how Taiwan – a country just 130 km from the epicenter of the outbreak in China – was able to contain the outbreak without the draconian lockdown measures in place throughout many of the advanced economies.

How did Taiwan manage to limit and contain the spread of the virus? The report highlights five interconnected factors: pandemic readiness, national electronic health records database, wide-scale testing, big data analytics, and the use of mobile technology to track movements of individuals who tested positive for COVID-19.

Within 72 hours of the outbreak, a comprehensive case identification protocol was instituted based on travel histories. Individuals determined to be high risk were monitored through their mobile devices.

Health authorities were then able to trace the movements of high-risk subjects and mitigate the risk of further transmission through targeted isolation measures. Taiwan may serve as a template for how to mitigate future pandemics.

Balancing public interest and data privacy rights.

Innovative initiatives are underway by major tech companies, notably Google, Apple, and Facebook, to track and analyze how the virus is spreading and to gauge the effectiveness of social distancing measures.

Facebook’s Data for Good project is designed to track the movements of users to measure and anticipate potential outbreaks.

In the context of the COVID-19 outbreak, researchers, non-profits and public agencies can leverage the data – which is anonymized and aggregated – to evaluate and implement strategies to slow the spread. However, such initiatives raise concerns about transparency and data privacy rights.

There’s a strong case to be made that the implementation of mobile tracking applications represents an unwelcome intrusion to privacy rights.

• The Washington Post reports that three out of five Americans are either unwilling or unable to use the infection alert system that is being created by Apple and Google.
• In certain contexts, however, there are some legal grounds for this type of mobile tracing.
• The General Data Protection Regulation (GDPR) identifies six grounds for lawful processing of personally identifiable information (PII).

When the processing of PII is necessary for the public interest, then it can be done without obtaining the data subject’s consent.

The GDPR includes specific guidelines for the use of data in the context of epidemics. Recital 46 of GDPR  stipulates that the collection and processing of personally identifiable information without data subject consent are acceptable when it is necessary for humanitarian purposes. The information includes monitoring the spread of epidemics and addressing humanitarian emergencies, such as natural or man-made disasters.

Tips for the transparent and ethical use of technology.

It is the responsibility of technology leaders and policymakers to implement ethically sound, transparent, and fair applications related to the use of AI-driven profiling technologies and the transmission of highly sensitive health information.

For mobile tracing applications to be widely adopted and therefore effective in slowing the spread of COVID-19, the first and most important step is the grain the public’s trust.

Principles of fairness and transparency related to artificial intelligence are re-enforced by the EU Commission on The Ethics Guidelines for Trustworthy Artificial Intelligence. Every organization should be committed to these seven fundamental guiding principles for the application of AI technologies:

1. Human agency and oversight
2. Technical robustness and safety
3. Privacy and data governance
4. Transparency
5. Diversity, non-discrimination and fairness
6. Societal and environmental well-being
7. Accountability

These principles were further re-enforced by AI Now Institute in its 2018 report in which the organization asserted the importance of the public’s right to known which technology systems are impacting their everyday lives and how they are doing so. To that end, organizations must be transparent of the algorithmic systems used and their purpose, applications, and potential public impact.

Furthermore, while the use of technologies to help mitigate the impact of COVID-19 may be essential to protect public health and safety, they should meet the following criteria as proposed by the Electronic Frontier Foundation:

• The use of such technology must be medically necessary, as determined by appropriate public health experts.
• New processing of personal data should be in proportion to actual needs.
• The use of such technology must be non-discriminatory and without bias; people must not be scrutinized due to nationality or other demographics.
• Any new government powers that have arisen due to new measures must expire once the disease is contained.

Innovative technologies have the potential to accelerate and transform efforts to combat the spread of the novel coronavirus.

In order for these solutions to fulfill their intended objective and have the greatest positive impact, transparency and fairness are needed.

Before the public adopts new technologies at scale, they must trust these new and emerging innovations. The ethical use of AI should be evaluated not only on a legal basis but on a moral one as well.

It’s the only way for novel solutions to gain the people’s trust, inspire widespread adoption, and make the greatest impact – in times of crisis and in the post-COVID-19 world.

The post How to Ensure Data Privacy in the Time of Coronavirus appeared first on ReadWrite.

As the pandemic forces many staff to work remotely, it is shaping the future of work – with more AI-enabled digital tools being incorporated to equip employees with ways to automate and enhance business processes.

Surprisingly, an IDC survey only last year revealed that almost one-in-three office workers would not delegate any work to AI (27 percent). A third meanwhile did not feel AI could do a better job than them on any task (32 percent).

What about software robots?

Fast forward a year, and the change in working behavior means employees’ fear of robots taking their jobs is subsiding. Companies are now realizing the benefit of assistance from “digital workers,” aka robotic process automation (RPA) software robots.

These so-called bots augment tasks and help employees expedite customer-facing and revenue-generating processes, such as onboarding, accounts payable, claims, shipping and logistics, and customer inquiries.

The IDC survey did confirm that workers would be happy to hand over “boring” jobs like data entry, electronic filing, and reviewing long documents. “Happy to hand over ‘boring jobs'” is fortunate because it’s clear the advent of AI, machine learning, and advanced cognitive technologies means more digital workers will be joining the office.

The IDC white paper revealed that the number of digital workers entering the workforce is expected to leap by 50 percent by the end of next year.

So what is the impact of the pandemic? Will we be seeing even more digital workers in the enterprise as a result? It seems so. However, is now a time to review change within your business?

Do your processes already work well — and is it time to change?

It can often take a crisis to realize broken processes, failures in a system, or better ways to achieve things, learn and create.

Indeed, many organizations “think” they know how their processes work, yet it is far from reality. Rather than rely on a manager’s assumptions, opinion or bias, there are cloud solutions that provide an in-depth visualization and analysis of processes.

