James Taylor is the CEO of Decision Management Solutions. He has over 20 years of experience in software development. He discusses how smarter systems must make more operational decisions using business rules, data mining, predictive analytics, and optimization. However, the design tools and methodology for operational decision making are currently lacking.
In this webinar recording, James Taylor, CEO of Decision Management Solutions and Claye Greene, Managing Director of Government Solutions Provider TechBlue share learnings and best practices from their extensive experience helping clients modernize their legacy systems with the targeted decision management approach. You will learn why you don’t need to modernize the whole application, why focusing on business rules is not enough; decision management is the essential ingredient and how to use decision modeling to identify and scope targeted legacy modernization efforts.
Many organizations' agility and responsiveness is hamstrung by their legacy systems. Replacing them wholesale is impossible but the constraint they impose on the business is unacceptable. In this session James Taylor, CEO of Decision Management Solutions, will show how you can use Decision Management and business rules to avoid replacing the whole application while still maximizing agility and improving business alignment.
What you will learn:
How decision components are often the highest change, most difficult to maintain pieces of legacy applications
How Decision Management builds on SOA by externalizing decisions from legacy systems
How a business rules management system dramatically decreases maintenance costs
Why modernizing this way improves business alignment and agility
Webinar recording available at:
https://decisionmanagement.omnovia.com/archives/71756
The Decision Management Manifesto lays out key principles of Decision Management - why decisions are central to your requirements process, why it makes sense to explicitly design decisions before applying technology. Using real world projects this webinar explains the rationale for each part of the manifesto and shows the value it can bring to your projects now and in the future.
Decision management and business rules management systems are the ideal platform for an agile and cost-effective compliance approach. In regulated industries like financial services, leading companies are building compliance into every process and system with consistency and transparency across the entire organization and with the agility to meet ever more challenging deadlines. Companies that fail to do so incur huge costs with manual checks and balances and risk significant fines.
In this webinar James Taylor, CEO of Decision Management Solutions and Jan Purchase, Director and Founder of Investment Banking Specialists Lux Magi, share know-how and best practices from their extensive experience of helping clients implement decision management and business rules management systems to conquer complexity, improve agility, lower costs and measure ongoing effectiveness in financial compliance.
The webinar includes illustrations of how the decision management approach has been applied in compliance projects and a walkthrough of real decision model from one of these.
Business analysts know that modeling business processes, rather than writing about them, defines them more accurately. Business process models make it easier to validate requirements, easier to see opportunities for improvement and easier to manage the process once it is implemented. Replacing traditional specifications with logical business process models based on standard notations like BPMN improves requirements and increases the likelihood of project success.
Yet over-complex processes are common. Complex process models make it harder to engage business owners and reduce the manageability of implementations. One of the prime causes of over-complex processes is the inclusion of decision-making in process designs. Business analysts that identify the decisions in their processes and model them separately – not part of the process but supporting it – find they can simplify process designs, increase agility and bring business users and IT into better alignment. With the publication of a new standard notation - OMG's Decision Model and Notation - and the inclusion of decision modeling in the BABOK, it's time for business analysts to improve their process models by modeling decisions.
Key learning points:
Decisions are central to straight through processing, process innovation and process effectiveness.
Process models obscure decision-making and become over-complex when it is embedded
A standards-based approach to decision modeling is a key technique for process analysts
Mainframe Assessment with Modern Systems' Portfolio Analysis ServicesModern Systems
Legacy systems have passed through many hands over many years, often without proper documentation of features or functional relationships. The most common issue with modernizing a system that very few people understand is that planning for and understanding the breadth and potential pitfalls of a project is virtually impossible without a lot of help. Undergoing a mainframe assessment using Modern Systems' Portfolio Analysis services can significantly reduce risk, cost, and project timelines.
A 2013 survey of IT leaders in the US insurance industry by Gartner reflects just how difficult planning modernizations can be.
- Only 42% of respondents said their modernization projects were completed within originally planned budget.
- Just 34% of the modernization attempts covered the originally planned scope, leaving a whopping 66% of these firms victims of dreaded and out of control scope creep.
- What’s worse, only 18% of respondents completed these projects within their originally planned timeframe.
In other words, modernization is a brutal undertaking. In order to develop well-designed applications from legacy environments, powerful tools and expertise are required to analyze the legacy system and aid in generating new programs that are architecturally sound and utilize modern design methods.
