I D C V E N D O R S P O T L I G H T. C o r t i c o n T e chnologies: A S o l u t i o n t o

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1 I D C V E N D O R S P O T L I G H T C o r t i c o n T e chnologies: A S o l u t i o n t o P e r formance and B u s i n ess Rule Integrity I s s u e s October 2011 Adapted from Worldwide Business Rules Management Systems Forecast and 2010 Vendor Shares by Stephen D. Hendrick, IDC # Sponsored by Corticon Decision management (DM) is now one of the highest growth areas in application development and deployment. Because making decisions is the cornerstone of DM, a business rules management system (BRMS) is viewed as the key "go to" technology for supporting decisioning. As a result, the BRMS market continues to grow at double-digit rates and reached $344 million in The explicit focus that a BRMS has on decisioning means that decision-making needs to be clear, complete, consistent, and correct. From a technology standpoint, this means that BRMS vendors need to ensure the integrity of business rules deployed in their environment. Referential rule integrity (RRI) is not an easy issue to address, but it is a must-have characteristic of any leading BRMS product. Introduction The BRMS market has been gathering momentum over the past several years. This is due in part to the compelling benefits that a BRMS provides in an "on-demand" world, the technological innovation in the BRMS market, and the alignment that a BRMS has with current architectural trends around process automation and process improvement. Service-oriented architecture (SOA) is an important evolutionary change that is occurring in IT. SOA is an important driver because it is perhaps the first time that the industry has found a way to build and integrate software assets in a way that better aligns IT with the needs of the business. Part of the benefit that stems from SOA is due to its standards centricity. However, much of SOA's benefit is a result of its more structured and infrastructural approach to application development. BRMSs are well aligned with SOA due to their exclusive business rule focus, which is one of the six key constructs identified by IDC as critical in building or integrating SOA applications, and their infrastructural support around rule development and deployment. Business process management (BPM) is also an important BRMS driver. This is because BPM, like BRMS, is a model-driven approach to developing and deploying business processes. However, BPM's focus on automating process execution creates a natural symbiotic relationship with business rules, thereby increasing the visibility of business rules and offering BRMS vendors numerous new ways to partner. Another key reason that BRMS continues to grow is the advent of new streamlined BRMS environments that make it easier to build, verify, and implement business rules. This new approach, of which Corticon is a prime example, addresses business rule processing in a more simplified way that is model driven and resolves the most pressing BRMS issues: business rule integrity and performance. The remainder of this document discusses key BRMS market issues, solutions to these issues, and Corticon's approach to BRMS. IDC 1202

2 Definitions Business rules management systems are defined as discrete systems that define, manage, and execute conditional logic in concert with other IT processes and actions. BRMSs are well known for their ability to automatically recognize the interrule relationships that evolve as rules are added or changed, thereby eliminating the need for the careful and complex rule sequencing and conflict resolution that would otherwise be necessary. Benefits An obvious realization when talking about a BRMS is that the rules enable decision making. A company is judged by its actions, and behind every action is a decision, regardless of how simplistic or ordinary. The emphasis over the past five years on process automation has raised the importance of having explicit and identifiable decisions that reside behind every action. The BRMS is an ideal repository for the rules that drive decision making. There are many reasons why this is true: Centralizing business rules enables an organization to create a system of record for its decision making. All good BRMSs provide powerful development and reporting capabilities, which makes it easy for business and IT users to understand what rules are active, what decisions can be made, and how these decisions are made. Besides the clarity that this brings regarding organizational and IT decision making, there are also obvious derivative benefits in satisfying IT and corporate governance requirements. Any advanced BRMS development environment supports aliasing and/or natural language processing. This means that business rules can largely be developed by nontechnical staff. Consequently, a BRMS is able to effectively bridge the gap between the business and IT, helping ensure that the rules and decisions needed by the business are the rules and decisions that are implemented. By maintaining a separate environment that supports decisioning, an organization is able to better evaluate rule interaction and ensure rule consistency. This also makes rule maintenance and management far easier and much faster. On a technical level, the design of a BRMS is consistent with the best practices in application development. This is due to separation of concerns that is achieved from decoupling decisions from data and process, the ease with which a BRMS fits