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What our customers say about SMARTS

What our customers say about SMARTS

You are about to modernize or develop a new automatic decision-making application, based on data, knowledge, or a combination of both. You wonder whether our SMARTS platform meets your business needs and technical specifications. Nothing is better proof of a product’s superiority than the testimonials of customers. So, we have selected some customers here so you can see why they chose SMARTS as their decision management solution.

Equifax, consumer credit reporting

Equifax is a global data, analytics, and technology company that serves financial institutions, corporations, government agencies, and individuals with enriched data and executable insights. These insights are typically derived from many data sources including financial, telecommunications and utility payments, employment, and income data.

Equifax chose SMARTS as a core part of the Equifax InterConnect platform. Credit and risk analysts, both at Equifax and their customers, can seamlessly import data, capture decision logic, A/B test and analyze how the decisions apply to each transaction, and measure the collective impact of making changes to decisions. Business users and business analysts, both at Equifax and their customers, can autonomously make changes to policy rules.

“SMARTS is at the heart of our InterConnect platform. It has helped us quickly enter an era where the credit process must be smooth, automated and optimized for lenders and consumers. SMARTS’ all-in-one approach to authoring, testing and deploying business rules into a sophisticated yet simple product appealed to us from the start. Since then, we have been very satisfied with the use we make of it on a daily basis” — Deepesh Mohandas, Vice President, Global Product Management, Decisioning Platforms.

Learn more about SMARTS at Equifax.

NICE Actimize, suspicious financial activity monitoring

NICE Actimize is the largest and broadest provider of financial crime, risk, and compliance solutions for regional and global financial institutions, as well as government regulators. Consistently ranked as number one in the space, NICE Actimize experts apply innovative technology to protect institutions and safeguard consumers’ and investors’ assets by identifying financial crime, preventing fraud, and providing regulatory compliance.

Integrated with NICE Actimize’s platform, SMARTS supports financial institution customers by making more rapid decisions on financial crime strategies and providing the ability to view the overall impact across all NICE Actimize analytics. This capability allows X-Sight customers to make more informed decisions while maximizing financial crime coverage and controlling costs.  

“This technology partnership delivers our X-Sight customers more rapid development and deployment of financial crime management strategies across the broader NICE Actimize analytics ecosystem” — Craig Costigan, CEO.

Learn more about SMARTS at NICE Actimize.

Percayso Inform, insurance intelligence

Percayso Inform is an insurance intelligence provider whose services go beyond traditional data enrichment, providing unique, real-time solutions at all stages of the insurance lifecycle and delivers unrivaled insight into insurance customers, risk, and fraud.

Powered by SMARTS, Percayso Inform Manager allows insurance providers of all shapes and sizes from start-ups to global insurance businesses across personal and commercial lines to build, adapt and optimize their own data enrichment, rating, and intelligence strategies dynamically and intuitively. It enables high volume data ingestion, rules configuration, operational and strategic decision management as well as a string of valuable features such as reporting, dashboards, champion challenger, data manipulation and more.

“Sparkling Logic stood out from the crowd. The functionality, configurability and ease of use of SMARTS ticked all our boxes but what really impressed us was the genuine desire by their team to create a true partnership and build a foundation from which we could both grow together” — Richard Tomlinson, Managing Director.

Learn more about SMARTS at Percayso Inform.

Enova Decisions, data analytics and decision management

Enova Decisions is an analytics and decision management technology company that was formed in 2016 to enable businesses to automate and optimize operational decisions through data, AI, and the cloud- in real-time and at scale.

“Leveraging technologies like Sparkling Logic in our cloud service allows our clients to oversee the fine details of the decision algorithm without feeling overburdened by the complexity of what they’re designing” — Sean Naismith, Head of Analytics Services at the time.

Learn more about SMARTS at Enova Decisions.

LTCG, insurance business processing

LTCG is a leading provider of business process outsourcing for the insurance industry. The largest insurers rely on our unparalleled expertise to help manage their complex long-term care portfolios and maximize financial performance.

LTCG evaluated tool and platform options and selected SMARTS as the decision engine for their claims adjudication system. They developed and implemented the new system and have since extended their use of SMARTS to support additional business processes.

