Sandy Kemsley’s Vlog - Future-Proofing Your Business With BPM
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Future-Proofing Your Business With BPM

By Sandy Kemsley

Video Time: 8 Minutes

Hi, I’m Sandy Kemsley of I’m here for the Trisotech blog with a new topic now that we’ve finished my series on best practices in business automation application development. Today, I’m going to talk about future proofing your business with process automation technologies such as BPM.

Now, a little over three years ago, everything was business as usual. Organizations were focused on new competitors, new business models, new regulations, but it wasn’t a particularly disruptive time. Then the pandemic happened, and that was disruptive! So, supply chains, customers, business models, everything changed dramatically in some cases.

Now, that’s not news of course not by now, but it’s become obvious that it’s not enough to have shifted to some new way of doing things in a response to a one-time event. Companies have to become more easily adaptable to frequent disruptions, whether they’re technological, societal or environmental, or they’re just not going to exist anymore. In many cases this means modernizing the very technological infrastructure that supports businesses.

So how is your business going to adopt a change? Both the changes that have already happened and the unknown changes in the future? There’s a lot that falls under the umbrella of modernization, and you need to look at whether you’re doing just enough to survive or if you’re taking advantage of this disruption to thrive and actually outgrow your competition.

I see three ways that companies have been reacting to disruption:


So you can support your existing business which is basically adding the minimum amount of technology to do the same things that you were doing before. This is purely a survival model, but if you have a unique product or service or very loyal customers, that might be enough for you.


You can improve your business by offering the same products or services but in a much better way. This will give you better resilience to future disruptions, it improves customer satisfaction and it shifts you from just surviving to thriving.


You can innovate to expand the products and services that you offer or move into completely new markets. This is going to let you LeapFrog your competition and truly thrive not just as we emerge from the pandemic, but in any sort of future disruption that we might have.

more than
managing your business processes

So I mentioned BPM, but this is about more than just managing your business processes. There’s a wide variety of technologies that come into play here and that really support future proofing of your business: process and decision automation, intelligent analysis with machine learning and AI, content and capture, customer interactions with intelligent chatbots, and Cloud infrastructure for Access anywhere anytime…

So you have to look at how to bring all of those together, and just understanding how all those fit, is like an entire day’s lecture all in one, but you probably have a bunch of those that you’re using already. Let’s look at a few kind of examples of this support/improve/innovate spectrum that I’ve been talking about though and we’re dealing with instruction and then just what it means for future proofing your business. So, supporting your existing business, a matter of just doing what you can to survive, and hoping that either you can keep up or that things will go back to normal. Now basically you’re doing the same business that you always were, but with maybe a bit of new technology to support some new ways of doing things:

But let’s just go a little bit beyond surviving disruption that you might do by sort of mandating together something to support your existing model. The next step to is to look at disruption as an opportunity to thrive. So you want to still be in the same business but embrace new technologies and new ways of doing things. So this really pushes further into looking at customer expectations: adding in self-serve options if you don’t already have them, and then coupling that with intelligent automation of processes and decisions. So, once you’ve added intelligence to your business operations to let them be done mostly without human intervention, now a customer can kick off a transaction through self-service and see a complete almost immediately by intelligent automation, same business – better way to do it, more efficient, faster, more accurate, better customer satisfaction.

Now, this is also going to be helped by having proper business metrics that are oriented towards your business goals. With more automation data is going to be captured directly,, regarding how your operation is working, and then that’s going to feed directly into the metrics. Those metrics then you can use to guide knowledge workers so that they know what they should be doing next. Also to understand how customer satisfaction is and how you can improve it.

So this lets you move past your competition, while keeping your previous business focus. So given that there’s two companies, you and your competitors, who are offering the same products or Services if one does only that survival support that I talked about previously and one does more intelligent improvements focused on customer satisfaction, who do you think is going to win?

Now, the third stage of responding to disruption and adapting to change is innovation. You’ll continue to do process and operational improvements through performance monitoring, data-driven analytics, but also move into completely new business models. So maybe you repackage your products or services and then you sell them to completely different markets, so you might move from commercial to Consumer markets or vice versa or you sell into different geography or different industries because now you have more intelligent processes you have this always-on elastic infrastructure. Here again, you’re just moving past your competition by not only improving your business but actually expanding into new markets, taking on new business models that are supported by this technology-based Innovation.