The data and reports gathered in a Modern Systems Portfolio Analysis mainframe assessment reduce risk by ensuring all technical inventory and use cases are documented and accounted for. It also reveals potential bumps in the road to modernization before they have a chance to derail a project, so mitigation plans can be established up front.
This mainframe assessment work is automated and precise, saving months of time, thousands of dollars in man hours- and ensures no critical requirements or functionality are left out of the target state design. This data also impacts regression testing, making it more accurate and efficient- reducing time to target.
In addition to the risk, cost, and time reduction, customers who undergo a Modern Systems mainframe assessment are able to reduce the scope of their modernization project by an average of 40%.
Here’s how it works:
First, Modern Systems documents the legacy environment's current state and any important dependencies or conditions such as external interfaces, data volumes, batch dependencies, etc.
From there, Modern Systems resources develop the Final Application Inventory package, containing analysis on unused code, Resource Definition and Usage, easy-to-understand visual diagrams laying out the legacy environment, highlighted areas of concentration, and much more.
Finally, the Modern Systems team holds a strategic workshop with your project stakeholders to discuss our findings, provide Optimum Solution Recommendations for areas of concentration, and to map out an informed modernization strategy and roadmap, backed by a soup-to-nuts mainframe assessment and over 3 decades of expe
Leading organizations today are looking to scale their advanced analytics capabilities, especially data mining and predictive analytics, to improve business performance, reduce fraud and improve customer responsiveness. However traditional analytic project approaches are hard to scale and difficult to implement in the real-time environment required in modern enterprise architectures.
Decision Modeling is a new Technique in v3 of the BABOK(r) Guide. It has also become a key element of the Business Intelligence and Business Process Management Perspectives. At the June 2014 IIBA Bay Area Event, James Taylor presents Decision Modeling as a technique (following the new Decision Model and Notation standard), shows how modeling decisions improves business analysis and requirements specification, and discusses the role of decision modeling in business process, business rules, business intelligence and analytic projects.
In this webinar recording, James Taylor, CEO of Decision Management Solutions and Claye Greene, Managing Director of Government Solutions Provider TechBlue share learnings and best practices from their extensive experience helping clients modernize their legacy systems with the targeted decision management approach. You will learn why you don’t need to modernize the whole application, why focusing on business rules is not enough; decision management is the essential ingredient and how to use decision modeling to identify and scope targeted legacy modernization efforts.
Many organizations' agility and responsiveness is hamstrung by their legacy systems. Replacing them wholesale is impossible but the constraint they impose on the business is unacceptable. In this session James Taylor, CEO of Decision Management Solutions, will show how you can use Decision Management and business rules to avoid replacing the whole application while still maximizing agility and improving business alignment.
What you will learn:
How decision components are often the highest change, most difficult to maintain pieces of legacy applications
How Decision Management builds on SOA by externalizing decisions from legacy systems
How a business rules management system dramatically decreases maintenance costs
Why modernizing this way improves business alignment and agility
Webinar recording available at:
https://decisionmanagement.omnovia.com/archives/71756
The Decision Management Manifesto lays out key principles of Decision Management - why decisions are central to your requirements process, why it makes sense to explicitly design decisions before applying technology. Using real world projects this webinar explains the rationale for each part of the manifesto and shows the value it can bring to your projects now and in the future.
Decision management and business rules management systems are the ideal platform for an agile and cost-effective compliance approach. In regulated industries like financial services, leading companies are building compliance into every process and system with consistency and transparency across the entire organization and with the agility to meet ever more challenging deadlines. Companies that fail to do so incur huge costs with manual checks and balances and risk significant fines.
In this webinar James Taylor, CEO of Decision Management Solutions and Jan Purchase, Director and Founder of Investment Banking Specialists Lux Magi, share know-how and best practices from their extensive experience of helping clients implement decision management and business rules management systems to conquer complexity, improve agility, lower costs and measure ongoing effectiveness in financial compliance.
The webinar includes illustrations of how the decision management approach has been applied in compliance projects and a walkthrough of real decision model from one of these.
Business analysts know that modeling business processes, rather than writing about them, defines them more accurately. Business process models make it easier to validate requirements, easier to see opportunities for improvement and easier to manage the process once it is implemented. Replacing traditional specifications with logical business process models based on standard notations like BPMN improves requirements and increases the likelihood of project success.