“Thanks to SMARTS, we were able to discover, test, and deploy automated claims decision logic in under six months” — Kyle Korzenowski, CIO at the time.

Learn more about SMARTS at LTCG.

ABT, power management

ABT Power Management, now part of Concentric, furnishes, engineers, installs, and services industrial batteries and charging systems and is a recognized industry leader in material handling power management.

“Now, using SMARTS, we have achieved near real time analysis of this [sensor] data and are able to respond immediately to conditions that need attention. SMARTS’ interface is easy and intuitive enough to allow our engineering staff to create and maintain the rules themselves” — Mike Shemancik, CIO at the time.

Learn more about SMARTS at ABT.

First Rate, wealth management

First Rate is the UK’s largest supplier of foreign currency and a top 5 currency wholesaler globally. They are one of the foremost FX experts in the industry, with a multi-billion-pound wholesale business and over 10 years’ trusted experience providing tailor-made travel money solutions for companies in the finance, travel, and retail sectors.

“We chose SMARTS for its comprehensive decision management environment with out-of-the-box integration of business rules, and predictive analytics, and focus on decision improvement” — Nick Collins, Head of Business Solutions at the time.

Learn more about SMARTS at First Rate.

Onlife Health, patient-centric care management

Onlife Health, a GuideWell company, brings simplicity to population health and wellness, connecting and integrating people, technology, and benefit design through a user-friendly engagement platform, guiding members on the “next right thing to do” in their healthcare journey.

“We are able to easily change our decisions as business needs dictate and deploy these changes without going through the full software change process.” — David Jarmoluk, Vice President of Enterprise Solutions at the time.

Learn more about SMARTS at Onlife Health.

Do you want to learn more or test SMARTS yourself? Just contact us or request a free trial.


Sparkling Logic is a company at the forefront of technological innovation in decision management. We help businesses automate their operational decisions with a powerful decision management platform, designed for business analysts first.

Sparkling Logic SMARTSTM (SMARTS for short) is a decision management platform that enables creating, testing, deploying, and improving automated data-based decisions in an integrated easy-to-use environment.

SMARTS as regulatory compliance technology

SMARTS as regulatory compliance technology

So far, we’ve covered how to use SMARTS for decision management, micro-calculation, and data transformation. In this blog post, we show how you can use it to implement regulatory technology (regtech).


Regulations, from Basel rules on bank capital requirement to Sarbanes-Oxley Act on corporate financial statements, to MiFID on pre- and post-trade transparency requirements across EU financial markets, have forced regulated companies to develop processes to find, assess and mitigate risks. To comply, investment firms, retail bankers, and insurance companies have turned to regtech for help.

Regtech is an acronym for governance, risk, and compliance management technologies in companies, more particularly those working in highly regulated industries such as financial services, insurance, and healthcare. They allow the implementation of legal requirements in the nervous system of companies, in front-, middle- and/or back-office.

All regulations being prescriptive, it was natural that rule-based systems were among the first technologies used, with varying degrees of success which we will detail here, before showing how SMARTS overcame them.

SMARTS as regulatory compliance technology

Your data is uploaded and transformed in the same tool
Highly regulated companies must deal with continuous growth in transaction volumes and a massive accumulation of data that they must ingest or produce daily while constantly complying with ongoing regulations. They could do it, but they had to use other tools besides rules-based systems and they either had to connect them or transfer the data back and forth. With SMARTS, they don’t have to, since it allows data to be uploaded and transformed into rules or calculations in the same tool.

Your data is turned into insights and your insights into decisions
Before the widespread use of big data and analytics, investment bankers relied on complex analysis of information using statistical learning. Today, the entire financial services and insurance industry has integrated advanced data analytics into its artillery to detect market signals and predict market trends. The most advanced want not only to transform data into insights, but these insights into decisions. SMARTS was one of the only tools if not the only tool to offer an integrated solution to transform such companies into lifelong learning organizations where data helps find opportunities and risks, machine learning turns that data into knowledge and rules transforms this knowledge into decisions, thereby closing the virtuous circle that data promises.

