Behind the scenes of any business process management workflow is a web of complex decision-making. Data whizzes through a decision tree, turning left at some waypoints and right at others to arrive at an ultimate conclusion. To the untrained eye, the code that routes data through a process reads like a foreign language, hampering communication between computer science whizzes and front-office team members. At the intersection of these two diverse groups is Decision Model and Notation (DMN).

What is Decision Model and Notation?

DMN is one of three complementary standards introduced by the Object Management Group (OMG), a global consortium dedicated to standardizing the languages behind different process management systems. Serving as a translator of sorts, DMN converts the code behind complex decision-making into easily readable diagrams. DMN enables everyone from C-Suite executives to technical developers to visualize the decision trees powering every workflow.

Organizations can use DMN to illustrate the logic behind many processes you’re likely familiar with:

Pricing calculators: DMN helps visualize the many conditions systems assess to produce an airfare or rental car rate.

• A traveler is browsing for tickets to Des Moines, Iowa.
• It is the week of Thanksgiving. Business rules state prices are higher during this timeframe, as are flights to the Midwest.
• The pricing platform displays a final price based on destination and time of year.

Product recommendations: DMN helps an internal team devise how their systems determine what holiday gifts or weekend movies a platform suggests to a given user.

• A viewer is browsing movies on a Friday night.
• Their customer profile indicates they usually watch comedies.
• It is November, so holiday movies are now available.
• The system recommends the latest holiday comedies.

Loan applications: Banks and credit unions can use DMN to pinpoint the Know-Your-Customer checks an application must move through before approval.

• A customer submits a loan application through a self-service portal.
• An automation routes the application through a background check system.
• The customer is red-flagged within the verification system.
• The system denies the application.

Vacation time: Calculate how much time off employees aggregate over the year.

• An employee has worked with the company for five years.
• The company awards three vacation days each year.
• The employee has earned 15 days of vacation.

DMN serves as a very user-friendly way to communicate IFTTT (if this, then that) business rules that govern both internal and customer-facing processes.

How does DMN complement BPMN and CMMN?

DMN is one of three important languages for business process modeling. Working alongside Business Process Modeling Notation (BPMN) and Case Management Model and Notation (CMMN), organizations have access to a full library of languages to help citizen developers and IT professionals collaborate on workflows and automations.

Business Process Modeling Notation

Business Process Modeling Notation (BPMN) illustrates the grand scheme of a predictable, repeatable process. BPMN Diagrams pinpoint the start and end of a workflow, as well as show the sequence of events that take place throughout.

Simple example: An event planner uses BPMN to layout the tasks involved in planning an upcoming party. Twelve weeks before the event, an automated system collects RSVPs, creates a seating chart, and polls attendees on their food preference.

Case Management Model and Notation

Not every process is predictable where a decision can be made following a set of concrete, fixed steps. In fact, there are many circumstances where an automated process requires human intervention to make a decision. Enter Case Management : a technique used to manage a state that diverges from the norm. Case Management Model and Notation helps teams model these fringe processes to integrate steps performed by an intervening knowledge worker.

Simple example: A party guest selects “Other” from the food preference survey and indicates an obscure food allergy. The system flags this response, and automatically alerts the party planner to further investigate the allergy and order a specialty dish for this fringe case.

Decision Model and Notation

DMN zooms in on the detailed logic behind each step.

Simple example: While an activity in a BPMN Diagram might read “Create Seating Chart,” DMN provides the granular logic powering this step. DMN pinpoints the detailed inputs like relationship compatibility and age of attendee to decide at where each guest will sit.

How to model a simple decision using DMN

A diagram used to map DMN is known as Decision Requirements Diagram. This model easily illustrates a complex network of decision waypoints that support an ultimate conclusion.

Let’s explore a simple DRD using the example of an ecommerce platform called Snow Shoppe selling popular holiday gifts. The holiday season is rife with promotions, deals, and customer rewards. While a popular item might be $99.99 for the majority of the calendar, there are lots of conditions surrounding this special time of year that ultimately impact an item’s price.

Let’s envision Snow Shoppe is setting Snow Globe prices based on a customer’s reward tier.

Instead of an individual worker manually tabulating the final price, these rules exist in a decision table. While code ultimately performs the calculating, front-office employees like sales or marketing can easily visualize how pricing is determined.

This chart uses the three elementary elements of a DRD:

Before displaying a price, the system assesses whether the account holder is a rewards member. If the shopper is a top-level Gold Member, the system subtracts $20.00 for a final price of $79.99. If the member is shopping as a guest, they will pay the standard list price of $99.99.

The holiday season is a big time of year for many businesses. Even with an advanced plan, marketing and sales teams might come up with fresh promotions that need rapid implementation. With a few changes to the visual model, they can easily communicate this necessary update with IT.

Perhaps Marketing wants to launch an additional promotion plan unlocked by a given rewards tier. You can create a series of dependent logic so one decision’s output fuels the input for the next. For instance, perhaps Gold Members get an additional discount on Black Friday. Once the system determines a shopper’s membership level, it will then use that information to determine whether time-sensitive Black Friday pricing is relevant to that rewards tier.

How to use FEEL in your DMN

Friendly Enough Expression Language, known as FEEL, helps express a variety of conditions for assessing data. In the chart above, you can use TRUE or FALSE to determine whether it is Black Friday, but FEEL has a variety of uses for calculating price within this DMN:

• The number of days before a big holiday is greater than a certain number.
• The customer has purchased a total dollar amount over the course of the year.
• A personalized date, like the celebration of the customer’s birthday.
• The number of Snow Globes that are in the customer’s cart.

FEEL helps citizen developers and IT professionals drill down on the nuances of very unique conditions within a DMN.

Decision Model and Notation is a powerful tool for establishing the granular logic at the foundation of your organization’s business rules. While complex code can mire dialog between business users and advanced technical experts, DMN bridges the gap to encourage crystal clear communication between departments.

Originally published at https://www.processmaker.com on November 2, 2020.

Decision Model and Notation Tutorial was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

1st Inaugural ProcessMaker Virtual User Conference

Join us on March 11th for a day of online sessions showcasing the latest in process automation technologies, customer success stories and use cases, partner, integration, and product roadmap sessions and a message from founder and CEO Brian Reale. Register now via Zoom or view the agenda below.