Tools to evaluate current productivity and processes.

These tools have the ability to evaluate your current processes in their “as-is” state so process automation teams can clearly set ROI expectations, assure agile service delivery and ensure that automation efforts do not produce any unintended consequences.

Healthcare

The healthcare industry is a prime example of the importance of process intelligence tools during this pandemic when the flow of information from different sources is critical to speedy and effective patient care.

Consider the challenges posed by a process’ scope such as orderly and efficient patient flow, timely processing of a lab test or the reading of a chest X-Ray. Accurately processing a treatment plan or the performance of many hundreds of other processes executed thousands of times daily is critical.

The challenge is aggravated since, in many of these examples, the information (data) related to the execution of each step may be stored across multiple different systems (EMR, LIS, RIS, PACS, ERP, etc.). Consequently, there is no central application that can provide a comprehensive view of the process histories.

With actionable insight into processes, healthcare leaders can make data-driven decisions and strategically optimize daily operations.

Remote workers.

The same goes for many business-critical processes in an organization, which has suddenly become more crucial in this time of social distancing.

The influx of remote workers has shined a spotlight on specific processes that threaten the continuity of business, especially as they relate to content-centric processes. Think of all the invoice processing, customer service requests, account openings or inquiries, and claims being filed.

Having access to these documents and systems and ensuring no interruption in service is critical to an organization’s bottom line. These types of forms and business processes would normally require manual input or monitoring. But the use of digital workers augments the human worker with digital intelligence to expedite processes.

Which business process in your organization is a candidate for automation?

All business processes are not created equal, some are critical to the survival and growth of your business, while some are not. Some consume costly resources — some do not.

There are a few qualifications that make a process a good candidate for automation.

• The process follows rules-based logic, rather than human judgment-based decisions
• The process is repetitive and may be prone to human error
• The process follows a clear set of instructions
• If there is input data, it is digitized or can be with methods such as OCR

It is important to note that the majority of processes that represent automation opportunities depend on unstructured data (e.g., invoices, orders, application forms, etc.), which is not a core capability of RPA products.

Unstructured data is even more significant when you consider that 90 percent of enterprise content is unstructured, and growing up to 65 percent per year, according to Cognilytica. The ability to understand this trove of unstructured data requires that document capture technology must be seamlessly integrated with RPA digital workers to transform unstructured data into structured content to be used in business processes.

Should Digital Transformation Projects Pause?

At emergency times like this, organizations realize they cannot afford to halt digital transformation projects, or they risk not being agile enough during the next crisis and delivering poor customer experiences.

Many executives are currently safeguarding their projects by leveraging low-code cloud solutions that will identify process bottlenecks, power automation, and infuse AI.

It’s the same scenario for sophisticated mobile capabilities, such as mobile web capture, SDKs, and mobile PDF productivity tools, which have become a top priority as offices, stores, and banks close, leaving much of the interaction via smartphones.

To maintain business continuity now is a time to reevaluate your company’s mobile strategy.

Providing customers with a frictionless mobile onboarding experience – from account openings, registering with a healthcare provider, applying for a credit card, or to gain an insurance quote – is no longer an added bonus.

You must provide a smooth, seamless, fully integrated customer experience starting from their very first interactions. That means being able to move easily from one channel to another, ensuring the process isn’t too lengthy, reducing typing requirements, and not having to download a native app to complete the process — otherwise, you risk abandonment.

What about mobile processes?

Also, evaluate how seamless your mobile processes integrate with back-end systems. Most consumers have a smartphone in their pocket, and by 2025 millennials will make up 75 percent of the workforce, which means onboarding processes will need to reflect the new mobile generation who are embracing the future of work.

Businesses understand they need to meet their customers where they are and engage with them in the most personalized way possible. In essence, this will determine their survival in a highly competitive digital transformation market landscape, and this unprecedented time when social distancing is raising digital expectations on all forms of technology.

Should you invest now?

According to a research firm, IDC technology workers with AI skills are being spared the current wave of layoffs and actually may see employment opportunities. IDC estimates that the number of AI jobs globally could increase by as much as 16 percent this year, reaching 969,000, driven by stronger demand for AI workers as companies contend with the impact of the pandemic and prepare for the future of work.

Artificial intelligence and machine learning are emerging across the globe.

Along with AI and ML, workers are finally ready to augment their work with digital workers. Within enterprises specifically, RPA, for example, is ultimately about using software to automate repetitive, high-volume process tasks that would have once required a human effort.

It shifts the worker to more intellectual work. Instead of people spending hours completing manual repetitive tasks, they can leverage RPA to focus on work that requires human ingenuity and creativity.

The good thing is that employees now working remotely are getting used to relying on digital tools and embracing their new assistants. As they become more familiar with these tools, they’ll be more open to incorporating solutions that augment their work.

No longer will there be a fear AI will replace them, and they will be open to how AI can enhance their roles with content and process intelligence, which will be a fundamental part of the future of work.

As more states and countries order shelter in place, ban social gatherings and push for zero-touch options for picking up essentials like medical and food supplies — we are having to adapt to getting work done through virtualization.

What this ultimately means is that work from home, and social distancing is a new paradigm for social and business interactions, where the point of both is to eliminate as many at-risk interactions as humanly possible.

Accordingly, we already are seeing how digital transformation can become the umbrella for making this work. Where safe distance, even isolation, are mandated to help flatten the curve of this virus, AI, digital workers, and virtualization technologies, including accelerated use of mobile and app-driven interactions, will become a necessity in doing business today.

The enterprise, as we know, it will never be the same again. Don’t miss the AI train — it’s time to look to the future.

The post How Will the Pandemic Impact the Future of Work? appeared first on ReadWrite.