New advancements in Intelligent Capture and RPA

With RPA set to supercharge productivity and efficiency across a range of businesses, interest in this field is developing almost as fast as the technology itself. Indeed, one study reported by Forrester predicted that RPA will represent a $2.9 billion industry by 2021.

Within such a dynamic environment it can be hard to keep on top of the latest developments. To make that simpler, we’ve summarized some of the most interesting trends in Intelligent Capture and RPA in recent months.

#1: Developing next-generation RPA

Early RPA was fairly limited in terms of its capabilities. Tasks like basic data entry, copying and pasting, and other processes that resembled simple macros were the mainstay of what was available.

Although perhaps not revolutionary, RPA of this type was nonetheless stunningly effective, allowing companies to achieve an output up to 15 times greater than what was possible with human workers alone, according to Deloitte.

RPA, however, is rapidly becoming an even more complex and useful technology. Although challenges remain in applying available machine learning and natural language processing to business needs, many companies are already adapting their processes and making ready for the “next step” towards a complete digital transformation. This may involve advanced robots capable of handling contracts, invoices and other complex documents, as well as end-to-end automation.

As cognitive processing develops, the role of RPA in business is only likely to grow.

#2: Intelligent Capture becoming prominent

Many businesses have their sights set on intelligent capture as the next technology that will streamline their business practice. It is undoubtedly a crucial part of task automation and one that will allow businesses to complete tasks in-house that previously would have required expensive outsourcing.

CapturePoint is just one example of a simple technology that automates a process that might otherwise require a significant amount of human time and attention.

Business process management is set to change dramatically in coming years. While previously this field was focused on the allocation of tasks among human resources, in the future it will likely look significantly different, with the deployment of intelligent machine resources taking prominence.

#3: Agility vs. cost-cutting

Intelligent data capture and RPA will, of course, reduce costs for many companies. Indeed, the National Association of Software and Services Companies (NASSCOM) predicted a reduction in costs of 35-65 percent for onshore operations in companies that successfully implement RPA.

And that’s not to mention the other benefits inherent in automated data capture.

It’s interesting to note that the focus of many businesses looking to employ these technologies is efficiency rather than simple cost-cutting. The higher process efficiency afforded by the use of RPA and intelligent capture will make businesses in a range of spheres more agile, with shorter development cycles and more agility once on the market.


With these developments in RPA and intelligent capture, it’s no wonder more businesses than ever before are looking to implement these new technologies.

Doing so, of course, is not without potential pitfalls, but with an experienced team of experts on board, almost any business stands to reap the rewards of well-implemented RPA processes, from increased efficiency to a lower error rate to the freeing up valuable human resources.

Preparing your business for machine learning and big data

Companies are buried in mountains of big data.

Big data keeps growing bigger every day. Between the IoT (Internet of Things), social media, mobile devices and cloud computing, the mountain grows higher and higher. Machine learning offers companies a way to transform the ever-growing mountains of data surrounding them into actionable insights.

But scaling that mountain is easier said than done.

A recent report from Gartner looks at the tricky situation facing businesses who want to conquer their data using machine learning. The report lays out the challenges of machine learning and the need to take proactive steps to prepare for it.

Let’s start at the beginning.

What is machine learning?

Part of the field of artificial intelligence, machine learning uses statistical techniques that give computer systems the ability to progressively improve on a specific task. Or, said another way, these computers can “learn.”

Although machine learning has technically been around since 1959, its importance has increased as businesses find better ways to understand big data.

What’s driving the adoption of machine learning now?

Big data is a tantalizing ideal, with 74 percent of companies saying they’re trying to be more “data-driven.” But the dream of big data has fallen far short of reality.

Many companies are simply overwhelmed by the structural and staffing challenges of managing big data.

The primary challenge is simple. How do you sift through huge amounts of data to get actionable insights? Currently, only 29 percent of companies able to connect data to action. Machine learning offers a key to unlock the insights buried in data.

It’s all about analyzing data to make accurate predictions.