10:00am — Keynote Fireside Chat with ProcessMaker Founder & CEO on “The Future of HyperAutomation & Low-Code”

• Brian Reale, Founder & CEO, ProcessMaker
• Q&A

10:30am — Keynote “Process Automation for Business Survival”

• Sandy Kemsley, Industry Analyst & Blogger, Column II
• Q&A

11:00am — Industry Panel “Hyper Automation and the Convergence of BPM, RPA, Rules, & iPaaS”

• Moderator: Brian Reale, Founder & CEO, ProcessMaker
• Participants:
• Param Kahlon, Chief Product Officer, UiPath
• Jacob Feldman, CTO, OpenRules
• Craig Stewart, CTO, SnapLogic

12:00pm — Customer Success Story “How the leading ERP in Energy Leverages Modern Process Orchestration”

• Tim Wadle, Product Manager, P2 Energy Solutions
• Brandi Greek, Product Manager, P2 Energy Solutions

12:30pm — Tech Talk “Product Evolution: The Next 12 Months for ProcessMaker”

1:00pm — Customer Success Story “Adapting to Changing Market Conditions with Process Automation”, Cooperative Bank of Kenya

1:30pm — Closing Remarks ProcessMaker’s Global Mission

Register now for ProcessCon via Zoom

Originally published at https://www.processmaker.com.

ProcessCon 21' Virtual User Conference on March 11th was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

The road to digital transformation is anything but straightforward.

Some organizations get so hung up on adopting new technologies they neglect to consider the people who’ll use them. Other organizations are often too change-resistant to even try.

Meanwhile, consumer expectations have never been higher. Today’s customer wants the user-friendliness of the iPhone, the personalization prowess of YouTube, and the one-click nature of Amazon-ideally from every business they transact with.

To help bridge the gap, this article offers a three-step framework that your organization can act on relatively quickly (without getting lost along the way).

1. Choose one business process to automate

One of the ultimate goals of digital transformation is eliminating silos. But for organizations just getting started, intentionally isolating one business process can not only produce quick wins, it can also better the odds of repeatable success.

That’s why we recommend starting with a business process that would clearly benefit from automation. For many organizations, this could mean a contract approval process. For others, it might mean appointing a chatbot to answer frequently asked questions.

No matter what process an organization chooses, those that understand the baseline cost and impact of their process will be in the best position to push for company-wide transformation.

For example, let’s say you’re a customer support manager. If one customer support process involves 10 employees who earn $50K/year, the total cost of that process is $500K/year.

If your team performs 250K tasks per year in service of this process, the cost per task is $2. But if intelligent process automation (IPA) can automate 100 percent of those tasks, the cost falls to $0, saving $375K worth of employee time that could be better spent elsewhere.

2. Define business logic and key integrations

Once you’ve chosen a business process to automate, it’s time to define how that process will work.

Known as business rules, this step is crucial to an organization’s digital transformation. By defining how businesses processes should occur, organizations can:

• Eliminate the inefficiencies that undocumented business processes usually produce
• Scale their operations while providing employees with optimum levels of autonomy

To execute and manage these business rules, organizations must also identify and implement the right technology. This is likely to include:

• Integrations needed to complete the process (e.g. government data API calls)
• Low or no-code AI add-ons (e.g. NLP chatbots such as )

But having a bunch of separate integrations and third-party apps won’t unify your operations any more than manual human interaction. To bring everything together, you’ll also need a platform that supports end-to-end automation.

3. Decide on the right automation platform

Workflow software is one of the most saturated markets in SaaS. To choose the right process automation technology best suited to its needs, an organization must carefully weigh the options.

Integration platform as a service (iPaaS)

The simplest workflow solutions are integration-based. Using an iPaaS tool like Zapier, an organization can connect thousands of apps to automate simple processes.

Due to their plug-and-play nature, iPaaS tools like Zapier work well for small businesses, entrepreneurs, and anyone looking to make certain tasks more convenient.

For instance, a customer service manager might use an iPaaS tool to automate the creation of spreadsheets that contain links to customer call recordings.

But an iPaaS tool won’t fit the bill for large or high-volume organizations. Building complex, multi-step workflows can get messy-and if things break, you’ll have to figure it out on your own.

Enterprise resource planning software (ERPS)

Enterprise resource planning software (ERPS) is a must-have for manufacturing companies of all sizes.

With an ERP solution, organizations can oversee production and access critical backend data that helps them make better business decisions.

But the drawbacks of ERP can easily outweigh the benefits. On its own, ERP software is:

• Expensive to implement
• Dependent on extensive employee training
• Slow to deploy (projects may take 1–3 years before fully functional)
• Inflexible (no APIs or third-party integrations)

Intelligent business process management suite (iBPMs)

The most complex solutions support AI-driven workflows. Dubbed “intelligent” business process management software (iBPMs) by Gartner, these tools leverage artificial intelligence to take automation several steps further than the alternatives.

For complex, high-volume organizations like financial and healthcare institutions, this means connecting legacy systems to third-party software to enhance process automation.

With machine learning and robotic process automation in place, organizations with complex infrastructures save tons in operating costs by eliminating the need for human intervention and manual data analysis.

The journey to digital transformation

Experience is often the best teacher. Any organization eager to begin its digital transformation should experiment with a few different automation solutions (through a mix of free trials and demos) before making a commitment.

Originally published at https://www.processmaker.com on January 25, 2021.

How to Kickstart Digital Transformation in 3 Steps was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

Business process management, hailed as the modern wizard of business productivity, has evolved. iBPMS, the intelligent evolution of BPM, is the new workflow whiz kid, rapidly ascending to the top of the list of technology that can truly transform how your business runs. iBPMS expands on the foundations of BPM by adding in a heavy dose of smart automation technologies like artificial intelligence . iBPMS can rapidly analyze diverse data sets at hyper-speeds-but its robust, lightning-quick capabilities are not mandatory for every type of business. How do you know if your organization needs the full power of a complete intelligent business process management platform?

What is iBPMS?

First introduced by Gartner in 2012, intelligent business process management software (iBPMS) has evolved beyond a business buzzword . By harnessing the sheer power of AI, iBPM gives businesses the ability to manage the modern deluge of data streaming in from social channels, new devices, and expansive IoT systems.

Gartner identifies a complete iBPMS as one with functionalities that revolve around:

• Model-driven composition environment: Instead of manually coding in programming languages like .NET or JavaScript, iBPMS breaks down the barriers of development by inviting citizen developers to design business processes. Advanced AI serves as the translator between visual diagramming tools and final implementation, automatically generating code from flowcharts and other layperson visuals.
• Continuous intelligence: iBPMS ups the ante on “real time” by constantly analyzing incoming data at never-before-seen speeds.
• Business activity monitoring: iBPMS improves the situational awareness of your systems. AI can quickly share incoming data and newly discovered information with related processes and personnel.
• Business rules management: Legacy systems are known for their unwieldy designs. Their intricacies are so delicate that they often stand in the way of change . iBPMS can transform even a monolithic system into a lightweight, agile platform by making it easy to adjust the underlying rules and conditions that impact systematic decision making.
• Process orchestration engine: A process orchestration engine manages all of the moving parts. This powerful engine streamlines all the relevant technologies and components that must work together to execute a particular process.

iBPMS infuses AI into all of your systems to increase speed, be it speed of implementation, speed of decision making, or speed of information processing. iBPMS poses as the brain of your organization, reacting to trillions of data inputs as quickly as your brain can respond to a pinprick on your finger.