You limit your risk for noise, errors, and biases
Since the advent of data, regulators have been closely monitoring the bias issues of automated decision-making systems, particularly those that rely solely on data and use machine learning to calculate scores and then decide instead of a human. In SMARTS, users implement decisions in the form of business rules, decision trees, decision tables, decision flows, and lookup models. All these intuitive representations make decisioning self-explainable so that they can test decisions individually as well as collectively. So, at any time, they can check potential noise and errors before they translate into biases.

Your data and transactions are tracked in real-time
A key need of the financial services industry is real-time responsiveness to suspicious events such as unusual transactions that may show fraud, money laundering, insider trading, or may not be unusual in themselves but nevertheless exceptional in relation to other transactions before or after. Based on their experience in the earlier generation of decision management systems, the founders of Sparkling Logic decided to integrate real-time decision analysis from the ideation of SMARTS. The product has always integrated a dashboard that tracks data and transactions so that the user can react by changing rules in real time.

You react very quickly before an error, an anomaly, or a fraud spreads
Companies must make thousands of complex risky decisions – monetary, reputational, and legal risks. For example, in every decision they make, there are tiered combinations of terms and conditions, legal constraints, eligibility criteria, and levels of risk involved. Rule-based systems allowed them to implement these decisions in the form of tables or decision trees, or rules, but at the expense of side effects on the business. With SMARTS, they graphically define KPIs and drag and drop them into a dashboard to visually check the impact of each decision or group of decisions on business performance. Users can also set thresholds and define patterns which if reached will trigger notifications and alerts. This way, the users will be able to react very quickly before an error, an anomaly, or a fraud spreads and results in enormous damage.

Your system is easy to maintain and upgrade
Prior to the emergence of regtech as a hot technology, highly regulated companies used rules engines to encode the directive logic of laws, regulations, and internal policies. Additionally, they could implement complicated decisions with tens of thousands or more if-then rules. All went well until they discovered that, like any hard-coded software, rule-based systems could be complex to maintain. With SMARTS, they don’t code and hope the code is correct. They create, test, deploy, run, monitor, and change graphically through web forms and point-and-click. Therefore, systems developed with SMARTS are easy to maintain and upgrade.


The SMARTS is not strictly speaking regtech in the sense that it does not come with all the code of financial and insurance regulations, but it allows them to be implemented quickly and explicitly in the form of rules, trees or graphs. This makes the code easier to change if regulations change as they often do, such as Basel which is in its third version and MiFID in its second version.

SMARTS not only eases the implementation of governance, risk and compliance rules, but it also facilitates their monitoring in real-time. SMARTS not only eases the implementation of governance, risk and compliance rules, but it also facilitates their monitoring. KPIs, dashboards and metrics were fundamental from the start of the product and not an afterthought once the product was released.

If you envision modernizing the implementation of a regulation, be it Basel, Sarbanes-Oxley, MiFID, GDPR, or any other regulation, SMARTS can help. Just contact us or request a free trial.


Sparkling Logic is a company at the forefront of technological innovation in decision management. We help businesses automate their operational decisions with a powerful decision management platform, designed for business analysts first.

Our motto is “your decisions, our business.” Using SMARTS, organizations have automated complex decisions in days, not weeks, or months. Our mission is to enable customers to implement the most demanding decisioning requirements and to easily maintain and improve them over time.

Sparkling Logic SMARTSTM (SMARTS for short) is a decision management platform that enables creating, testing, deploying, and improving automated data-based decisions in an integrated easy-to-use environment.

Unlike other tools that focus solely on the authoring and maintenance of business rules, SMARTS is decision-centric and focuses on measuring and improving business outcomes in the context in which our clients work, especially with complex regulations. Major enterprise customers like Equifax, First American, SwissRE, Centene, and NICE Actimize integrate SMARTS in their core systems.

Decision Management Systems: What Are They and When to Use Them?

Decision Management Systems:  What Are They and When to Use Them?
The purpose of this blog post is to succinctly introduce decision management systems for those who are new to the field. First, I present what decision management is, then the technologies that make it up. I also present where they are used and what they bring to the companies that use them.

What is decision management?