What are the challenges of using machine learning with big data?

The Gartner report calls attention to a specific issue facing IT analysts. When analytic architectures and end-to-end data aren’t set up to work together, the disconnect creates an underlying problem.

In order to conquer that challenge, it’s ideal to have a data scientist on your team. At the very least, you need access to someone who deeply understands machine learning.

But learning the algorithms is difficult without a specific mathematical background. The way businesses integrate data also becomes more complex. In addition, infrastructure must be addressed.

How should SMBs prepare for machine learning and big data?

The challenges are different for small and midsize business than at the enterprise level, where there are more resources. According to the Gartner report, there are many ways to prepare for machine learning. But the leadership needs to come from the IT department

The people who understand the technical challenges of the issues simply must be involved.

Being proactive is the key to deriving the benefits of machine learning. Here are some of the specific recommended steps:

  • Examine the computer clusters and storage infrastructure needed to support machine learning
  • Select a machine learning platform that works with different machine learning frameworks when planning to work with off-the-shelf algorithms
  • Make sure the data organization is updated in an end-to-end analytics architecture in order to support machine learning algorithms
  • If you’re planning to build custom machine learning algorithms, put a development life cycle in place capable of supporting learning models
  • Take note of new frameworks being packaged with AI and machine learning solutions, which provide seamless solutions
  • Go to the cloud if you don’t have appropriate engineering infrastructure and staff to support machine learning, as it’s flexible enough to scale

The next big thing in big data

Machine learning is what’s next for dealing with big data. Companies should be building for the needs of machine learning by understanding the problems they’re trying to solve.

That means going to the IT support experts who uniquely understand machine learning issues. There’s simply no other way to be prepared for what’s next.

3 ways data capture can make your office more efficient

Data—SMBs have a whole load of it when creating marketing campaigns and customer profiles. In fact, businesses collected more data in 2017 than in the previous 5,000 years combined. But how much of this data is actionable?

Capturing the right data can improve efficiency in the office—the complete prism from high value conversions to clear communication. Here are three ways data collection turbocharges productivity at work.

1. Data capture increases sales.

Data collection provides SMBs with valuable customer intelligence—the type of information that boosts sales across the board. The latest breed of data capture softwares collect data from a wide range of sources—website forms, mobile devices, social media, third parties etc.—and generate accurate insights into consumers’ behavior as they progress through the sales funnel. All of this information is available in one place, so marketers can make quick decisions and solve problems.

48% of sales and marketing teams use data collection for customer value analytics, where information influences market segmentation and predictive analytics. This can have a significant impact on sales. Marketers can discover which customers have the most value, for example, or which products are the most popular.

2. Enhance customer engagement.

Data capture also lets SMBs engage with customers on a more meaningful level. When consumers provide these companies with data—names, addresses, email addresses, etc.—marketers can build customer profiles and send targeted communications via email, social media and SMS. These personalized messages bridge the gap between companies and their customers and foster consumer relationships. SMBs can also forecast future trends by analyzing customers’ behaviors and interests.

Customers who don’t receive good service can take their business elsewhere. Data capture, however, provides SMBs with actionable insights into what consumers really want.

“Today, more and more companies are realizing that true competitive advantage lies in creating an engaging customer experience—one that is personal, fast, easy and useful,” says digital transformation analyst Daniel Newman, writing for Forbes magazine.

3. Improve mobile workforce productivity.

Research suggests that 3.7 million employees now work from home at least half of the time. With data capture, SMBs can monitor their mobile workforce through devices such as laptops, smartphones and tablets. Managers can track time and attendance, manage absences, and assign work to telecommuters with the latest software, which instantly improves productivity in the office.

Many small and medium businesses lack the office space and resources to hire on-premise staff, resulting in an influx of mobile workers. The latest analytics provides these companies with useful information for decision-making and problem solving, such as staff members who have achieved the most sales or workers who have put in the most hours in a given time period.

Data capture also improves digital transformation, which allows managers to provide mobile workers with the right technology.