How do I know if iBPMS is right for my business?

Not every organization needs the sheer power of a complete iBPMS. Business size, growth, and level of complexity can trigger new reasons to make the switch. Here are the top factors that influence an organization’s decision to transfer over to an iBPMS.

How quickly do you need to respond to incoming data?

Banks need the ability to identify fraudulent wire transfers and suspicious credit card behavior within seconds. Automated driving platforms need to rapidly read the road to decide, in an instant, when to change lanes and when to use the brakes. iBPMS strives to further decrease the asymptotic window between event and action for organizations that need to act on complex, incoming data at lighting-quick speeds.

Is your business experiencing rapid growth?

Consider your employee headcount

It’s unlikely that a two-person business experiences too much trouble collaborating with one another. As you expand your team, complexity increases exponentially. At around 40 employees , experts estimate that a business will need more advanced productivity workflows to organize employee onboarding , manage benefits, and streamline tasks and communication. The sheer amount of information becomes impossible to manually track and accurately collate. For organizations with hundreds to thousands of employees, the automation and AI-infused capabilities of an iBPMS are a must.

Review the needs of your customer base

A small business processing ten invoices per week might have the bandwidth to manually process and pay each one. However, as the number of customers and clients grows, so does internal complexity. In fact, the Institute of Finance & Management estimates that in larger organizations, the average accounts payable representative processes over 8,000 invoices per year-a number impossible to manage through traditional manual methods. As businesses increase their customer base, they need fresh technologies like iBPMS to organize and analyze a more expansive breadth of data.

Does your business provide an omnichannel experience?

Experts estimate that by 2030, each customer will interact with your business on up to 15 different devices . A banking customer constantly switches gadgets: sending money through their smartwatch, checking balances via a phone app, chatting with a customer service agent via Facebook Messenger, and paying bills on their laptop. Your system must be ready to reflect changes to balances in mere seconds, no matter what device the customer uses. For businesses that interact with customers across multiple gadgets and channels, iBPMS can autonomously aggregate incoming data into a comprehensive user profile to serve the best omnichannel experience.

As a small business or entrepreneur, you may have the bandwidth to tackle your workflows with a lightweight automation platform. As you increase the sophistication of your processes, hire more employees, win new customers, and introduce next generation customer experiences, iBPMS becomes a must-have for large organizations.

Originally published at https://www.processmaker.com on October 23, 2020.

Does Your Organization Need a Complete iBPMS? was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

Developers may be highly skilled and experienced, but they still realize that hand-coding is outrageously time-consuming. When businesses need to meet growing needs, it’s difficult to retain enough software developers to fulfill demand. Applications miss their deadlines and quality suffers. As a result, the popularity of low-code is on the rise. Further, citizen developers are already using low-code to create custom business apps and more. low-code will comprise over 65% of application development by 2024. So, what is low-code and why isn’t it just for citizen developers? According to Gartner, low-code will comprise over 65% of application development by 2024. So, what is low-code and why isn’t it just for citizen developers?

What is low-code?

As people live and manage more of their lives digitally, the demand for new software will continue to rise . Moreover, the COVID-19 pandemic has turned remote work from a niche trend towards becoming the new normal. Invariably, the demand for new applications is skyrocketing.

Low-code uses automation to manage coding, debugging, testing, and application deployment. The low-code platform, or Integrated Development Environment (IDE), creates the application and offers the workflows and features to automate testing, debugging, and deployment either on premises or on the cloud. Then, after deployment, the application is managed and run by the platform.

Using a low-code platform can flush out high quality applications

Low-code platforms offer visual diagrams, drag and drop interfaces, and connectors to create workflows, entities, and relationships. In addition, they provide event, action, and process definition. In the background, the platform writes the software, backend databases, business logic, and designs the user interface. Next, the applications can be built, tested, and deployed in the cloud.

It’s similar to rapid application development (RAD) tools like Visual Studio or Delphi where developers can access a visual designer to drag and drop a list of visual objects and then configure properties, actions, events, and data models.

The many benefits of low-code

The demand always trends up in terms of getting things built faster and cheaper, without sacrificing quality. Low-code helps developers reach that objective by offering the ability to reduce turnaround time and write code more quickly. Indeed, with low-code, creating high-quality apps takes less time and requires fewer resources.

Unquestionably, hand-coding under time pressures will often lead to errors that can affect application performance, reliability, availability, and usability. Some development teams may vary in terms of experience and background, therefore producing inconsistencies in code quality. Over the long-term, low-quality coding can spell disaster.

Using a low-code platform means that cyber security is already baked in based on industry standards and best practices. If the goal is to produce high-quality code at a rapid clip, low-code is the solution.

Also, developers enjoy the fact that low-code platforms are extensible and flexible. Low-code can be used to extend functionality of existing applications. You can also integrate third-party APIs without having to write any code. Read more about extending low-code platforms with API Driven Architecture in Business Process Management

Not to mention that if CI/CD practices are not already part of the application workflow, then building, testing, and deployment becomes even more time-consuming and even clunky. However, a low-code platform automates testing and deployment to ensure a quicker delivery cycle.

Enhance the development process

There isn’t any reason for developers to fear the activity around interface element dragging and dropping. It may take some getting used to for developers who love outdated tactics for delivering software. Once developers get the hang of a low-code platform, it becomes enjoyable to generate code quickly. In terms of optimizing the software development workflow, a low-code platform is more cost-effective than hiring four or five more software developers. And, a low-code platform can easily integrate with existing infrastructure.

These days, every development team wants to be “agile.” Who doesn’t? Before low-code, the software development cycle would include prototyping to demonstrate the product to the intended users. On the other hand, low-code eliminates the need for prototyping because the drag-and-drop interface means developers can create a working application in the same amount of time it used to take just for prototyping.

Merge conflicts are stressful. What’s a merge conflict? Well, prior to low-code, developers would separate their incompleted code via version control system from finished software products. When new code is ready to be added, developers need to use the master branch to merge the updates. And, some developers may change the files once again but version control systems can tell which changes to add and which to delete. So then, you get undesirable merge conflicts.