So it’s the right application of technology that lets you do more types of business and more volume without increasing your employee headcount. Without automation and flexible processes you just couldn’t do that, and without data-driven analytics you wouldn’t have any understanding of the impact that such a change would have on your business or whether you should even try it. So you need to have all of that: you need to have the the data that supports the analytics and you need to have the right type of technology that you’re applying to have more intelligent operations business operations, and this was going to allow you to move from just surviving to thriving to innovation.

Now, a lot of change here. The question that all of you need to be asking yourself now is not is this the new normal but really why weren’t we doing things this way before? There’s just a lot of better ways that we could be doing things and we’re now being pushed to take those things on.

That’s all for today. Next month I’m going to be attending the academic BPM conference in the Netherlands, and there’s always some cool new ideas that come up so watch for my reports from over there!

You can find more of my writing and videos on the Trisotech blog or on my own blog at See you next time.

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What is FEEL?

FEEL (Friendly Enough Expression Language) is a powerful and flexible standard expression language developed by the OMG® (Object Management Group) as part of the Decision Model and Notation (DMN™) international standard.

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It is a valuable tool for modeling and managing decision logic in many domains, including healthcare, finance, insurance, and supply chain management. FEEL is designed specifically for decision modeling and execution and to be human-readable to business users, while still maintaining the expressive power needed for complex decision-making. Its simplicity, expressiveness, domain-agnostic functionality, strong typing, extensibility, and standardization make FEEL a valuable tool for representing and executing complex decision logic in a clear and efficient manner. Organizations using FEEL enjoy better collaboration, increased productivity, and more accurate decision-making.

What Are Expression Languages?

FEEL is a low-code expression language, but what is the difference between Expression Languages, Scripting Languages, and Programming Languages. They are all different types of languages used to write code, but they have distinct characteristics and uses.

Expression Languages

Expression languages are primarily designed for data manipulation and configuration purposes. They are focused on evaluating expressions rather than providing full-fledged programming capabilities. Expression languages are normally functional in nature, meaning that at execution the expression will be replaced by the resulting value. What makes them attractive to both citizen developers and professional developers is that they are usually simpler and have a more limited syntax compared to general-purpose programming languages and/or scripting languages. Due to their simplicity, expression languages are often more readable and easier to use for non-programmers or users who don’t have an extensive coding background. FEEL is a standard expression language.

Scripting Languages

Scripting languages provide abstractions and higher-level constructs that make programming using them easier and more concise than programming languages. They are usually interpreted rather than compiled, meaning that the code is executed line-by-line by an interpreter rather than being transformed into machine code before execution. Popular examples of scripting languages are Python, JavaScript, and Ruby.

Programming Languages

Programming languages are general-purpose computer languages designed to express algorithms and instructions to perform a wide range of tasks and create applications. They offer extensive features and capabilities for developing complex algorithms, data structures, and user interfaces. They offer better performance compared to scripting languages due to the possibility of compiling code directly into machine code. Examples of programming languages include C++, Java, and C#.

Is FEEL Like Microsoft Power FX (Excel Formula Language)?

FEEL and Power FX are both expression languages used for data, business rules, and expressions, but in different contexts. Power FX is a low-code programming language based on Excel Formula Language, tailored for Microsoft Power Platform, with some limitations in handling complex decision logic. As soon as the business logic gets a bit tricky, Power FX expressions tend to become highly complex to read and maintain. On the other hand, FEEL is a human-readable decision modeling language, designed for business analysts and domain experts, offering a rich set of features for defining decision logic, including support for data transformations, nested decision structures, and iteration. FEEL provides clear logic and data separation, making it easier to understand and maintain complex decision models.

While Power FX has a visual development environment in the Microsoft Power Platform, FEEL is primarily used within business rules and decision management systems supporting DMN and process orchestration platforms. FEEL is a language standard across multiple BPM and decision management platforms, providing interoperability, while Power FX is tightly integrated with Microsoft Power Platform services. For further comparison, Bruce Silver’s articles FEEL versus Excel Formulas and Translating Excel Examples into DMN Logic.

FEEL Benefits for Technical people and for Business people.

Technical Benefits of FEEL

Decision focus language

FEEL is designed specifically for decision modeling and business rules. It provides a rich set of built-in functions and operators that are tailored for common decision-making tasks. This decision focus nature makes FEEL highly expressive and efficient for modeling complex business logic.