Data capture is a must-have for any SMB that wants to increase sales, enhance customer engagement and improve mobile workforce productivity. The amount of information that’s available to these companies is vast and far-reaching. As a result, companies can optimize efficiency and productivity in the office.

4 reasons RPA implementations fail and how to avoid them.

A surprising 30 to 50% of RPA projects initially fail. Business owners are often left wondering what went wrong. To help you avoid common pitfalls, we created a list of 4 reasons RPA efforts fail and how to avoid them.

“57 percent of organizations surveyed look to increase process quality through innovation.” ―Deloitte

#1: Not selecting the right processes to automate.

If you’re a first-time RPA implementer, you’re likely excited to improve your workflow. And that’s great. You just need to make sure that you’re automating processes that will have the greatest impact on productivity.

Focus on automating simple tasks that employees do on a daily basis or that take a long time to complete. Things like data entry, social media posts, and payroll are great places to start. Automating these tedious tasks frees up your team’s time. That way they can focus on tackling more critical projects.

“Implementation challenges can be serious, but proactive planning up front can reduce or eliminate them.” ―Deloitte

#2: Attempting deployment too fast.

It’s easy to get hyper-focused on using RPA to increase ROI. Sure, you want to increase your profitability. But you also have think about your current resources and capabilities. Can your IT department take on a project right now? Is your network equipped to handle an implementation? How will you measure an RPA project’s success?

Rushing into deployment is a risky move. One that will likely lead to frustration and wasted resources. Creating an implementation plan will help you achieve success. Get your business strategy team and IT department involved in its creation. And be sure to maintain an open line of communication throughout the entire project.

#3: Neglecting your RPA software after deployment.

Even after an RPA implementation, there’s still work to do. RPA software requires ongoing maintenance so that it continues to run smoothly.

Robots never deviate from their configured algorithms. But software interfaces, data formats, and company processes change. To make sure your RPA software continues to work in your environment, you need to make sure your business strategy team maintains it.

#4: Relying only on RPA.

While RPA is a helpful tool, it’s not the only tool. There are lots of productivity-enhancing solutions on the market. You should use RPA software as a part of your overall process optimization strategy. Not the entirety of it.

Take the time to analyze your business processes and determine where automation will make the most impact. You can also enlist the help of a provider skilled in RPA implementations. They’ll be able to provide guidance how to maximize your ROI using RPA software.

“It’s important to recognize and mitigate these [common issues] in order to facilitate the success of the organization’s RPA program.” —Ernst & Young

Deploying RPA in your business.

You need to consider every aspect of an RPA implementation before you undertake one. Evaluate the risks, rewards, and what resources you’ll need to maintain your RPA software. And remember, if at first you don’t succeed in your implementations, try again. There’s always a lesson to learn and apply to your future digital transformation efforts.

Related Blog: 3 areas of business that robotic process automation is optimizing.


3 areas of business that robotic process automation is optimizing.

By 2035, artificial intelligence is expected to boost average business profitability by 38% and lead to an economic increase of $14 trillion dollars.

One component of artificial intelligence taking the business world by storm is robotic process automation (RPA).

Robotic process automation is a type of software meant to mimic human actions in performing smaller tasks within larger processes. RPA systems learn actions by watching an end user execute a task within a software application’s graphical user interface.

The goal of RPA is to perform repetitive tasks quickly and accurately using a robot. This lets employees focus on more important aspects of the business like customer interaction and strategy.

“RPA takes the robot out of the human.” — McKinsey

In the business world, there are 3 areas where robotic process automation is making a dramatic impact.

#1: Business process management.

Business process management (BPM) is a systematic approach to streamlining processes, identifying areas that need improvement, and implementing best practices across all areas of an organization. It’s achieved through consultation with business strategists specializing in BPM.

One aspect of BPM is automation. That’s where RPA is changing the game.

RPA is the natural evolution of traditional automation. It’s easier to install onto existing software systems and extremely scalable. RPA software automates processes without changing, replacing, compromising, or adding maintenance expenses to existing applications. Thus, business consultants are increasingly using RPA in their optimization strategies.