Here are some other reasons why low-code isn’t just for citizen developers:

• Cross-platform: Low-code platforms are often built to deploy applications across a wide variety of platforms. Developers can use HTML or even JavaScript. All it takes is a single codebase to create applications for the mobile and desktop space. Write once, and run everywhere.
• Integrate seamlessly: Before software deployment is said and done, often developers have already tried to integrate data stores, third-party APIs, and open-source libraries. Unfortunately, each iteration needs new code to manage the requirements of every dependency — and, the code does require maintenance. Yet, low-code offers templates and instant connection logic.
• Reduce the workload: Developers can’t resist their need for speed. As mentioned in several of the points above, quick deployments mean developers can amplify their workflows. It’s the write-once-run-everywhere paradigm that is appealing. Reduce the time it takes to hand code, eliminate bugs, and maintenance requirements. What’s not to love? Low-code reduces the time-crippling slowdowns of manual coding and testing. When developers use low-code, they feel free.
• Quick turnaround: In contrast to the alternative, low-code is easy to use and learn. Developers don’t have to worry about learning a new programming language. Low-code is as easy as drag-and-drop. Getting up to speed with low-code is rather quick.
• Deploy rapidly: Unquestionably, application projects can be very complex. Deployment processes are also quite complicated. At times it involves a shell script to package the master code, send it to the servers, and hope for a successful callback. And, deployment might require maintenance to perform backups and upgrade the databases. In contrast, low-code takes care of a majority of the DevOps tasks. The hard work is taken care of so developers can work on projects they enjoy.

Low-code decreases the average workload and takes the pressure off developers. The code is reusable for any app as necessary. Since the code is reusable, developers will notice a significant decrease in application time-to-market. Low-code also saves time around testing, implementing security, and verifying reliability. Further, application development is truly scalable while developers can easily clear out their backlog and streamline their workflows.

Use the low-code advantageIndeed, most code will be managed and written on low-code platforms in the future. Using visual IDE components saves on time, resources, and complexity. Once a low-code application is built, use a few clicks to debug, test, and deploy. Unquestionably, there is a reason why low-code isn’t just for citizen developers. It is the means for getting more done in less time. And, developers will have the ability to focus on strategic applications. If you’re interested in learning more about how low-code can optimize your development cycles, Processmaker is here to help.

Originally published at https://www.processmaker.com on November 6, 2020.

Why Low-Code Isn’t Just for Citizen Developers was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

One of the core functions for a treasury is money modeling. Invariably, every entity must have a tight handle on their liquidity positions and funds. In a rapidly-evolving marketplace, this isn’t without it’s fair share of challenges. As a result, many treasuries need to step it up as modern business has become increasingly complex and volatile. Accurate management, reporting, and forecasting is critical. There isn’t any question that high-value activities such as cash management can easily become problematic. Further, increasing the quality, consistency, and accuracy of data is crucial. In addition, real-time access to treasury analytics and cash data can help to improve a compliant and secure treasury infrastructure. The lifeblood of any organization is cash flow, but there is also a dire need to have the right tools in place to explain variances and to predict shifts in the market.

The evolution of treasury processes and management systems

Treasury management is a field designed to understand and report on cash flow data. Initially, treasury processes involved a lot of manual paper recordings, manual workflows, and processes. As technologies have evolved so have some of the processes in the treasury. Unfortunately, Strategic Treasurer has found that some institutions still rely on Excel for handling forecasting and other treasury-related tasks. While digital transformation deployments have taken many industries by storm, some treasury departments are still way behind the competition.

The fourth industrial revolution and treasury

According to IDC Financial Insights , banking CIO’s are making digital transformation their first priority and plan to dedicate 40% of their IT spend to the effort. Now, let’s discuss Industry 4.0.

When you think of the Industrial Revolution, you probably think of manufacturing and not treasury. It’s true, the First Industrial Revolution occurred when the world mechanized production. The second industrial revolution is associated with using electricity for mass production, and the third encompasses automation and digitization. However, we are now in Industry 4.0. What is the Fourth Industrial Revolution? Well, Industry 4.0 is about blurring the lines between the physical and digital worlds. It is also about a world of connected devices via IoT and AI. Moreover, it melds the skills of both humans and machines.

Treasury functions will be impacted by Industry 4.0, as well…

In terms of digital transformation, next-gen treasury functions will be highly integrated with intelligent automation. Better data will drive decision-making so that the treasury can eliminate error-prone processes and the “rear view mirror” paradigm.

Here are some of the technologies expected to transform treasuries:

• Artificial intelligence (AI) and machine learning (ML)
• Robotics Process Automation (RPA)
• Cloud computing
• Open application programming interface (APIs)
• Big data and advanced data analytics

Invariably, this process won’t happen overnight. Bankers play a role in taking the time to understand the real-world examples of intelligent automation for use within treasury functions and processes. In fact, AI is already used in some treasury departments for liquidity forecasting. In addition, digitally transformative technologies can help treasurers calculate more comprehensive forecasts.

Another important tool for treasury process optimization are APIs. You can plug in data from banks, vendors, or fintechs and create custom dashboards with APIs. There isn’t a better time like the present to enable digital transformation for treasuries. Intelligent automation can help treasury processes become more agile, flexible, scalable, and efficient. You don’t want to leave complicated investments or nation-specific risks to an Excel spreadsheet. Moreover, it’s vital to have the right technologies in place to detect and help prevent payments fraud. So then, it’s imperative for bankers to look for value-adding opportunities throughout every treasury process. Digital transformation is the only path for ensuring banks are equipped to support their customer’s treasury needs both now and in the future.

The benefits of digital transformation for treasury services

Consider the advantages of next-gen automation to dramatically reduce the time it takes to onboard new customers or to provide better data insights for decision-making. APIs can also give treasuries the ability to offer omni-channel experiences and new product offerings with faster service. Here are the key areas where treasury services can evolve:

• Insights — In the digital age, customers demand accurate and updated information. Treasury processes that can benefit from better data insights include capital management, foreign exchange risk, hedging, and interest rate risks. Also, higher-quality data helps with insights on risk exposures, governance strategies, and cash positions.
• Customer onboarding — Clients expect a seamless and painless onboarding experience, otherwise, they will simply take their business to a competitor. Intelligent automation can improve the entire client lifecycle by shortening response times and complexity. Not to mention, intelligent automation can remove the silos that often leave onboarding processes hamstrung. Using intelligent automation for customer onboarding can save on costs and errors associated with manual processing while improving conversions and retention.
• The client experience — Bankers should research where intelligent automation can help to provide an omni-channel experience and also offer self-service capabilities to bolster the client experiences. Of course, it’s also crucial to do so with the client persona and expectations in mind. Advanced APIs can give treasurers a 360-view of their customers to reach the objective of anticipating upcoming needs and providing relevant solutions.
• Products — As strategies and growth agendas continue to evolve, it’s important to offer faster payment services and innovative products that keep up with both customer demand and FinTechs.
• Fraud — Unfortunately, cyber crime has become increasingly sophisticated and treasuries serve as a highly lucrative target. So then, using intelligent automation for early detection and to help mitigate human error makes sense.

Smarter treasuries

At its core, a smart treasury uses intelligent automation for rules-based operational processes. As a result, employees can focus on higher-value tasks. Invariably, intelligent automation is applicable in a wide variety of treasury services, workflows, and processes. Automating time-consuming manual tasks is a start. Once operational processes incorporate intelligent automation, then treasuries have a better capability to make sense of big data to focus on long-term capital financing goals. Use automation to break down departmental silos so all records can be managed and updated in real time.