Yet over-complex processes are common. Complex process models make it harder to engage business owners and reduce the manageability of implementations. One of the prime causes of over-complex processes is the inclusion of decision-making in process designs. Business analysts that identify the decisions in their processes and model them separately – not part of the process but supporting it – find they can simplify process designs, increase agility and bring business users and IT into better alignment. With the publication of a new standard notation - OMG's Decision Model and Notation - and the inclusion of decision modeling in the BABOK, it's time for business analysts to improve their process models by modeling decisions.
Key learning points:
Decisions are central to straight through processing, process innovation and process effectiveness.
Process models obscure decision-making and become over-complex when it is embedded
A standards-based approach to decision modeling is a key technique for process analysts
Mainframe Assessment with Modern Systems' Portfolio Analysis ServicesModern Systems
Legacy systems have passed through many hands over many years, often without proper documentation of features or functional relationships. The most common issue with modernizing a system that very few people understand is that planning for and understanding the breadth and potential pitfalls of a project is virtually impossible without a lot of help. Undergoing a mainframe assessment using Modern Systems' Portfolio Analysis services can significantly reduce risk, cost, and project timelines.
A 2013 survey of IT leaders in the US insurance industry by Gartner reflects just how difficult planning modernizations can be.
- Only 42% of respondents said their modernization projects were completed within originally planned budget.
- Just 34% of the modernization attempts covered the originally planned scope, leaving a whopping 66% of these firms victims of dreaded and out of control scope creep.
- What’s worse, only 18% of respondents completed these projects within their originally planned timeframe.
In other words, modernization is a brutal undertaking. In order to develop well-designed applications from legacy environments, powerful tools and expertise are required to analyze the legacy system and aid in generating new programs that are architecturally sound and utilize modern design methods.
The data and reports gathered in a Modern Systems Portfolio Analysis mainframe assessment reduce risk by ensuring all technical inventory and use cases are documented and accounted for. It also reveals potential bumps in the road to modernization before they have a chance to derail a project, so mitigation plans can be established up front.
This mainframe assessment work is automated and precise, saving months of time, thousands of dollars in man hours- and ensures no critical requirements or functionality are left out of the target state design. This data also impacts regression testing, making it more accurate and efficient- reducing time to target.
In addition to the risk, cost, and time reduction, customers who undergo a Modern Systems mainframe assessment are able to reduce the scope of their modernization project by an average of 40%.
Here’s how it works:
First, Modern Systems documents the legacy environment's current state and any important dependencies or conditions such as external interfaces, data volumes, batch dependencies, etc.
From there, Modern Systems resources develop the Final Application Inventory package, containing analysis on unused code, Resource Definition and Usage, easy-to-understand visual diagrams laying out the legacy environment, highlighted areas of concentration, and much more.
Finally, the Modern Systems team holds a strategic workshop with your project stakeholders to discuss our findings, provide Optimum Solution Recommendations for areas of concentration, and to map out an informed modernization strategy and roadmap, backed by a soup-to-nuts mainframe assessment and over 3 decades of expe
Leading organizations today are looking to scale their advanced analytics capabilities, especially data mining and predictive analytics, to improve business performance, reduce fraud and improve customer responsiveness. However traditional analytic project approaches are hard to scale and difficult to implement in the real-time environment required in modern enterprise architectures.
Decision Modeling is a new Technique in v3 of the BABOK(r) Guide. It has also become a key element of the Business Intelligence and Business Process Management Perspectives. At the June 2014 IIBA Bay Area Event, James Taylor presents Decision Modeling as a technique (following the new Decision Model and Notation standard), shows how modeling decisions improves business analysis and requirements specification, and discusses the role of decision modeling in business process, business rules, business intelligence and analytic projects.
A discussion of the value of Decision Management and decision modeling to the effective management of large, complex operations - including that of a large, global, financial services organization. Presented by James Taylor of Decision Management Solutions at the Building Business Capability Conference (BBCCon) 2015
PASS Business Analytics 2015 - Most organizations lack an approach that lets them specify their requirements for BI or for analytics more broadly. Their ability to find opportunities for, and successfully use, more advanced analytics is limited. In this session, James Taylor will introduce decision modeling with DMN, a new standards-based approach to modeling decisions. He will introduce the core concepts of the approach and show how it can be used to drive more effective requirements for BI, dashboard and analytic projects. Attendees will learn how to begin with the decision in mind, defining their BI requirements in terms of the decision-making they need to improve.