There are two types of decision-making technologies. The first are descriptive in that they implement how people make choices among alternatives based on their beliefs and preferences. Think of a doctor deciding a treatment following a diagnosis or a trader buying an asset following a predictive model. The second are normative in that they implement regulations, policies, or strategies regardless of the beliefs or preferences of those who follow the decisions. Think of a loan officer deciding based on an applicant’s repayment history or an insurer calculating the premium an applicant should pay based on the applicant’s medical condition.

There is no single definition that differentiates the two technologies. You have heard of knowledge-based systems, expert systems or reinforcement learning for the former technologies and decision tables, decision trees or business rules for the latter. But there is a consensus to name the second type of technologies decision management systems. So, when you hear or read someone referring to decision management, think of prescriptive methods, technologies, products, and systems implementing formal laws, industry regulations, company policies, and business strategies.

What are the underlying technologies?

Often decision management systems are confused with business rule engines, but they are more than that. Behind the terminology of decision management systems hide multiple technologies. The simplest are decision tables, trees, and graphs. The most sophisticated combine rules and predictive models. If we take the example of SMARTS, it integrates eight decision engines into the same platform. Depending on the problem at hand, one may choose one or the other, or even combine them in the same set-up.

Also, the users of modern decision management systems are not IT people anymore but businesspeople instead. So, they come with features that allow non-specialists to use them without IT intervention. With modern decision management systems, IT only takes care of the first installations and configurations, the systems come with everything necessary to ensure the governance and security of the applications developed as well as the ease of integrating them into the corporate IT architecture. If we take the example of SMARTS again, it comes with an easy-to-use graphical authoring interface, pre-deployment rule testing, rule repository with version control and rollback, large-scale simulation, real-time decision performance monitoring, and much more.

Where decision management systems are most used?

Like any technology, decision management systems are not a one-size-fits-all solution for every decision problem. They are not suitable for long-term or midterm slow decisions that companies make once a year or a quarter. In these cases, optimization technologies are more used. They are not also suitable for cases with uncertainty and where probabilistic technologies such as probabilistic graphical models are more used.

Decision management systems are best suited when there is a substantial number of decisions and calculations that are often nested, often invoked, and likely to change often. Therefore, one must consider decision management systems for the operational and day-to-day decisions that companies make in the thousands and sometimes millions in a single day. We find these cases in banking for credit risk assessment, in insurance for premium calculation and even in retail for product configuration.

Although not dedicated to finance, insurance and healthcare, customers of SMARTS have widely used it for loan origination, risk management, fraud detection and money laundering prevention. These are typically cases where organizations make decisions and calculations thousands and sometimes million times a day and may change based on the market dynamics or global economy, or updates to regulations or business strategy.

What are the key benefits of using decision management systems?

Decision management systems come with two critical benefits. As decisions are explicit, they make it possible to understand and explain the decisions implemented so that one can change them more easily when a new situation requires it. They also reduce the risk of errors and biases met in customer-facing applications, such as recommendation, credit, or insurance systems based solely on machine learning.

Key takeaways

  • There are two sets of decision-making technologies. The first is descriptive. The second is prescriptive. Decision management systems are descriptive in that they implement formal laws, industry regulations, company policies, or business strategies.
  • Decision management systems are best suited when there are thousands or millions of decisions and calculations that are often nested, often invoked, and likely to change often.
  • The power of modern decision management systems lies less in the engines but more in the features surrounding them to enable businesspeople take full control of the decisioning process without heavy IT intervention beyond first installation and default configuration.
  • Decision management systems have two key benefits. They ease the integration of changes in regulations, policies, and strategies. They also reduce errors and biases in customer-facing applications.

Where to look for further information?

We write regularly about decision management systems and SMARTS. You can find quite a bit of information on our blog and webinars. You can also download our white paper, request a demo of SMARTS, or try it.


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.

Hassan Lâasri is a data consultant and interim executive, now leading marketing for Sparkling Logic. You can reach him at

Noise reduction in digital decisioning with Sparkling Logic SMARTS

noise-digital-decisioning-explicit-decisions-dashboards-analyticsIn this post, we present how to deal with the problem of noise, which is both a source of errors and biases in digital decision-making in organizations, through explicit decision rules, dashboards, and analytics. To illustrate our point, we use the example of the Sparkling Logic SMARTS decision management platform.