Treasury shouldn’t operate as an island. Intelligent automation can help treasurers keep up with evolving customer needs. When used correctly, intelligent automation can improve and accelerate account openings, payments, and internal processes. Decision-making is easier, and workflows are more efficient. Additionally, when business processes are streamlined and transparent, both employees and customers become more engaged.

Final thought

Bankers must always consider industry, maturity, and client preferences when seeking to improve offerings, the client experience, and channels. Further, intelligent automation can help to consolidate redundancies and contribute to reducing operational costs as well as complexity. Repetitive processes can be automated and streamlined allowing for human employees to focus on value-added projects instead. Moreover, API-driven architecture can help to create a 360-degree view of their clientele.

With Processmaker, enabling digital transformation for treasuries is easy. The platform offers a user-friendly interface that doesn’t require any extensive training or coding skills. Ready to get digital? Optimize and streamline treasury processes with Processmaker.

Originally published at https://www.processmaker.com on November 10, 2020.

The Banker’s Role in Enabling Digital Transformation for Treasuries was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

Higher education has become increasingly competitive as colleges and universities compete for a dwindling pool of prospective students. According to the National Student Clearinghouse Research Center, fall 2020 undergraduate enrollment decreased by 4 percent from the prior year. Community colleges have fared the worst, with enrollment falling 9.4 percent.

A confluence of factors are to blame for declining college enrollments. One is that the population of American high school graduates has plateaued. Another is that years of economic prosperity has discouraged older students from returning to school. And then there is, of course, the COVID-19 pandemic that has ushered in what many are calling the “new normal”.

While colleges and universities face more challenges to their core business models, student service expectations have not diminished. These pressures have led many schools to leverage cost-effective automation technology to lower costs and provide exceptional student experiences. Three areas where schools have focused their automation efforts are the student journey, creating smart campuses, and back office processes.

Student Journey Automation

For schools to succeed in this dynamic and competitive new landscape, they must provide superior experiences at every stage of the student journey.

Enrollment Process

Improving college enrollment is a critical and complex process that involves many different criteria, parties, and workflows. Business process management (BPM) software helps schools to automate the enrollment process. Customizable forms make it easy for students to register and for schools to streamline communication with students. Centralized student records allow student enrollment staff to access student data from anywhere and quickly notify students of application decisions to keep them from enrolling elsewhere.

Student Services

Student services play a vital role in improving the student experience and increasing retention rates. In fact, according to studies the most important factors in education quality assurance are quality of learning and support for students. One of the main reasons why students grow disillusioned with student services is one of perception. Students view their school as a single entity, but in reality, most colleges and universities are highly disconnected with each department serving distinct functions.

With automation, schools can improve the student experience by integrating student services. One way to accomplish this is by creating centralized student hubs. Students can communicate with staff and access student services (i.e., setting appointments) easily through an online portal. This serves to both increase student access to services while increasing transparency into departmental functions.

Financial Aid Process

The financial aid process plays an integral role in both the college application and selection processes as well as student experience once enrolled. For many students, deciding which school to attend is as much about cost as it is about quality. Thus, it critical for schools to help students to understand their financial aid options by timely processing financial aid applications.

Yet without automation the financial aid process can be time-consuming and can result in students attending school elsewhere. Automation technologies like document capture and data extraction eliminate manual tasks, reduce costs, and greatly expedite financial aid decisions.

Smart Campus

A smart campus combines the IoT and other advanced digital technologies to improve student learning, provide greater security, and lower school operating costs. Traditionally, colleges and universities have relied on manual processes and legacy single application workflows. In addition to being inefficient, these archaic processes and systems limit student learning opportunities and quality of life.

There is no one-size fits all smart campus automation solution. Rather, schools can pick and choose the automation technologies that work best for them. Students can use their mobile devices to attend video classes or access their homework assignments through online portals. Or they can use their devices to pay for meals or course materials. Or schools can solve infrastructure challenges like security through digital identification card readers or geofencing.

The flexibility that smart campus automation solutions provide will be crucial in helping schools to implement safe and engaging learning environments as we continue to adapt to the “new normal”.

Back office automation

The COVID-19 pandemic has had a devastating economic impact on U.S. colleges and universities. According to the American Council on Education (ACE) , higher education institutions will lose more than $120 billion from the pandemic in the form of decreased revenue and increased costs (i.e., COVID-19 testing and treatment). While colleges and universities may receive a fresh round of stimulus funds to keep them afloat in the short-term, they need to reexamine their long-term business models to cope with the “new normal”.

One way for colleges to free up cash is by automating back office processes, allowing them to do more with less. Automating repetitive and time-consuming administrative tasks allows employees to focus on higher-value functions. For example, at many schools much of employees’ days are filled with answering phones and responding to emails. Implementing an automation solution like a chatbot not only reduces inbound messages, but can also help to streamline internal processes (i.e., managing calendars or hunting down documentation).

Colleges and universities are subject to strict regulations. Paper-based processes require compliance teams to review and cross-reference everything in excruciating detail. Automation technology, however, can scan through large amounts of data to flag questionable items. Moreover, with a document management system , important information is kept secure and easily accessible for future use.

Schools will continue to face unique challenges that will force higher education officials to reexamine their business models and student offerings. Automation technologies will play an increasingly important role in helping schools to transform their processes. Learn how ProcessMaker’s industry leading low-code business process management (BPM) software can help your school to master automation.

Originally published at https://www.processmaker.com on November 9, 2020.

Mastering Automation at Your School was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

Over the past two decades, every industry has felt the impact of technological disruptors. Innovation has become the law of today. Due to highly-regulated environments, banks have been able to retain their position of dominance but now new Fintech competitors threaten displacement and market share.

The massive adoption of mobile phones, paired with much faster WiFi connectivity, has enabled consumers worldwide to take out loans, transfer money, open accounts, and make deposits on their mobile devices — this is true even in remote rural areas. The approval of Varo as the first consumer fintech in US history to gain full regulatory approval as a national bank has escalated the threat. Further, in China, WeChat allows users to execute a multitude of financial transactions without a bank account. If there is one thing about fintechs, it’s that they are specialized with these four crucial characteristics:

• Focus on an in-demand product or service
• Provide service at a much lower cost than traditional banks but with an amazing customer experience
• They zone in on solving customer issues quickly.
• They incorporate advanced technologies to obtain competitive advantage in the market.

They focus on a single product or service, which they provide superbly, with lower costs and an exceptional user experience. One example is TransferWise, an international money-transfer application.

Take a look at small business lender Kabbage who uses artificial intelligence to grant lines of credit in 10 minutes or less. The trend is leading towards mobile-only banks who can also offer a bank account, credit card, and debit card. These fintechs, or neo-banks, are changing the banking playbook at a rapid clip. They don’t require an army of human employees or a cadre of physical branches — hence, they forego the associated costs and complexities while passing on the savings to their customers.