A DMN-based full-fledged implementation of the “UServ Product Derby” decision model showing a DMN Decision Requirements Model and a set of DMN-based Decision Tables that implement it. The derby, recently renamed The Decision Management Challenge, deals with vehicle insurance problems including eligibility and premium calculation policies for a hypothetical insurance company.
Presented by James Taylor of Decision Management Solutions and Dr. Jacob Feldman of OpenRules at the Building Business Capability Conference (BBCCon) 2015.
The new Decision Model and Notation (DMN) standard has been used to gather requirements for and to design Enterprise IT Management dashboards at two Fortune 200 Financial Corporations. These dashboards are used to manage 100+ projects being released every 2 weeks into production across hundreds of critical applications ranging from mainframe, client-server, web and mobile applications.
Presentation from BBC2014
In this webinar, IIA Faculty Member James Taylor, CEO of Decision Management Solutions, will show how to improve analytic results with decision modeling. Decision modeling focuses analytic efforts, clarifies the business goals of analytic projects, and improves collaboration between analytic, business and IT organizations. James will introduce decision modeling, show how it can be used in a wide range of analytic projects and share experiences from using decision modeling in various industries.
The path to a better bottom line is paved by large numbers of operational decisions made by people, by processes and by software applications. Systematically improving each operational decision – at scale – is at the core of Decision Management. Business Architects and Analysts identify, describe and model operational decisions in Decision Discovery.
In this webinar, James Taylor, CEO of Decision Management Solutions, and Dr. Juergen Pitschke, Founder and Managing Director at BCS, will show you how to get started with Decision Management on your next application development or business process improvement project with Decision Discovery. Learn how to:
Identify decisions, sub-decisions and information and knowledge resources (including rules and analytics)
Describe decisions in detail (Decision Tables and other Metaphors)
Model decisions in a DMN-conformant decision modeling tool for communication and documentation
Link to execution environments
Learn how to innovate risk management and customer processes with decision and process management, from leading experts Roger Burlton and James Taylor.
Our business partner and insurance operations expert, Rob Berg, will show you how he helped a major insurance company reducing costs and cycle time using Trisotech Digital Enterprise Suite through process simulation.
In this webinar, analysts, architects and other subject matter experts will learn how to:
- Generate defensible data to make clear and objective decisions
- Accurately model the way things are and the way you would like them to be
- Apply real-life data to process models
- Bring a static model to life by simulating the impact of process changes
Learn how to industrialize your analytic efforts with decision management to get the most out of predictive analytic insights, resources and investments.
201308 Insurance And Technology Webinar: Upgrading Financial SystemsSteven Callahan
Webinar on the reasons for upgrading financial systems, which are often left behind with the focus on customer facing administration and distribution management systems. Yet regulations are forcing companies to look at the benefits of upgrading their financial systems.
This article describes 10 Architecture Solution Design principles to help organization focus their solution architecture teams around simple but effective design criteria.
Models Collecting Dust? How to Transform Your Results from Interesting to Imp...Revolution Analytics
Data scientists sometimes lament, "Why can't I get anyone to use my predictions?" Great models that make accurate predictions are sometimes disconnected from organizational decision-making. This hurts the business and reduces the data scientists’ perceived value the within the organization. But it doesn't have to be this way. Leading expert James Taylor, author of Decision Management Systems: A Practical Guide to Business Rules and Predictive Analytics, has developed a practical approach you can use to improve adoption and elevate your organization.
Investing Intelligently In The IT FunctionAlan McSweeney
Describes an approach to defining the competencies and capabilities required of the IT function and to use current levels of competence and importance of competency across all activity areas of the IT function to identify those areas at which getting better will yield the greatest return, allowing for targeted investment of resources to get good at what matters
Analytics is an overused term. This webinar shows how BI, web analytics, data mining and predictive analytics all have a role but all need a focus on decisions - especially operational decisions - to maximize their value. Webinar recording available here: http://decisionmanagement.omnovia.com/archives/64147
A discussion of the value of Decision Management and decision modeling to the effective management of large, complex operations - including that of a large, global, financial services organization. Presented by James Taylor of Decision Management Solutions at the Building Business Capability Conference (BBCCon) 2015
PASS Business Analytics 2015 - Most organizations lack an approach that lets them specify their requirements for BI or for analytics more broadly. Their ability to find opportunities for, and successfully use, more advanced analytics is limited. In this session, James Taylor will introduce decision modeling with DMN, a new standards-based approach to modeling decisions. He will introduce the core concepts of the approach and show how it can be used to drive more effective requirements for BI, dashboard and analytic projects. Attendees will learn how to begin with the decision in mind, defining their BI requirements in terms of the decision-making they need to improve.