inside SOA, and the complementary match with BPM systems. A BRMS also is the best place to develop and execute complex business rules. This is because some BRMSs provide automated checks for rule completeness and consistency along with impact analysis. Trends Business rule integrity and performance issues exist in the BRMS market because until recently, the most successful approach to business rules processing was based around providing a way to address many-pattern/many-match (MP/MM) problems. An MP/MM problem is the most complex form of pattern matching where many patterns (rules) are evaluated and updated as data elements change. When all of the conditions are met that define a pattern, one or more candidate matches are identified. Multiple candidate matches occur when the pattern is nonspecific. Conflict resolution is then applied to determine what matches are to be executed and potentially in what order. Algorithms to address MP/MM matching perform inferencing (matching) at runtime. The RETE algorithm is the best-known approach to the MP/MM problem. Performance issues, due to the computational intensity of RETE, have led to successive revisions to the RETE algorithm as well as derivative and alternate algorithms. The complexity of the MP/MM problem also has other implications. The MP/MM problem makes it very difficult to statistically analyze a rulebase for rule IDC

3 completeness or consistency because each rule is granted a large measure of independence and autonomy. This imparts a high measure of flexibility in the definition of rules, but at the expense of performance and reliability, because incompleteness and inconsistency in the rulebase can go undetected and lead to undesired matches. If you are interested in an MP/MM BRMS, you should look for one that evaluates for rule completeness and consistency. Some vendors in the BRMS market are choosing to follow a slightly different architectural approach that addresses the single-pattern/many-match (SP/MM) problem. The SP/MM problem is a subset of the MP/MM domain, which significantly reduces architectural complexity. SP/MM problems can be approached in a far more systematic fashion that resolves the performance issues and reliability issues that exist in the MP/MM domain. By constraining the MP/MM domain to a collection of single patterns, each pattern can be fully resolved at design time. Each pattern therefore is factored into a series of paths, which can be compiled. SP/MM patterns are likewise evaluated and updated as data elements change and, just like MP/MM approaches, can result in one or more candidate matches, which are applied based on conflict resolution techniques. Consequently, in SP/MM approaches, no inferencing is performed at runtime, so performance is typically between one and two orders of magnitude faster than that of MP/MM approaches. However, more importantly, the full resolution of each pattern means that all rule intersections are known. The more sophisticated SP/MM products use this ability to fully resolve a pattern to check for and enforce rule completeness and consistency. Enforced rule completeness and consistency ensures that the BRMS will deliver reliable results. This elimination of reliability and integrity issues is a critical capability for the BRMS market. Corticon Corticon enables organizations to make better, faster decisions by automating business rules. Corticon's patented "no coding" rules engine is used by over 450 customers worldwide to automate their most sophisticated decision processes, reducing development and change cycles by 90%. Corticon is a privately held company headquartered in Redwood City, California, with international offices in the United Kingdom, the Netherlands, and Japan and an extensive partner network. The company is recognized as a leading BRMS vendor by industry analysts and thought leaders, and its products are in use today at many of the world's largest financial services, insurance, and ecommerce companies as well as federal and state government organizations, collectively automating millions of decisions per day. Automated decision management with Corticon empowers these organizations to improve productivity and customer service and adapt quickly to changing market conditions. Product Overview Corticon's BRMS is a powerful and easy-to-use rules engine. Unique to Corticon is the process of verifying rules as they are input at design time for logic errors. These logic errors are the basis of RRI problems. Rule ambiguity, inconsistency, and incompleteness are automatically highlighted for users or automatically resolved where understood. This simplifies the rules-building process, reduces the iterative cycles typically associated with creating business rules, and drives complete and consistent rules. Corticon Studio is used to model business rules, and Corticon Server executes the decision services that comprise the modeled business rules. While RETE-based business rule engines perform inferencing at runtime, the decision verification process within Corticon Studio eliminates the need for runtime inferencing in the Corticon Server, significantly increasing performance and efficiency. Moreover, the verification performed during design increases the reliability of the rules by eliminating errors and ambiguities early in the rules-building process. This rule verification and testing is how Corticon addresses rule completeness and consistency concerns in ways that some RETE-based products do not. Corticon Server is built entirely upon a service-oriented architecture, and all 2011 IDC 3