In fact, APIs can connect varying suppliers of differing financial products and services so that the fintech doesn’t even have to produce proprietary products and services — this is also called open banking.

Indeed, the most logical solution for traditional banks who wish to remain competitive is to incorporate new technological capabilities into their current processes with the objective of improving agility, cost reduction, and customer engagement. In the digital economy, this is the only way banks can defend themselves against disruption from fintechs even under tremendous assault. Fintechs are gaining a foothold on the market, they are no longer niche players.

Traditional banks don’t have to throw in the towel. How can financial institutions evolve? Those with a commitment to digital transformation and improving the customer experience will be in a good position moving forward.

Competing with Disruption from Fintechs

There are several ways banks can retain leadership in the digital age, we list them below:

Determine your core audience

If a bank decides their core audience consists of baby boomers, it may work out well for another 20–30 years. On the other hand, if the bank also chooses to tailor a range of products and services for millennials, this adds another 73 million potential customers. As a result, the bank can remain relevant for decades to come.

Transform the institution into a tech company

Legacy banks must embrace digitization or risk failure. It helps to think of themselves as tech companies first, who also happen to provide banking services. In addition, it is vital to adopt the startup perspective not just in terms of making processes more agile but also in relation to talent recruitment. Then, focus on the option of acqui-hiring where you acquire a smaller fintech along with their employees. For instance, JP Morgan acquired WePay. Another piece is to hire freelancers and contractors to increase specialized talent while cutting down on hiring costs.

The point is to focus on digital banking processes. When you think of the oft-told tale of David vs. Goliath, it would seem the fintechs have the advantage. However, in the real world, sometimes David wins and sometimes Goliath comes out as the victor. The solution is to have a bit of David and a bit of Goliath. Focus on an area where a distinct advantage can be obtained such as automating time-consuming, rule-based, and repetitive processes to free up your human employees so they can spend more time addressing customer needs and enhancing the customer experience.

Implement intelligent automation

Today, the technology underlying intelligent automation is mature enough to empower banks to move towards a full digital transformation. Moreover, banks who deploy intelligent automation can save up to $70 billion by 2025.

When financial institutions incorporate intelligent automation from an end-to-end perspective, not only do they increase the efficiency of existing processes but they also improve customer engagement and turnaround times. What is vital is to deploy intelligent automation as part of a business process model redesign including updates to governance, policies, roles, responsibilities, and even organizational structure. Some examples of where intelligent automation can immediately provide a positive impact include:

• Data capture — collection and analytics of structured and unstructured data using AI to understand sentiment.
• Advanced analytics — enable data-driven, real-time insight with recognition of patterns and historical trends.
• Decision-making and predictions — intelligent automation can make inferences and learn from executing tasks while performing high-volume, repetitive, and rules-based tasks so human employees can focus on solving complex issues that add more value.

Indeed, it is imperative to tie your intelligent automation strategy to your business strategy to increase agility without affecting the customer experience. Nonetheless, this takes a thorough review of your end-to-end processes, identifying the weak links, and reengineering via intelligent automation.

Design and optimize your processes to meet customer needs

Many times, legacy banks create a customer experience that does not have all of the backend processes in mind. Sometimes they spend time on net promoter scores instead of focusing on the inherent value of data to strengthen customer relations and set themselves apart from fintechs. The only way to alleviate these issues is by redesigning and optimizing your business processes with the customer’s expectations in mind. To illustrate, a bank might use intelligent automation to capture and analyze data which can help to decrease the number of touch points and time-consuming fulfillment areas.

Invariably, with the massive influx of fintechs, it is important for financial institutions to evolve by boosting productivity while optimizing costs. With a scarcity in specialized human talent, and increase in hiring costs, intelligent automation can be used to improve processes consistently.

Intelligent automation use cases for banks

Onboarding new customers

There isn’t any question that customer onboarding can easily become a long, time-consuming process due to manual verifications and more. Intelligent automation can reduce the length of the process through data capture to automatically match information against what the new customer has provided.

Opening accounts

There is a reason why many new customers loathe opening new bank accounts, because it takes too much time. Yet, with intelligent automation, banks can automatically eliminate any data errors and auto-fill forms and more. So then, data is accurate, human errors are eliminated and turnaround times experience a significant reduction.

Report processing and generation

Artificial intelligence can decipher structured and unstructured data, even compliance documents, routing the required information to designated locations. Intelligence automation can take inputs from compliance staff to process data where needed. So then, banks can save time and reduce operational costs.

Anti-Money laundering (AML)

AML processes are critical for banks in a highly-regulated industry, but searching for suspicious activity is quite data-intensive. However, intelligent automation can automate rules-based AML processes to save both costs and time.

Mortgage lending

Intelligent automation can be used to initiate loans, process documents, manage quality, and make financial comparisons. Customers are much more satisfied when decisions are made swiftly.

Processing loans

Loan processing has never been accused of being a fun activity, for either party. Nonetheless, it is a constant process for banks, especially during the COVID-19 pandemic. The good news is intelligent automation can cut down processing times for query responses, application routing, and more. How would it impact customer engagement if you can reduce turnaround time to 10–15 minutes?

Other ways intelligent automation can help banks compete against disruption from fintechs includes automating validation of credit card applications, improving compliance around account closure requests by sending automated notifications and reminders of required documents, and even automating processes around employee onboarding.

In conclusion

To keep pace with evolving customer demands and retain a competitive advantage against disruption from fintechs, banks should focus on intelligent automation. However, it is critical to partner with a vendor who has proven expertise with intelligent automation throughout transition and implementation. At Processmaker, we have established a proprietary approach to deploying intelligent automation and will work hand-in-hand with you to create your intelligent automation roadmap before going live.

Learn More

How Banks Can Compete With Disruption From Fintechs was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

Banking is experiencing a bustling state of disruption. New competition from Fintech apps and nimble branchless banks is upending the paradigm of what it means to be a “bank.”

For these new disruptors — born in the age of “move fast and break things” — constantly iterating systems and making quick changes based on shifting trends and emerging technologies are hard-wired into their DNA. Their platforms can move at the lightning-speed shifts in customer psychology and preference. A pace that traditional legacy IT systems can’t compete with.

The buzz of new financial technologies does not have to feel like a threat to banks. It can be a valuable tool for improving customer experience. New strategies like composable banking enable traditional banks and financial institutions to leverage innovative Fintech tools; like artificial intelligence, anti-fraud machine learning, voice recognition, chatbots, and more.

Traditional legacy banking IT would cement all these services together into a single yoked, inelastic offering. Instead, composable banking separates individual functionalities from the operating whole so you can combine, edit, and adjust functions without crashing the overall infrastructure.

What is composable banking?