A DMN-based full-fledged implementation of the “UServ Product Derby” decision model showing a DMN Decision Requirements Model and a set of DMN-based Decision Tables that implement it. The derby, recently renamed The Decision Management Challenge, deals with vehicle insurance problems including eligibility and premium calculation policies for a hypothetical insurance company.
Presented by James Taylor of Decision Management Solutions and Dr. Jacob Feldman of OpenRules at the Building Business Capability Conference (BBCCon) 2015.
The new Decision Model and Notation (DMN) standard has been used to gather requirements for and to design Enterprise IT Management dashboards at two Fortune 200 Financial Corporations. These dashboards are used to manage 100+ projects being released every 2 weeks into production across hundreds of critical applications ranging from mainframe, client-server, web and mobile applications.
Presentation from BBC2014
In this webinar, IIA Faculty Member James Taylor, CEO of Decision Management Solutions, will show how to improve analytic results with decision modeling. Decision modeling focuses analytic efforts, clarifies the business goals of analytic projects, and improves collaboration between analytic, business and IT organizations. James will introduce decision modeling, show how it can be used in a wide range of analytic projects and share experiences from using decision modeling in various industries.
The path to a better bottom line is paved by large numbers of operational decisions made by people, by processes and by software applications. Systematically improving each operational decision – at scale – is at the core of Decision Management. Business Architects and Analysts identify, describe and model operational decisions in Decision Discovery.
In this webinar, James Taylor, CEO of Decision Management Solutions, and Dr. Juergen Pitschke, Founder and Managing Director at BCS, will show you how to get started with Decision Management on your next application development or business process improvement project with Decision Discovery. Learn how to:
Identify decisions, sub-decisions and information and knowledge resources (including rules and analytics)
Describe decisions in detail (Decision Tables and other Metaphors)
Model decisions in a DMN-conformant decision modeling tool for communication and documentation
Link to execution environments
Learn how to innovate risk management and customer processes with decision and process management, from leading experts Roger Burlton and James Taylor.
Our business partner and insurance operations expert, Rob Berg, will show you how he helped a major insurance company reducing costs and cycle time using Trisotech Digital Enterprise Suite through process simulation.
In this webinar, analysts, architects and other subject matter experts will learn how to:
- Generate defensible data to make clear and objective decisions
- Accurately model the way things are and the way you would like them to be
- Apply real-life data to process models
- Bring a static model to life by simulating the impact of process changes
Learn how to industrialize your analytic efforts with decision management to get the most out of predictive analytic insights, resources and investments.
201308 Insurance And Technology Webinar: Upgrading Financial SystemsSteven Callahan
Webinar on the reasons for upgrading financial systems, which are often left behind with the focus on customer facing administration and distribution management systems. Yet regulations are forcing companies to look at the benefits of upgrading their financial systems.
This article describes 10 Architecture Solution Design principles to help organization focus their solution architecture teams around simple but effective design criteria.
Models Collecting Dust? How to Transform Your Results from Interesting to Imp...Revolution Analytics
Data scientists sometimes lament, "Why can't I get anyone to use my predictions?" Great models that make accurate predictions are sometimes disconnected from organizational decision-making. This hurts the business and reduces the data scientists’ perceived value the within the organization. But it doesn't have to be this way. Leading expert James Taylor, author of Decision Management Systems: A Practical Guide to Business Rules and Predictive Analytics, has developed a practical approach you can use to improve adoption and elevate your organization.
Investing Intelligently In The IT FunctionAlan McSweeney
Describes an approach to defining the competencies and capabilities required of the IT function and to use current levels of competence and importance of competency across all activity areas of the IT function to identify those areas at which getting better will yield the greatest return, allowing for targeted investment of resources to get good at what matters
Analytics is an overused term. This webinar shows how BI, web analytics, data mining and predictive analytics all have a role but all need a focus on decisions - especially operational decisions - to maximize their value. Webinar recording available here: http://decisionmanagement.omnovia.com/archives/64147
A presentation on Customer Decision Management and how it results in more accurate, more real-time, more consistent, more agile and more scalable customer decisions. Presented at Teradata Partners 2013
Deploying analytics with a rules-based infrastructure, James Taylor, CEO of Decision Management Solutions, presentation at Predictive Analytics World, SF 2011. #pawcon
Decision management's systematic embedding of predictive analytics into automated decision-making systems complements cloud technologies and maximizes the value of predictive analytics.
