As an enterprise IT solution, SMARTS has different customers in the same organization who directly use it or indirectly benefit from it. This blog post aims to succinctly describe who our customers are, what they want, and what value we bring to each of them that matches their unique needs.
In our terminology, these are the customers in the organizations who design, author, deploy, and update decisions according to the company’s policies and industry’s directives.
When they looked for a decision management solution, they looked for product simplicity and rich functionality. More importantly, they wanted autonomy once the solution was in place.
After a few weeks after training on SMARTS, our business analyst customers reported that they very much liked to have data, models, and business rules in the same tool. They enjoyed how we succeeded in managing SMARTS’ evolution to have both richness and easiness in the same product. They also enjoyed being able to quickly author, test, deploy, run, monitor, and change decisions. Their experience with SMARTS was a joy as they could focus on the decisioning process and its outcomes instead of the technology to implement it.
Business users are the people who run, monitor, and manage the performance of the business. In our case, they are the internal customers of business analysts. They are the ones who use the solution daily.
They wanted to know how easy it will be for them to monitor decisions built by business analysts and make the necessary changes when the actual performance may deviate from the expected performance.
After using SMARTS, business users reported the following benefits: Quick change-test-deploy-run cycles, being able to work without coding and with no prior knowledge of machine learning or business rules, just with their knowledge of the business and using web forms and point-and-click.
By IT, we designate IT the people who install and connect the solution to the rest of the organization’s IT system. They asked for integration, performance, security, and fit with the IT global architecture and governance.
They want to have business analysts and business users to be autonomous but at the same time being able to monitor the solution as the rest of the IT infrastructure.
IT people liked all the performance, security, integration, and scalability we promised. They also appreciated SMARTS adherence to the enterprise IT architecture and governance as expected. They liked how easily they could deploy SMARTS on premises or in the cloud. Finally, they also very much liked to have no additional development or changes in the current applications.
These are the people who develop and manage models using data science libraries through languages such as Python, R, SAS, and SPSS.
They are not direct users, but they were willing to see their models fully operational into the new solution while they continue their effort on enhancing existing models and experimenting with new ones.
Thanks to SMARTS, they were able to know the performance of their models in production with real data and transactions. SMARTS was an effective demonstrator of their models.
In our case, these are the people who head organizations or verticals where decisions are at the core of their operations, throughout all the organizations activity. Their attention is “more revenue, less cost, and why not both!”
They wanted to hear about similar successful implementations in their market, in particular the time it would take to recoup their investment in the new solution, and the strategic advantages it will provide them after one year or two in production.
To management people, we brought strategic benefits. They could operate the business under a decisioning process that implements the business strategy. Their organization could finally make informed, error-free, and unbiased decisions. And they were insured that the decisions taken were in full compliance to internal policies and industry regulations.
Sparkling Logic is a Silicon Valley company dedicated to helping businesses automate and improve the quality of their operational decisions with a powerful decision management platform, accessible to business analysts and ‘citizen developers.’ Sparkling Logic’s customers include global leaders in financial services, insurance, healthcare, retail, utility, and IoT.
Sparkling Logic SMARTSTM (SMARTS for short) is an all-in-one low-code platform for data-driven decision-making. It unifies authoring, testing, deployment, and maintenance of operational decisions. SMARTS combines business rules with predictive models to create intelligent decisioning systems.
If you envision modernizing or building a credit origination system, an insurance underwriting application, a rating engine, a product configurator, a condition-based maintenance application, or such applications, SMARTS can help. Just contact us or request a free trial.
Sparkling Logic helps businesses automate and improve the quality of their operational decisions with a technology platform that is powerful and simple: SMARTS for short. In this post, we present SMARTS through 10 selected questions and answers.
1) What is SMARTS?
SMARTS is a decision management platform for business analysts and ‘citizen developers’ to author, test, simulate, deploy, run, and change decisions autonomously, without involving developers or IT beyond first installation.
2) Is SMARTS a business rules engine?
SMARTS is more than a business rules engine. It integrates multiple decision technologies into the same platform. SMARTS provides eight execution engines: A decision flow engine to sequence tasks of a business process; a state-machine engine to orchestrate tasks; a rule set engine to sequence decisions; a sequential engine that either fires all or just the first valid decision; a Rete-NT engine for inference; a lookup engine for data search in large datasets; a PMML engine to execute predictive models; and a DMN 1.3 engine to execute decision models. Depending on the problem you have, you may choose one or the other, or even combine them in the same set-up.
3) What are the typical applications for which SMARTS is the best fit?