Composable banking untethers your team from a bundled set of legacy services and enables your team to arrange their own tech stack of banking tools. Essentially, composable banking allows you to split your bank’s functionalities into chunks, like marketing and transaction monitoring. A change to one API doesn’t require an overhaul of the entire stack. Using the “plug and play” API-enabled approach of composable banking, banks can build by selecting the best available technology tool for each section.

5 important trends that illustrate how composable banking is paving the future

Banks operating on a monolithic legacy system find it difficult to implement change. A recent study revealed that 9 out of 10 banking professionals ranked a “complicated banking infrastructure” as the biggest obstacle to upgrading their technology offering. Composable banking uncomplicates these systems to develop new opportunities that improve customer experience in parallel to the legacy system, or as a fresh perspective on your infrastructure as a whole.

1. Proprietary systems are no longer a unique value proposition

In the past, the idea of a bank operating on its own, unique legacy system was a compelling draw in attracting new customers. Now, customers no longer care about ‘what’s under the hood’ — they want fast, easy-to-use services they can access from their phone while in line at the grocery store or from their tablet while watching television. While customers used to be brand loyal, we’ve evolved into a new era of loyalty — one that revolves around convenience. If your bank cannot offer the most convenient experience, you risk losing the 97% of customers who will immediately abandon your bank for a more organized competitor.

Composable banking allows you to shop around for the most convenient, streamlined technology for each functionality under your banking umbrella. Select one vendor that offers the most state-of-the-art Know Your Customer (KYC) checks, and another that is a leading specialist in call center technology or customer data analysis. Without being locked in to a single-vendor legacy system, you can build your ideal powerhouse suite of best-of-the-best systems and offer the cutting edge convenience customers are clamoring for.

2. Composable banking frees you to make the smaller changes that add up to a big difference

When operating on a legacy system, making even the smallest change to a feature or function can have a damaging effect on the system as a whole. Functions are not meant to operate independently and rely on layers of complex code challenging to adjust in an agile way. Even the smallest adjustment can require a sweeping overhaul of a convoluted web of programming that most banking professionals are reluctant to initiate.

Using composable banking, your team is free to tweak functions and experiment with new technologies without bringing down the entire house. The theory of Incrementalism posits that the ability to make adaptable, small alterations over time leads to the biggest gains. With composable banking, you can make nimble, incremental changes without fear — and they can quickly add up into a stellar, powerhouse customer experience.

The ability to enact small changes instead of waiting for the opportunity to make one massive update isn’t just theory. Consider the mantra adopted by 5X NBA Champions, the San Antonio Spurs. Plastered on their locker room walls is the following: “When nothing seems to help, I go and look at a stonecutter hammering away at his rock, perhaps a hundred times without as much as a crack showing in it. Yet at the hundred and first blow it will split in two, and I know it was not that last blow that did it — but all that had gone before.”

3. The most powerful applications are light on infrastructure

Is the basement of your bank headquarters filled with rows and rows of expensive servers constantly monitored by your IT team? A barrier to growth for many organizations, banks included, is the need to procure and rack physical services in order to scale operations to serve a fresh influx of customers. “Serverless” — a cloud computing model where a separate party (like Amazon Web Services) manages the background infrastructure powering your banking systems, allowing you to take advantage of the cost-cutting measures enjoyed by Fintech businesses born in the digital age.

4. We’re in a new era of citizen developers

Modern Fintech tools were forged in a new era of development than legacy systems. Legacy systems are designed like an intertwined web, where tugging on one end can distort the entire shape. It’s nearly impossible for a layman to make any changes without understanding the expanse of the entire ecosystem.

While older software setups require eons of technical training to navigate, citizen developers now build contemporary platforms that extend development capabilities to your entire staff. Drag-and-drop tools make it easy for a member of the marketing team to adjust a scenario in a chatbot conversation schema, or for a sales manager to swap a new email script into an automated workflow. This fresh flexibility allows you to make changes on the fly, adaptively adjust workflows, and deputize more workers to take ownership of the technologies that define their roles.

5. Availability of powerful business process management platforms

New intelligent business process management (BPM) platforms like ProcessMaker stand as the creator of your new suite of services, connecting cross-vendor applications and functions under a single operational umbrella.

Banks are constantly in motion, processing loan applications, opening new accounts, and transferring money. A powerful BPM can overlay on top of your entire ecosystem, connecting and monitoring processes while efficiently managing the exchange of information using automation. While each platform executes the kernel of activity in which it is a specialist, a BPM platform provides full visibility into your systems and governs the efficient orchestration of every platform in your suite.

The ability to make changes, experiment with new technologies, and build a thriving ecosystem of applications is the key to achieving modern banking operations. When it comes to remaining relevant, innovative and a step ahead of industry disruptors- composable banking is leading the charge.

Decoding Composable Banking was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.

The tech industry is facing an alarming shortage in data-savvy talent. Despite reports showing men and women earning STEM degrees now more than ever, the hunt for experts in areas of machine learning, data science, and other “hard sciences” fields continues. Gartner reveals that “50% of organizations will lack sufficient AI and data literacy skills to achieve business value by 2020.” A shortage of people is not the underlying problem. The root issue is a lack of data literacy available among potential — and current — talent.

What is data literacy?

The Massachusetts Institute of Technology (MIT) defines data literacy as “the ability to read, work with, analyze and argue with data.” In short, it’s a skill that has been promoted by Gartner, FastCompany, and other leading companies as the most influential predictor of business success in tech today.

While data may be the underdog champion for any business intelligence strategy right now, confidence in data is low. Organizations are losing their competitive edge because greater data literacy increases higher enterprise performance — 85% of data literate workers say they are performing “very well” at their jobs, compared to 54% of the rest of the workforce (Qlik).

Even for digital natives like Millennials, Forbes indicates data literacy sat at only 22%. If you think that’s unsettling, the Wharton School of the University of Pennsylvania discovered in the same study that just 24% of senior decision-makers passed standard data literacy tests.

Yikes.

That’s not to say businesses aren’t trying. It’s a high-quality problem, one where we are moving a lot faster than the upcoming workforce and the rest of the current enterprise system can keep up. And not to much surprise, slower-to-innovate industries like commercial air travel, retail, education, and government are getting hit the hardest. In fact, Getting Smart reveals that “just one fifth of students ages 16 to 24 years feel comfortable interpreting and applying data.”

What’s preventing data literacy from becoming widespread?

Sure, the majority of research facilities like universities, labs, and data-driven companies are making strides in technological advancements. The Society of Experiential Graphic Design reveals a few common barriers to adopting data literacy within certain organizations:

1. Current big data software is already complex thanks to new waves made in deep learning and other data science
2. Certain enterprises do not have the computational or talent infrastructure to store, analyze, and make full use of big data, and
3. The concept of data is still foreign and even dry to many non-technical audiences, both in and out of enterprise culture

Barriers don’t just stop at technology — politics and even socioeconomic systems are factors too. (For example, Sweden has the highest percentage of enterprises where everyone is empowered to use data at 33%; Japan is at only 13%.) Barriers to data literacy include access to technological resources around the world, the rapid evolution of technology before humans can keep up, and lack of current experts available worldwide.