Organizations can choose to incorporate RPA as a part of a complete business process management overhaul. Or they can simply automate individual tasks within their existing processes, achieving significant results with less time and investment.

“RPA projects save money, recoup the investment in just six to nine months, and don’t require major IT architecture changes or deep integration with underlying systems.” — Everest Group

#2: Data capture and transfer.

Instead of manually entering data into multiple databases, RPA is able to pull data from one application and push it into another according to the business needs. This is beneficial for form-driven and data-heavy processes like onboarding new accounts, fulfilling purchase orders or processing invoices.

Combined with machine learning capabilities, RPA learns from its mistakes and enters data more accurately over time, eventually eliminating the need for human supervision and error checking.

Related Blog: Harnessing Machine Learning’s Role in Data Capture

#3: Customer service.

Call centers use a variety of different systems and vendors to satisfy customer needs. When a customer calls in, a call center employee needs to pull up the appropriate account information, determine the reason for their call, switch between different systems and applications to retrieve the right details, and relay the best response back to the customer.

The longer this process takes, the more a customer’s frustration grows.

Using RPA, information can be captured, analyzed, cross-referenced, and shared across platforms. Thus, when a customer calls in, a tab with all of the right account details can automatically be opened on a representative’s desktop.

Robotic process automation also allows customer service representatives to avoid spending time entering the same data into different systems. Once a representative inputs data into one vendor system, the other systems automatically populate with that same information.

Each automation allows call center employees to successfully help more customers in less time with better results.

Harnessing the power of robotic process automation.

There are plenty of additional ways that RPA can have a dramatic impact on your business. A great place to start is looking at all of the processes within your company and identifying steps within them that can be automated. If you need help, be sure to reach out to an IT provider skilled in implementing artificial intelligence-based solutions.

Related Blog: Digital Transformation Trends to Watch in 2018

Digital Transformation Trends to Watch in 2018

As technology continues to advance, so does the rate of digital transformation among growing businesses.

Companies that leverage technology to automate their workflows gain a significant edge over their competitors. They are able to increase their productivity and drive down operational costs, maximizing their ROI.

In short, digital transformation makes rapid growth more attainable.

Many business owners are looking to the future, wondering what digital transformation trends will emerge. We’ve created a list of the ones that will likely continue to gain momentum in 2018.

Artificial Intelligence (AI)

AI is the technology behind advanced automation. It encompasses things like machine learning, cognitive computing, and more. It essentially allows computer systems to learn from data batches and past mistakes to adapt and fine-tune their operations automatically. With it, optimization opportunities are endless and innovation is inevitable.

“The aim of artificial intelligence is to have machines learn and deduct mass amounts of individual and collective data –and process through it quicker than a human brain would– to give the user a truly personalized response.” – Forbes

Arguably the most common example of AI in action is IBM’s Watson. This tool uses AI to help users to build customer service chatbots analyze content, translate natural language, and predict personality characteristics via text.

The Internet of Things (IoT)

Since its inception, the IoT has revolutionized the business world. It enables companies to automate, monitor, and improve their processes. And it simplifies the transfer and analysis of data.

For example, IoT automation enables manufacturing companies to reduce the number of employees they need to maintain asset production.

“The industrial IoT market is estimated to reach $123.89 billion by 2021.” – IndustryARC

Another major advantage of IoT is that it allows businesses to more easily provide customer support. For instance, Tesla recently began implementing “over the air” auto upgrades, allowing the luxury electric car owners to easily keep their firmware up-to-date.

Expect IoT to expand as different industries find innovative ways to take advantage of its capabilities.

Robotic Process Automation (RPA)

Data collection and analysis is the key to process optimization, and the latest approach is leveraging robotic process automation (RPA). In data analytics, RPA is a software configuration that quickly captures and interpret information.

Using this technology, business owners can easily identify bottlenecks and make fact-based decisions on how to improve processes and develop innovative solutions.