FEEL supports common mathematical operations, string manipulation, date and time functions, temporal logic and more. This expressiveness enables the representation of complex decision rules in a concise and intuitive manner.

Decision Table Support

FEEL has native support for decision tables, which are a popular technique for representing decision logic. Decision tables provide a tabular representation of rules and outcomes, making it easy to understand and maintain complex decision logic.

Strong typing and type inference

FEEL is a strongly typed language, which means it enforces strict type checking. This feature helps prevent common programming errors by ensuring that values and operations are compatible.

Boxed Expression Support for FEEL

Boxed expressions allow FEEL expressions and statements to be structured visually including:

  • If, then, else statements
  • For, in, return statements
  • List membership statements
  • … and more.

These visual constructs, along with autocomplete make creating, reading, and understanding complex expressions easy to model and debug.

Flexibility and modularity

FEEL supports modular rule definitions and reusable expressions, promoting code reuse and maintainability. It allows the creation of decision models and rule sets that can be easily extended, modified, and updated as business requirements change. This flexibility ensures agility in decision-making processes.

Testing and Debugging

FEEL expressions can be tested and debugged independently of the larger application or system. This enables users to validate and verify decision logic before deployment, ensuring accuracy and reliability. FEEL also provides error handling and exception mechanisms that help identify and resolve issues in decision models.

Execution efficiency

FEEL expressions are designed to be executed efficiently, providing fast and scalable performance. FEEL engines often use optimized evaluation algorithms and data structures to ensure high-speed execution of decision logic, even for complex rule sets.

Integration FEEL

can be easily integrated with other programming languages and platforms. Many decision management systems and business rules engines provide support for executing FEEL expressions alongside other code or as part of a larger application. This enables seamless integration of decision logic via services into existing IT architectures and workflows.


FEEL can be extended with domain-specific functions and operators to cater to specific industries or business domains. These extensions can be defined to encapsulate common calculations, business rules, or industry-specific logic, enabling greater reusability and modularity.


FEEL also enables the sharing and reuse of decision models across different organizations and applications.

Business Benefits of FEEL

Standardization and Vendor-neutrality

FEEL is a standardized language within the OMG DMN standard, which means it has a well-defined specification and is supported by various software tools and platforms. Standardization ensures interoperability, as FEEL expressions can be used across different DMN-compliant systems without compatibility issues. FEEL is designed to be portable across different platforms and implementations.


FEEL focuses on capturing business rules and decision logic in a way that is intuitive and natural for business users. This allows subject matter experts and domain specialists to directly participate in the decision modeling process, reducing the dependency on IT teams and accelerating the development cycle.

Simplicity and Readability

FEEL has a syntax that is easy to read and understand – even for non-technical users like subject matter experts and citizen developers. It uses natural language constructs including spaces in names and common mathematical notation. This simplicity enhances collaboration between technical and non-technical stakeholders, facilitating the development of effective decision models.

Ease of Use

FEEL is supported by various decision management tools and platforms. These tools provide visual modeling capabilities, debugging, testing, and other features that enhance productivity and ease of use. The availability of modeling and automation tooling support simplifies the adoption and usage of FEEL.

Decision Traceability

FEEL expressions support the capture of decision traceability, allowing users to track and document the underlying logic behind decision-making processes. This traceability enhances transparency and auditability, making it easier to understand and justify the decisions made within an organization.

Decision Automation

FEEL has well-defined semantics that support the execution of decision models. It allows the evaluation of expressions and decision tables, enabling the automated execution of decision logic. This executable semantics ensures that the decision models defined in FEEL can be deployed and executed in a runtime environment with other programs and systems.

Compliance and Governance

FEEL supports the definition of decision logic in a structured and auditable manner. This helps businesses ensure compliance with regulatory requirements and internal policies. FEEL’s ability to express decision rules transparently allows organizations to track and document decision-making processes, facilitating regulatory audits and internal governance practices. FEEL includes several features specifically tailored for decision modeling and rule evaluation. It supports concepts like ranges, intervals, and temporal reasoning, allowing for precise specification of conditions and constraints. These domain-specific features make FEEL particularly suitable for industries where decision-making based on rules and constraints is critical, such as healthcare, finance, insurance, and compliance.