If data is as obscure to most C-suite and senior management figures as research indicates, companies not innovating sooner will be in a lot of trouble at the turn of the decade. Neglecting consumer trends and demand is not only costly, but bad for entire industries. Airbnb is a classic example of a business that took advantage of design, performance management initiatives like BPM, and data to understand user needs to build a better solution for its customers. Because of Airbnb’s proactivity in leveraging data’s power in its business model, the entire hotel industry is now threatened.

Fortunately, there are initiatives you can take to improve data literacy in your organization so this doesn’t happen to your business.

Encourage a data-driven culture

Data literate professionals have always been hired by data-driven companies. The problem is addressing the organizational silos that occur as a result of keeping those experts confined to only IT or intelligence departments. Since departments and teams are becoming more interdependent on one another to generate more customer satisfaction (and thus, profit), companies need to include these experts where the decision-making is happening — for most larger enterprises, that’s in the boardroom.

What happens when that doesn’t occur? The scary reality is that the majority of enterprises today won’t exist in the near future due to lack of prioritization about data.

Due to changes in the digital landscape of business, approximately half of the companies currently on the S&P 500 will be replaced over the next decade (Inc).

Microstrategy’s Content Director Tricia Morris attributes this to what she calls “digital darwinism,” or business’ ability to adapt successfully in the age of the information revolution. Companies with a “future-back strategy” that understand the future is now may have a better chance at surviving, according to Innosight research.

Often, the main hurdle to changing a less-technical company privy to the power of data starts with mindset. Many enterprises have embraced C-suite titles like Chief Intelligence or Innovation Officers, but these titles tend to focus more on leveraging business intelligence strategy, not necessarily leveraging the power of data to boost revenue strategy.

A lack of qualified leadership and ethical business decision-making on the executive board can undermine the authority and confidence of an entire enterprise (Uber is still recovering from this issue). To combat this, enterprises can focus on building stronger relationships among external and internal stakeholders, and as well as the nurture of a future Chief Data Officer (CDO) among its network, an organizational head that can help mitigate common pitfalls found as a result of data illiteracy.

But change cannot happen overnight. These processes require change from within from the leadership board to inspire growth within a business. CDOs cannot give marching orders to their employees expecting to spur change. Instead, they must “use emotional and rational arguments” to win over stakeholders, counteracting the often unsexy perceived nature of data among non-technical team members. Failure to educate your current employees and consumer base could result in becoming one of ten known companies to go out of business because of lack of innovation, as found by Collective Campus.

It’s not just about losing a competitive edge on the organizational level. Not taking care of current employee talent leaves dangerous wiggle room for employees to fall behind. And this change as to come top-down, CMS Wire suggests.

“Stop believing in unicorns,” warns Tamara Dull, Director of Emerging Technologies for SAS Best Practices. “Big data deserves a seat at the table, but it doesn’t need its own table.” Dull doesn’t believe in a one-stop-shop solution. Instead, she opts for companies to change their approach to developing a culture that encourages data literacy. Soft skills like leading by example, effective communication, and understanding KPIs in relation to business strategy can transform a company’s current elasticity to innovation.

So, we know that encouraging human-centric basics in business can ripen a data-resistant workforce to change. But what about closing the data literacy divide in technical skills? One strategy involves being proactive rather than reactive in regard to on-the-job training.

Invest in current talent

Instead of reinventing the wheel by searching for top talent elsewhere, Mike Gavin believes enterprises can take advantage today by investing in current employees.

Gavin leads Corporate Training at Metis, a data science and analytics training company. As far “upskilling” non-technical talent, the lessons “enable broader staff to identify and scope problems within the business and to perform initial analysis without needing the help of a highly technical person, “ he says in an interview with Burtch Works. “It also improves communication and collaboration between teams.”

Metis isn’t the only company to hop on the coding bootcamp or analytics academy train. Popular EdTech companies like Coursera, Udemy, and General Assembly specialize in offering certificates in data science, programming, or Business Analytics 101 for the not so data-savvy individual. Even cloud technology giants like Microsoft Azure, AWS, and Google Cloud now offer certifications in data science.

But don’t worry about these companies not delivering top-notch value. Students can expect to earn industry-recognized credentials that boost salary earnings on top of skills learned. Udacity takes this one step further by partnering exclusively with Google to offer nanodegrees, or small degree-like programs designed to address the lack of technical talent available in current enterprise institutions.

The result of these training initiatives? Recruiters are seeing improved data literacy among job candidates with new skills recycled back into the workforce, all at a fraction of the cost associated with employee churn. Retraining may cost a lot upfront, but the savings payoff is estimated in the millions thanks to happier employees and increased job satisfaction from the new skills acquired.

Sounds like a win-win to us.

Build a data literacy program

Finally, the last strategy to improving data literacy in businesses is by investing a little elbow grease into developing easily accessible data literature designed to educate multidisciplinary teams, both in and out of the C-suite.

For companies in the SaaS space like Business Process Management software (BPMS), quantitative metrics relying on data are key performance indicators of efficiency in the customer’s eyes. Teams outside of the IT department need to be able to communicate the business value of such software, a task that requires time and attention across an entire organization.

Typically, translating technical jargon is done through hiring a knowledgeable technical writer or relying on the acumen of a highly-trained Product Manager. While these practices aren’t discouraged, implementing data literature on a regular basis is an effective alternative to just relying on a data-fluent liaison to play the role of the messenger.

For implementing, Qlik recommends following a four-step process: communication, assess, train, and iterate. It’s not going to happen overnight, but making the effort at least gets the transformation started.

A look to the future

Data literacy is becoming one of the most sought-after skills an organization can have in lieu of technological advancement. While currently reports show that the majority of senior-level executives, employees, students, and the wider workforce is not data confident, there are initiatives and resources available to encourage greater fluency in interpreting data across the enterprise system.

Bottom line: Don’t let your company fall behind because of not prioritizing this critical (and proven) predictor of business success. Invest in the resources you need to overcome the challenges against barriers today by adopting data-driven practices that drive forward your business intelligence strategy, like Business Process Management (BPM).

About ProcessMaker

ProcessMaker is an American international SaaS corporation headquartered in Raleigh-Durham, North Carolina. We provide total customer support, training, and professional services to larger enterprises requiring highly-customized workflow solutions with our Business Process Management (BPM) software. Our flagship Low-Code product is the preferred choice for our customers due to its deep customization ability with little programming knowledge needed, making Low-Code an easy-to-use solution among non-technical teams.

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Why Data Literacy Will Make or Break Your Company’s Future (and How to Improve It) was originally published in ProcessMaker on Medium, where people are continuing the conversation by highlighting and responding to this story.