4 decisions are stored as services and are available through open standards. Product specifics are provided in the following sections. Corticon Studio Corticon Studio's model-driven approach enables business analysts and policy makers those who best understand the dynamics forcing change within the organization to easily model and deploy business rules without the need for traditional programming. Corticon Studio was designed specifically for business agility, providing an out-of-the-box Excel-like modeling environment to create, analyze, test, and verify rules. Corticon Studio also guarantees accurate results with unique rule integrity features. Corticon Studio provides capabilities to build a rules Vocabulary and for modeling the rules. Business rules are created by applying conditional logic to entities to trigger actions. Consequently, a Vocabulary that defines these entities as well as their attributes and relationship to other entities is critical. The purpose of Corticon's Business Rules Modeling Studio is to first define a Vocabulary, then create business rules around this Vocabulary, and then analyze the business rules to ensure they are consistent and complete. More complex groups of rules can be organized into independent, reusable units called "Rulesheets" that can be orchestrated within a "Ruleflow" process metaphor. Once the business rules are defined and analyzed, Test Scenarios can be built to execute the rules, thus ensuring the determination of the correct business results. In addition, Corticon Studio can generate reports of all assets (Vocabularies, Rulesheets, Ruleflows, and Test Scenarios) in XML or HTML. Defining a Vocabulary To model rules within Corticon, a user must first have a Vocabulary to define the entities and attributes of the business decision being modeled. A Vocabulary defines the nouns of the rules language and defines a schema for sending data to and from a Corticon decision service. The Vocabulary provides an abstracted view containing only information relevant to the rule creation process. A Vocabulary in Corticon may be created from scratch or from an existing data model. Creating a Vocabulary from an existing data model can greatly simplify the rule modeling process. Corticon Studio can accept any OMG-compliant XMI data model, which is a common output option of most modeling and architectural tools. In addition, Corticon can automatically generate Vocabularies from database schemas, XML schemas, or Java classes. Or, via an API, a Vocabulary could be generated from other formats. Business Rule Modeling Most BRMS products typically use decision trees, decision tables, or inferencing, or a combination of these options, for expressing and/or evaluating business rules. Corticon has elected to use a combination of an extended decision table metaphor and design time inferencing. While decision tables account for all condition/value pairs for the entities and are complete and reliable, they become impractical because they don't scale well. Corticon has implemented features within Studio to offset this drawback, extending the decision table as a metaphor to make it significantly more expressive. Corticon approaches the development of a rulebase by focusing on a particular decision, problem, or other manageable unit of SP/MM work. This is created as a Rulesheet and deployed as a decision service. More complex problems can be modeled as a number of Rulesheets orchestrated via a Ruleflow, which is a BPMN-compliant process diagram. This approach can make it easier to check and resolve problems by segmenting the rules into smaller scale clusters and providing automated techniques to check for completeness and consistency. Corticon's SP/MM design point means that rule patterns are fully resolved at design time, which has the advantage of removing any ambiguity in or need for procedural control over rule execution. Business Modeler focuses on the business decisions themselves, not on how those decisions are executed. Users are empowered to use their expertise in designing rules for decisions in familiar terminology they understand IDC

5 Completeness and Consistency Checking Once rules are entered into the decision table, they are analyzed for completeness and consistency (eliminating ambiguity). Completeness in this context means that the Rulesheet addresses all possible data scenarios. While a rule may seem clear to the user entering it, it may not take into consideration all scenarios that may occur. Ambiguity (inconsistency) means that the rules may address scenarios in a conflicting manner. Each of these analyses is selected from a drop-down window and automatically performed by Studio. Once the Check for Ambiguities option has been executed, columns are highlighted in red to identify where problems exist between columns or between rules. Analyzing and identifying ambiguity and completeness, checking for unintended logical loops, and testing rules are critical aspects of building a reliable decisioning system. Conducting these verifications as rules are added to the rulebase makes it a more manageable process and ensures the quality of the rulebase as it continues to evolve. By incorporating these capabilities into its BRMS, Corticon addresses IDC-defined requirements for completeness and consistency. While there is always a human factor involved in building business rules that are complete and consistent, Corticon is one of the few vendors that automate the process