Noise in organizations’ decisioning and what to do about it

In an interview with McKinsey, Olivier Sibony, one of the renowned experts in decisioning, recommends algorithms, rules, or artificial intelligence to solve the problem of noise, a generator of errors and biases in decisioning in organizations. This recommendation resonates with our vision of automating decisioning — not all of the decisioning but the operational decisions that organizations make by thousands and sometimes millions per day. Think credit origination, claim processing, fraud detection, emergency routing, and so on.

In our vision, one of the best ways to reduce noise, and therefore errors and biases, is to make decisions explicit (like the rules of laws) so that those who implement the decisions can test them out, one at a time or in groups, and visualize their outcomes in dashboards. Designers must be able to analyze the consequences of decisions on the organization before putting them into production.

Noise reduction with explicit decision rules, dashboards, and analytics

Our SMARTS decisioning platform helps organizations make their operational decisions explicit, so that they can be tested and simulated before implementation, reducing biases that could be a failure to comply with industry regulations, a deviation from organizational policies, or a source of an applicant disqualification. The consequences of biases could be high in terms of image or fees, and even tremendous for certain sensitive industries such as financial, insurance, and healthcare services.

In SMARTS, business users (credit analysts, underwriters, call center professionals, fraud specialists, product marketers, etc.) express decisions in the form of business rules, decision trees, decision tables, decision flows, lookup models, and other intuitive representations that make decisioning self-explainable so that they can test decisions individually as well as collectively. So, at any time, they can check potential noise, errors, and biases before they translate into harmful consequences for the organization.

In addition to making development of decisioning explicit, SMARTS also comes with built-in dashboards to assess alternative decision strategies and measure the quality of performance at all stages of the lifecycle of decisions. By design, SMARTS focuses the decision automation effort on tangible objectives, measured by Key Performance Indicators (KPIs). Users define multiple KPIs through graphical interactions and simple, yet powerful formulas. As they capture decision logic, simply dragging and dropping any attribute into the dashboard pane automatically creates reports. Moreover, they can customize these distributions, aggregations, and/or rule metrics, as well as the charts to view the results in the dashboard.

During the testing phase, the users have access to SMARTS’ built-in map-reduce-based simulation capability to measure these metrics against large samples of data and transactions. Doing so, they can estimate the KPIs for impact analysis before the actual deployment. And all of this testing work does not require IT to code these metrics, because they are transparently translated by SMARTS.

And once the decisioning application is deployed, the users have access to SMARTS’ real-time decision analytics, a kind of cockpit for them to monitor the application, make the necessary changes, without stopping the decisioning application. SMARTS platform automatically displays KPI metrics over time or in a time window. The platform also generates notifications and alerts when some of the thresholds users have defined are crossed or certain patterns are detected. Notifications and alerts can be pushed by email, SMS, or generate a ticket in the organization’s incident management system.

Rather than being a blackbox, SMARTS makes decisioning explicit so that the users who developed it can easily explain it to those who will operate it. Moreover, the latter can adjust the decision making so that biases can be quickly detected and corrected, without putting the organization at risk for violating legal constraints, eligibility criteria, or consumer rights.
So, if you are planning to build a noise-free, error-free, and bias-free decisioning application, SMARTS can help. The Sparkling Logic team enjoys nothing more than helping customers implement their most demanding business requirements and technical specifications. Our obsession is not only to have them satisfied, but also proud of the system they build. We helped companies to build flaw-proof, data-tested, and scalable applications for loan origination, claims processing, credit risk assessment, or even fraud detection and response. 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.


Sparkling Logic is a Silicon Valley company dedicated to helping businesses automate and improve the quality of their operational decisions with a powerful digital decisioning 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, AI-powered business decision management 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.

Hassan Lâasri is a data strategy consultant, now leading marketing for Sparkling Logic. You can reach him at

Capturing Business Rules for Medical Treatment Recommendation

Our friend Jacob contributed a sample of medical rules to the DMN (Decision Model Notation) standardization effort at OMG.  He encouraged me to show how those business rules would look like in our Sparkling Logic SMARTS Decision Management tool.