In the financial, insurance, and healthcare services, SMARTS often won over the competition for origination and underwriting, pricing and rating engines, account management, fraud detection, and collections and recovery. More generally, SMARTS is a good fit when there are a lot of decisions that are data-based, frequently invoked, and likely to change often.
4) What is the difference between authoring business decisions and rules with SMARTS and coding them directly in the final application?
You can code decision logic but you will need detailed specifications from business analysts. This process may take too much time when compared to SMARTS. And once the decision logic is coded, it becomes complicated for business analysts to understand and take control of. SMARTS targets business-critical decision logic that either implements business models, corporate policies or industry directives in a dynamic and continually changing economy. Think of all the financial, insurance, and healthcare regulations since the financial crisis of 2008 and the changes since the coronavirus crisis of 2020. These two crises are typical examples of complex situations where business decisions not only need to be implemented quickly and accurately, but they also need to change dynamically and continuously.
5) Does SMARTS come with a decision design process?
SMARTS not only supports but it also augments the Decision Model and Notation (DMN) standard of the OMG (Object Management Group). DMN models decision dependencies very well, but not decision sequencing, which is also a natural way experts use to describe a complete decision logic. SMARTS addresses both dependency and sequencing through the combination of Pencil, RedPen, and the decision flow.
6) What machine learning models does SMARTS support?
SMARTS supports the execution of 13 machine learning models including classification, linear and logistic regression, support vector machines (SVMs), decision trees, random forests and ensemble learning, clustering, and neural networks. SMARTS uses PMML, the standardized predictive model markup language, to import and execute whatever model your data scientists have built.
7) Does SMARTS integrate with business process management platforms?
Yes, a SMARTS decision service can be natively invoked by a business process like any other service. Also, for decision-centric processes, SMARTS provides an orchestration capability.
8) What is the difference between an RPA tool and SMARTS?
If you think of a process as a sequence of “what to do”, “how to do it”, “do it”, and “report it”, then SMARTS automates the “what to do” and “how to do it” tasks while an RPA tool automates the “do it” and “report it” tasks.
9) Is SMARTS cloud-based?
SMARTS was designed from the ground-up for the cloud. Whether you have chosen to host your application or use our SaaS solution, we provide you with the most modern tools. SMARTS comes in a container, ready to install on your premises, AWS, GCP, Azure, or Aliyun. Choose yours, change your mind, no need to recode to redeploy your application.
10) What makes you unique?
Our motto is “your decisions, our business”. We enjoy nothing more than helping customers implement their most demanding business requirements and technical specifications. Our obsession is not only to have clients satisfied but also to be proud of the system they built. So dare to give us a challenge and we will solve it for you in days, not weeks, or months. Just email us or request a free trial.
In this post, we introduced SMARTS through 10 selected questions and answers. If you have more, feel free to read our blog, sign up for our webinars, or contact us. We would be happy to get back to you very quickly.
Sparkling Logic is a Silicon Valley company dedicated to helping businesses automate and improve the quality of their operational decisions with a powerful decision management platform, accessible to business analysts and ‘citizen developers’. Sparkling Logic’s customers include global leaders in financial services, insurance, healthcare, retail, utility, and IoT.
Sparkling Logic SMARTSTM (SMARTS for short) is a cloud-based, low-code, decision technology platform that unifies authoring, testing, deployment and maintenance of operational decisions. SMARTS combines the highly scalable Rete-NT inference engine, with predictive analytics and machine learning models, and low-code functionality to create intelligent decisioning systems.
This article presents the three software industry trends driving the digital transformation revolution: DevOps, low-code / no-code automation, vertical integration with digital decisioning.
IntroductionThe pandemic changed tech priorities for many people both at work and home making a ‘hybrid’ work a top initiative. Where and how we do the work accelerated the need to improve customer digital experiences and efficiency across work, shopping, and everyday chores.
The data supports this new trend. The independent research firm Omdia compiled over 300 responses from executives at large companies indicated that working away from traditional offices will become the new norm. 58% percent of respondents said they will adopt a hybrid home/work. Even more interesting is that 68% of enterprises believe employee productivity has improved since the move to remote work.
Similarly, adoption of everyday on-line activities such as shopping, banking and entertainment further accelerated the pace of digital transformation. The need for improved applications increased the pressure on companies to relaunch efficient, friendly front-end customer apps with more intuitive UX. The back end now needs to support faster turnaround with the need to automate processes for the new on-line community of users demanding faster, cleaner, and more intelligent offerings.
To respond to this digital transformation, companies are rapidly adopting easy-to-use integrated enterprise software tools to optimize and accelerate development of these efficient digital products.
Several trends like DevOps, Low-code/automation and vertical integrations with integrated digital decisioning have emerged to help enterprises take the digital transformation journey faster and cheaper.