“47% of businesses are currently using big data tools to predict customer behavior.” – IDG

Uber currently uses RPA to more accurately calculate surge pricing and identify unsatisfactory drivers. Manufacturing firms are also leveraging it to receive supply chain analytics in real time and easily identify changes in product demand.

Adopting digital transformation trends.

Digital transformation is going to continue innovating the way business is done. As technology continues to advance, the number of ways to leverage AI, IoT, and RPA will increase. And the number of organizations harnessing the technology to increase productivity and decrease their human workforce will grow.

If you’re interested in learning more about how you can digitally transform your business, reach out. With so many applications available to improve results, our goal is to help you find the ones that work best for your organization.

Harnessing Machine Learning’s Role in Data Capture

Picture this: you’re faced with a seemingly endless stack of paper documents and told to enter them into your database. By hand. Four hours tick by and you’ve barely made a dent in the pile.

You’ve got a meeting in 30 minutes and a critical project to complete after that, all before you’re out for a week on vacation. But Janet from accounting needs these documents by the end of the day. When is this going to get done?

Let’s face it. Manual data entry is the stuff of nightmares. It’s the ultimate time-suck for you and your employees. And Heaven help you if you actually have to go back and find a singular piece of information amid the thousands of PDFs on your server. That’s enough to make a full-grown adult break down and cry. There’s got to be a better way.

Thankfully, there is.

Meet Data Capture

Essentially, data capture allows organizations to easily convert paper documents into digital, business-ready data. Digitally transformed documents are easily readable, editable, and searchable. Thus eliminating valuable man-hours spent sifting through and updating paper files.

What makes data capture possible? Machine learning, a branch of artificial intelligence (AI), is the key. This division of AI focuses on creating programming systems that are able to make decisions like humans, operating on self-learning algorithms and improving their processes without being repeatedly programmed. The goal of an application using machine learning is to reduce human involvement and help predict future outcomes based on past data trends.

It’s the same technology responsible for advancements such as self-driving cars and voice recognition technology. And, it’s here now to help you avoid endless hours of document processing.

Here’s a brief look at how.

Machine Learning and Document Transformation

Possibly the biggest benefit of data capture is saving time, effort and errors by turning paper documents into easily accessible, classifiable, and searchable online files. How?   

Supervised Learning

Information extraction via supervised learning essentially infers an outcome based on a set of pre-programmed examples called “training datasets.” In human and animal psychology, this idea is called “concept learning” and allows us to distinguish different objects, events, and ideas from one another.

Through the use of supervised learning, machines are able to analyze documents and identify the type they are – PDF, image, text, spreadsheet, etc. They are then able to extract specific data and automatically index documents, linking to patients or projects based via language processing technologies.

Active Learning

While this document identification and processing can be done entirely without human intervention, active learning can be employed when resources for employing machine learning are limited.

Active learning is when a computer is only able to use a limited number of training datasets (usually due to budgetary restrictions). As the machine learns over time, these processes will eventually be completed without human intervention.

After documents are scanned, properly programmed machines have the ability to detect fraudulent information. The machine will analyze a document and ask the user if it classified the file and/or extracted the data correctly. Then, based on user feedback, it will refine its document processing rules until the task can be done without user assistance.

Next Steps

A whopping 72% of SMB decision-makers state that technology solutions can significantly improve business outcomes and/or help them run their business better. Machine learning is most certainly one of these technologies.

The scalability, customizable architecture, and easy integration of machine learning makes adopting this technology to improve company processes a no-brainer (machine learning joke, anyone?).

We specialize in making technology advancements easily accessible, helping businesses everywhere process documents faster and share them more securely. If you are interested in learning how your organization can harness machine learning to improve your business outcomes, reach out.

3 Technology Trends in 2018: Our Predictions

Technology continues to advance and evolve at breakneck speed. 2017 saw the growth of tech like self-driving cars, facial recognition, gene therapy, and machine learning, among others. Most new things are trendy. Fashion, ideas, slang. At first, each innovation is the cool, hot thing. If it’s particularly interesting or meaningful, it sticks and becomes integrated into society.