of identifying where rules are incomplete and what ambiguities need to be resolved. This is absolutely key in helping business analysts find and resolve incomplete and inconsistent rules, which is how they address what IDC terms "referential rule integrity." Corticon's approach is interesting on a variety of levels. Architecturally, Corticon is designed to solve an SP/MM situation. By choosing to address just the SP/MM domain, Corticon can dispense with runtime inferencing,which renders the performance issue moot. Corticon's SP/MM focus means that it is able to perform only forward-chaining, but it's hard to see how this really matters to the general IT market, where virtually all of the use cases are oriented around forward-chaining. More importantly, this approach also enables Corticon to solve the RRI problem. Corticon Server Corticon Server is the "no coding" rules engine component of Corticon's BRMS. It processes the rules that have been modeled, verified, and tested in Corticon Studio, ensuring reliable results and delivering fast performance. Corticon's business rule engine fits naturally in today's service-oriented architectures, deploying as a service, and leverages the enterprise-class performance, scalability, and high-availability features of today's application servers. Corticon Server is available in either a native Java or a native.net version. The same business rule models, created in Corticon Studio, can be deployed into one or more J2EE and/or Microsoft.NET execution environments running Corticon Server. Most MP/MM rule engines analyze rules during execution. This means significant processing is taking place when other systems are looking for an answer from the rules system. The traditional and most well-known pattern-matching algorithm to efficiently process and execute rules is RETE. The RETE algorithm shows close to linear scalability when increasing the number of rules but degrades when increasing the number of data elements. This is commonly referred to as the "RETE wall" and has resulted in improved versions of the algorithm (RETE II, III, and Plus) to help address this issue. These improvements, while improving performance about one order of magnitude, still do not resolve the underlying architectural issue for the most complex data models. Corticon's approach sidesteps this entire issue, which is useful for system development efforts that have the potential to scale significantly. Corticon Server is built on a service-oriented architecture. Users have a choice of deployment architectures based upon their individual needs. The server offers high performance through an optimized compiler, and because inferencing is analyzed at design time, the engine does not have to perform in-depth analysis at runtime. It is a stateless environment, and as such, state is persisted through the message payloads. It is possible to distribute and run replicas of the Corticon Server 2011 IDC 5

6 across multiple CPUs to support load balancing. In addition, the server can also run multiple copies of a decision service and execute them concurrently in a multithreaded environment. The server supports warm, cold, or hot rules deployment and is inherently reliable due to design time completeness and consistency checking. Challenges Corticon's SP/MM architectural approach yields benefits from the standpoint of complex data scalability. This approach also helps simplify rule definition by focusing it around a single pattern. Some users will find this added simplicity in rule definition a valuable feature because it reduces the number of rule intersections (gaps and overlaps), making static analysis and resolution of completeness and consistency issues in the rulebase for each Rulesheet easier to address. The downside is that rule definition must be approached in a more thoughtful and organized manner with foresight into how rules should be partitioned by Rulesheet. Conclusion The BRMS market is expected to grow at double-digit rates over the forecast period. Revenue is expected to reach almost $600 million by This suggests that the BRMS market is becoming a key component in the decision management arena. Corticon is one of a small number of leading BRMS vendors that have developed a breakthrough technology in the BRMS market and address the RRI issue as well. Performance and reliability issues are longstanding issues in the BRMS market, and therefore the advent of a BRMS that addresses both these issues in a compelling way is exciting to see. A B O U T T H I S P U B L I C A T I ON This publication was produced by IDC Go-to-Market Services. The opinion, analysis, and research results presented herein are drawn from more detailed research and analysis independently conducted and published by IDC, unless specific vendor sponsorship is noted. IDC Go-to-Market Services makes IDC content available in a wide range of formats for distribution by various companies. A license to distribute IDC content does not imply endorsement of or opinion about the licensee. C O P Y R I G H T A N D R E S T R I C T I O N S Any IDC information or reference to IDC that is to be used in advertising, press releases, or promotional materials requires prior written approval from IDC. For permission requests, contact the GMS information line at or gms@idc.com. Translation and/or localization of this document requires an additional license from IDC. For more information on IDC, visit For more information on IDC GMS, visit Global Headquarters: 5 Speen Street Framingham, MA USA P F IDC