Decision Analytics

FEEL provides the foundation for decision analytics and reporting. By expressing decision logic in FEEL, organizations can capture data and insights related to decision-making processes. This data can be leveraged for analysis, optimization, and continuous improvement of decision models. FEEL’s expressive capabilities allow for the integration of decision analytics tools and techniques, enabling businesses to gain deeper insights into their decision-making processes.

Trisotech FEEL Support

Most comprehensive FEEL implementation

Trisotech provides the industry’s most comprehensive modeling and automation tools for DMN including support for the full syntax, grammar, and functions of the FEEL expression language. To learn more about basic types, logical operators, arithmetic operators, intervals, statements, extraction and filters supported by Trisotech see the FEEL Poster.

FEEL Boxed Expressions

Boxed Expressions are visual depictions of the decisions’ logic. Trisotech’s visual editor makes the creation of Boxed Expressions and FEEL expressions easy and accessible to non-programmers and professional programmers alike.

FEEL Functions

FEEL’s entire set of built-in functions are documented and menu selectable in the editor. The visual editor also offers supports for the Trisotech-provided custom FEEL functions including functions for Automation, Finance, Healthcare, and other categories.


The Trisotech FEEL autocompletion feature proposes variable and function names including qualified names as you type when editing expressions thus saving time and improving accuracy.

FEEL as a Universal Expression Language

Trisotech has also expanded the availability of the international standard FEEL expression language to its Workflow (BPMN) and Case Management (CMMN) visual modelers. For example, FEEL expressions can be used for providing Gateway logic in BPMN and If Part Condition expressions on sentries in CMMN.

FEEL Validation and Debugging

Trisotech provides validation for FEEL and real-time full-featured debugging capabilities. To learn more about testing and debugging read the blog Trisotech Debuggers.

Additional Presentations and Blogs

You can also watch a presentation by Denis Gagne on using FEEL as a standards-based low-code development tool and read a blog by Bruce Silver about how using FEEL in DMN along with BPMN™ is the key to standards-based Low-Code Business Automation.

OMG®, BPMN™ (Business Process Model and Notation™), DMN™ (Decision Model and Notation™), CMMN™, (Case Management Model and Notation™), FIBO®, and BPM+ Health™ are either registered trademarks or trademarks of Object Management Group, Inc. in the United States and/or other countries.



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Trisotech's blog post - Invoking AWS Lambda functions
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Invoking AWS Lambda functions

By Trisotech

Read Time: 2 Minutes

You have created your own code in an AWS Lambda function in Python, Java, JavaScript or C# and want to integrate it with an automated workflow created in the Trisotech Digital Enterprise Suite?

This simple Python function says hello from the region it is deployed in with HTTP 200 as plain text.

AWS Lambda Function can be easily deployed but it is important to make sure that access to this function is restricted. This is where authentication comes into the picture. In this case it is going to be based on an API key that is assigned and provided to the consumers of this function. To be able to use API key-based authentication, the function needs to have a trigger based on API Gateway.

Adding API gateway is done via adding a trigger to the function. It is important to use the REST-API as the type and API key as security mode.

With API Gateway as trigger, this function will get assigned URL to invoke this function from outside. It will be in following format:


where xxxxxxxxx and region are replaced with actual value based on AWS environment.

Additionally, there will be one API key created automatically and more API keys can be created in the configuration of the API Gateway. The API key needs to be provided as an HTTP header (named x-api-key) when invoking the function.

Trisotech Digital Modelling and Automation suites trivialize the orchestration of externally defined code with its low code approach if it’s exposed though a standard REST API that can be described using the OpenAPI (Swagger) standard.

The integration is done through a BPMN service task that invokes the lambda function.

The lambda function is referenced using the Operation Library that allows to define where the lambda function can be accessed, its parameters and its security constraints. Clicking on the service task gear will allow you to create a new Interface and Operation.

Name your Interface and configure it (using the pen icon) with:

Security section defines the mechanisms to authenticate when invoking the service. In this case, it uses API Key as defined in the API Gateway for the AWS Lambda function.

Name your Operation and configure it (using the pen icon) with:

This integration allows to invoke lambda functions written in any language, but also more complex services exposed through a REST API opening an infinite world of orchestration and integration using your existing or newly created functions and services.

Trisotech also offer an Automation Cookbook as part of the Digital Automation Suite that contains a lot of other recipes to integrate systems and with its automation capabilities.

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