In this demo, you will see how I created the entire project from scratch, in a business-user-friendly environment, leveraging heavily the use cases he gave me.


RedPenTM is a patent-pending approach to capturing and updating business rules in the context of data.  Graffiti on the use cases turn into business rules automagically!

Thanks again Jacob for allowing us to demo your project!

BBC 2011 – Business Rules for Cancer

healthcareAlthough Healthcare is a perfect fit for Business Rules technology, the providers have been late to adopt the technology.  We have seen many healthcare insurance companies use rules for eligibility or claims processing, but providers are lagging.  I was delighted to attend a session at BBC on Cancer Care.

Michael Katz, BS/MBA at International Myeloma Foundation, gave us a heartbreaking overview of the disease…  incurable but treatable.

The project focused on providing timely information to diagnosed patients healthcare providers.  The solution is available on the internet, with an iPad client available.

Michael shared a demo of the rules they created to detect anemia or bone issues for example.

The iPad application interprets the input data (gender, serotonin level, etc.) by invoking the rules running in a web service.

What’s next?

Nurses have written a 60-page survivor care plan, which they are translating into business rules now.

Similarly, they are translating a 10-step guide for the newly diagnosed (get the correct diagnosis, tests you really need, initial treatment options, supportive care…).

How Kaiser Innovates

A little while ago, I enjoyed reading the trip reports that both Jim Sinur and Elise Olding published on the Gartner blog about innovation at Kaiser Permanente.  Institutionalizing innovation?  This is just the kind of thing that picks my interest.  I could not pass on the opportunity to do that tour as well.  I signed Carlos and I up for a visit of the Sidney R. Garfield Health Care Innovation Center.

Kaiser Permanente - Garfield Healthcare Innovation CenterI also recommend the tour if you happen to be in California but plan ahead as they fill up very quickly.  Our guide was very knowledgeable as well and could give us some “techie” nuggets knowing we were on the IT side.  They combine 3 main aspects: Facilities, Patient Care and IT.  So you could request a guide with any of those specialties.  Isn’t that cool?

Jim described the process innovation that Kaiser implemented very successfully to reduce drug administration errors.  It is so ridiculously simple it is impressive.  It is often the case that the best solutions are actually very simple.  It was interesting that the environment allowed them to think outside the box and focus on the key issues to address.  With the in-situ brainstorming involving all stakeholders, they have been able to come up with an innovative solution to the problem and to test it.  They literally tested out several sashes once they settled on the idea.

I was intrigued by their robotic initiatives.  Having robots deliver bedding throughout the hospital feels a like Start-Trek-ish and cool.  The future is being tested over there though.  They finish the tour with the room of the future.  The trend to simplification continues there of course, bringing tablet-like devices at reach in replacement for many devices they use today.  With the Cloud and all the modern technology, it becomes less of a stretch to consider digital information exchange ver seamlessly from iPad to television to support interactive discussions between the healthcare provider and the patient.  Information will have to flow seamlessly to the home too, for better support and integration of wellness programs that lower “Back to the ER” statistics.

We only talked about Gamification in the context of nurse training, to simulate birth delivery, but you can tell from their website that Gamification is one important focus they experiment with.

My personal take-away was the impressive results they achieved by testing out their new processes or solutions in “reality”.  They have rooms that are designed exactly as real hospital rooms (although they felt much bigger than the room I was in for my son’s delivery).  They try, try and try again.  They iterate in the context of a real-life situation.  They observe; they measure; they assess.  With this use-case-driven approach, they have been able to correct or abandon ideas that looked perfect on paper — they call them their “successful failures”.  It saved them millions of dollars or more.  Our guide pointed out to a few architecture issues that may have been overlooked without the simulation.

That is an interesting parallel with the use-case-driven approach we are evangelizing.  In Decision Management, eliciting and refining business rules in the context of data leads to similar outcomes:

  • Detection of “successful failures”: decisioning that sounds good on paper but that leads to poor business results
  • Collaborative refinement: talking in the abstract can lead to misunderstanding and misalignment; when the discussion is concrete about a specific case, stakeholders can be more precise on their comments and contributions, accelerating the path to the “best” solution

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