DevOpsDevOps is a software development concept bringing together historically disconnected functions in the lifecycle of the software development. Traditionally, business analysts would define the problem, developers would interpret the concept and build applications, and operations teams would test, report bugs and provide feedback. The disconnect between the functions, silo’d approach created inefficiencies, increased costs and slowed down application releases.
The emergence of integrated tools and processes which integrate this multiple aspect of software development and promote collaboration between these different functions supported growth of the DevOps industry.
In fact, the market data shows that these trends are supported by the investment community and exit activity. According to Venture Beat, in 2Q 2021, Venture funding for global DevOps startups reached $4 billion and the exit activity deal value was dominated by the IPOs of UiPath (robotic process automation) and Confluent, (data / application integration platform).
Low code / no code automationApplication development is also coming closer to non-developers with low/no-code approach and automation.
Software engineering, traditionally owned by IT and software engineers, has always been coveted by other, non-IT stakeholders in the enterprise. In 1991, Powerbuilder introduced a revolutionary concept of a development framework, aiming at democratizing development by allowing non-software professionals to get access to application development. Perhaps ahead of its time with clunky UX, WYSIWYG, Powerbuilder started the revolution of introducing emergence of ‘citizen-developers’, people who originally participated alongside IT in shaping the application and business models but could not code and create the applications themselves. It also introduced data integration with application logic and object-oriented concepts like inheritance and polymorphism and encapsulation, bringing software engineering to the masses.
Fast forward to 2020’s, virtually every enterprise tool platform and enterprise customer have adopted a low-code/no-code approach. The mission is the same as 30 years ago – to provide easy to use, graphical UI/UX, drag and drop concept to application development and allow business analysts, ‘citizen-developers’ and non-software engineers to create, test and even deploy enterprise applications.
Vertical integration with digital decisioningThe perennial challenge of allowing non-developers to create applications is the conundrum of how deep they can develop without coding and to what extent they can customize complex enterprise cloud applications without IT and coding.
To accelerate digital transformation, enterprise software vendors are emerging mostly from the workflow / BPA world, such as Pega and ServiceNow. They are applying a two prong approach – core tool collection and vertical integration. The workflow vendors have developed (or acquired) a collection of point tools in a core-component framework. Those components typically include AI/ML, reporting, workflow, RPA (Robotic Process Automation), case management, rules engine, decision management, knowledge bases, BPA (business process automation) and process orchestration. Those components typically feature common UI and work across a normalized data model and unified architecture.
But that is not enough. To satisfy modern rapid digital transformation needs, in case of fintech enterprise customers (i.e. banks, insurance companies and financial services) also now require pre-built workflow, data and application models. These vertical templates are higher level and more specific, providing out-of-the box, drag/drop solutions like credit card operations, loan management and payment operations. Using the low-code approach, a business analyst can graphically drag/drop pre-defined steps into a loan origination workflow with pre-defined commonly used tasks, created using best practices defined by the ‘centers of excellence’. Companies like UIPath have created a 3rd party marketplace for additional steps and templates created by analysts and consultants. (Those steps could be ‘get customer data’, ‘OCR input form’, ‘scrub customer data’, authorize user’, ‘assess risk profile’ etc.).
Beyond the top level tasks, the functionality ultimately becomes more complex and the sophisticated customer needs powerful decision capabilities to introduce their own business rules and implement proprietary features. The ‘secret-sauce’, which separtes most common steps from proprietary concepts distinguishes top corporations from the competition, requires more sophisticated digital decisioning tools. These digital decisioning tools enable non-developers to customize and manage decision logic, implement AI/ML features, run A/B testing and visualize performance results on training and production data in real time.
To satisfy most common customer base, digital workflow vendors typically provide rudimentary business rules integrated in their low-code platforms and further integrate them with the downstream workflow platforms and vertical ecosystem vendors (i.e. FiServ, Jack Henry, SAP, Salesforce and FIS in banking for example).
The most sophisticated and demanding customers, however, need a more sophisticated set of digital decisioning tools like standalone professional DM platforms. To simplify and visualize this complex decision management, a new generation of low-code digital decision management platforms like Sparkling Logic emerged. These platforms integrate historical business rules engine, data and AI, demystifying machine-learning and providing low-code approach to development and monitoring of application logic performance, continuously as the business logic and training data change and drift.
The pandemic, hybrid work and pervasiveness of the cloud computing have irreversibly changed the software application development. Enterprise customers are seeking and deploying better, faster, more integrated software tools. DevOps integration, low-code, vertical templates, integrated AI and digital decisioning are becoming a new normal while defining the next generation of applications, created not only by software engineers, but by mere mortals across the enterprise.