Essentially, in any field, there will always be trends and IT is no different. The question is always, what will these technology trends be? As we gear up for 2018, we put together a list of our predictions for the New Year. Without further ado…

Artificial Intelligence

Artificial Intelligence (AI) deals with the simulation of human intelligence in computers. Behaviors and capabilities like visual perception, decision-making, language translation, and more all fall under this area of science.

We predict that developments in AI aren’t going to slow down anytime soon. In 2018, it’s likely that businesses in a variety of industries are going to increase productivity by automating their workflows with artificial intelligence technology. In fact, a recent Gartner survey showed that 59% of organizations are still gathering information to build their AI strategies, while the remainder have already made progress in adopting AI-driven solutions. More applications and equipment are likely to begin incorporating AI into their functionality, helping businesses augment the day-to-day tasks their employees already perform.


Also known as the tech behind Bitcoin, blockchain is essentially a continuously growing database of time-stamped records (known as blocks) that are linked together using cryptography. It allows various parties to exchange transactions securely, with no one single point of failure. This means, there’s not just one person in charge of the entire chain. It’s a self-managed, peer-to-peer ledger of records.

About 50% of business leaders predict blockchain will be mainstream by 2020. Currently, the financial sector is primarily using it with about 90% of major European and North American banks exploring blockchain solutions. The challenge will be diversifying its applications so that businesses in different industries (healthcare, government, content distribution, supply chain, etc.) will be able to take advantage of the technology.

3D Printing

In traditional manufacturing, objects are formed of different materials using fabrication tools. However, in 3D printing, things are created through a technique called additive manufacturing, when materials are layered on top of one another to form an object. A major benefit of 3D printing is that far more complex shapes can be created than in traditional manufacturing, allowing for greater customization.

Our prediction is that 3D printing will continue to rise in popularity this coming year. With the advent of machines priced (and sized) for the average customer, more and more people are starting to use them in their homes and small businesses.

And there you have it! 3 technology trends to keep an eye on in 2018. We look forward to seeing what new tech developments will emerge during the next year.

If you ever have IT-related questions or want to learn more about how your business can harness technology improve their processes and increase network security, please reach out. It’s our resolution to continue serving our customers and offering an educational resource for business leaders looking to improve the way they approach IT.

How to Create a Digital Transformation Strategy

It’s likely that, as a business owner, you’ve heard the term “digital transformation.” So, what exactly does it mean?

Digital transformation is the change associated with using new technologies to enhance and innovate the ways you do business. 72% of SMB decision-makers say that technology solutions help them significantly improve business outcomes and/or run the business better. Thus, more and more SMBs are incorporating technology into their everyday processes to boost productivity, increase results and optimize resources. Ultimately, they’re also leveraging the power of these new technologies to stay relevant and competitive.  

Companies that are ready to digitally transform their business should first create a strategy for success before diving head first into big change. This means outlining a plan for the why, what, how, and when of achieving transformation objectives. If you’re looking to reap the full benefits of digital transformation in your company, it’s a good idea to create your own game plan.

Here’s our recommended approach to starting on the right path:

1. Why: Assess Business Goals

First thing’s first. You’ve got to determine why it’s time to make the shift and what you want to achieve through digital transformation. Ask yourself: what are the business goals we want to achieve better or faster with new technology? Where do we see ourselves in six months? A year? Five years? Once you know the objectives you want to work toward, you can figure out how to achieve them.

2. What: Determine What to Enhance

Create a prioritized list of operational problems you’d like to solve, technologies you’d like to update, and processes you’d like to automate. Decide how, specifically, you’d like to improve. A good way to do this is by looking at the information available regarding various technologies and processes (for example). Find out what works for businesses like yours, and compare what you find with your current operations. This will tell you exactly what parts of your business could benefit most from a technology update or change.

3. How: Research the Options

There are a variety of technologies out there designed to transform the way you work. Not all of them are going to work for company’s needs. That’s okay. Put in the time exploring different options, comparing their offerings to what your goals are. How can they help you reach them – be realistic about which ones make sense for your organization? Doing this will help you decide what combination of technology solutions is the best fit for your business.

4. When: Create a Timeline

Once you decide the technologies your business needs to grow, change and improve processes, you should decide on an implementation timeline. You may not have the funds and time to do the entire transformation at once. So, it’s critical to plan out when each of the key steps should happen. This allows you to properly allocate resources to make sure the transformation happen according to your vision.

It’s also important that all C-level positions and managers in your company are aware of, if not involved in, the implementation timeline. They will be important to lend support for and even drive the transformation process, not to mention help resolve any challenges that come up.

Need Help?

At Process Fusion, we specialize in developing technologies that help you process faster and share more securely. If you are looking for experts to help you digitally transform your business, please reach out. We would love to discuss your company’s goals and work with you to create a digital transformation strategy that helps your business move forward in the right direction.

4 Ways Digital Transformation Accelerates Your Processes

Time is money, there’s no way around it. If your employees are spending valuable time performing manual labor-intensive projects, your business is wasting money and time waiting for results.

Enter digital transformation.

Digital transformation is essentially the integration of digital technology into business processes to improve work and business outcomes. The idea behind it is to enhance how your company does business so you can boost productivity, save resources, and eliminate inefficiencies and flaws associated with human error.

Here are four ways to use digital transformation to  take your business to the next level:

Data Capture

Data capture is the automatic identification and collection of an object’s data. This data gathered through optical or audio technology is converted to a digital format and entered into a computer system, sans human involvement. A great example of data capture in action is the conversion of a paper document into an editable, digital formats like PDF or Microsoft Word or Excel. Manual data entry is often error-prone and time-consuming. Automating this activity eliminates both of these issues and allows you to add data gathered to your digital workflow, boosting productivity, increasing efficiency and saving valuable resources at the same time.

The Cloud

As 90% of organizations use the cloud in some way, you’ve probably heard of it before. The cloud is a massive, online server that allows employees to securely access company documents anywhere and anytime. Thus, it maximizes collaboration, productivity, and efficiency in a business setting. Cloud technology also helps control access to documents and data belonging to your company and your customers. It’s no wonder that 50% of businesses using the cloud cite it as their preferred digital transformation solution.

Artificial Intelligence

AI technologies can help your business automate processes and reduce the amount of time it takes to perform a variety of key functions. Depending on your industry and operational requirements, there are a few examples that are accessible through a range of business software tools and platforms:

  • Machine Learning: A branch of AI that uses algorithms to find patterns in data in order to predict outcomes and classify data. A more in-depth write-up on how machine learning can add value to your business can be found here.
  • Natural Language Generation: Technology that produces natural-sounding language and text from computer data to automate content production. It’s especially useful in customer service, operational reporting, and business performance analysis.
  • Robotic Process Automation: Artificial intelligence that uses scripts and other forms of communication to automate human support. For instance, when you receive a generated reply in regards to your email inquiry or when a robot directs your call.

There are a variety of other AI approaches that can help your business embrace digital transformation.


It’s both cumbersome and risky a pain to send multiple versions of sensitive documents back and forth between colleagues. There’s a large margin for human error, and it takes time to make sure you’re updating the right document(s). Blockchain is here to eliminate these headaches. Essentially, blockchain is a continuously growing database of records (aka, blocks) that are linked together using cryptography. Each block is timestamped, making it easy to track edits.

50% of financial organizations see mainstream adoption of blockchain by 2020.” That’s fast growth, but not surprising as the new technology is already revolutionizing the way financial organizations are recording transaction histories.

Digitally Transform Your Business

With so many options out there, it can be hard to know where to start when it comes to selecting the right digital transformation tactics for your business. We specialize in helping businesses determine processes that they can implement and update in order to boost productivity and save resources. If you’re interested in learning more about how digital transformation can benefit your business, reach out today.