Decision CAMP 2014 - James Taylor - Decision Management 101Decision CAMP
Decision Management is both an approach and a technology stack.
In this opening day workshop, Decision Management consultant and author James Taylor will introduce both.
We'll begin with the discovery and modeling of suitable decisions, move into the construction of decision services and wrap up with the importance of decision analysis for continuous improvement. The critical technology capabilities - managing decision logic, embedding analytics, monitoring decision performance, and optimizing results - will all be introduced and presented in a coherent architecture for building Decision Management Systems.
Different adoption paths and some best practices will conclude the session, putting you on a path to Decision Management success.
Although Big Data is changing enterprise data architecture models, support for Big Data extends beyond the walls of IT. The most successful companies are focused on building strong business cases for Big Data to drive support, adoption and funding though the enterprise.
This webinar investigated the two perspectives in constructing a business case for Big Data as well as how to create a compelling business case for Big Data success.
During this webinar, we covered:
-Challenges Creating Business Cases for Big Data
-Two perspectives for building Big Data business-cases
-Building the business-focused case and getting to monetized benefits
-Fortifying your business case with IT-benefits
What opportunities are you looking for to improve your business performance? In this webinar you will learn six opportunities that are readily available when you adopt a decision management approach to business rules and predictive analytics.
Predictive analytic models are not new within many analytical organizations. However, the use of predictive analytics is growing rapidly. Data-driven decision-making initiatives are compelling more and more enterprises to move their analytics efforts beyond the basics. Enterprises must go from measurement and reporting to predictions and decision management. With ever-increasing amounts of historical data ready for mining, the right predictive analytic models can help an enterprise understand future behavior – adherence to medical prescriptions, increased or decreased spending, loan repayment, and more. By driving better decision-making, such insights can be transformative. Join us as we look into best-practices for building a predictive enterprise, technology tips for using and implementing predictive analytics tools, and guidelines for building predictive models.
A rebroadcast of one of the best reviewed sessions at this year's Predictive Analytics World. Learn the critical success factors in delivering business value with advanced analytics.
Retail Decision Analytics: Linking BI with automated executionQuantum Retail
This presentation covers the history of retail business analytics, the challenges retailers face, and checkpoints of what they should be seeking in a BI or analytics tool.
While many Digital Transformation initiatives are focused on improving the customer experience, often too little attention is paid to the customer-facing operational decisions that impact customers every day. To get the most from your Digital Transformation efforts, your customers’ experience and the decisions that impact it cannot be ignored.
The speed, volume and complexity of decisions – as well as the impact they have on customer experience – demand automated, real-time decision making. Digital decisioning is an emerging best practice for delivering business impact from AI, machine learning, and analytics. Digital decisioning is an approach that ensures your systems act intelligently on your behalf, making precise, consistent, real-time decisions at every customer touchpoint.
Audio on our YouTube Channel: https://youtu.be/cGxPYnE5PTM
The speed, volume and complexity of decisions – as well as the impact they have on customer experience – demand automated, real-time decision making. Digital decisioning is an emerging best practice for delivering business impact from AI, machine learning, and analytics. Digital decisioning is an approach that ensures your systems act intelligently on your behalf, making precise, consistent, real-time decisions at every customer touchpoint.
Audio on our YouTube Channel: https://youtu.be/cGxPYnE5PTM
Hear insurance industry expert Craig Bedell and Decision Management expert James Taylor discuss the importance of digital decisioning to improving insurance productivity.
See slides with audio here: https://youtu.be/YgCOkc23s8k
Does your Rules Consultant think execution matters more than management? That's “old school” thinking. Find out if your Rules Consultant is providing your business with real value by watching this webinar.
Join Decision Management Solutions, Velocity Business Services and Datarobot as we discuss the importance of operational decisions, industrialized predictive analytics and business learning in creating a predictive enterprise.
A claims handling pilot delivers data-driven claims risk, fraud and wastage decisions directly into your claims process. Using real-world examples, learn how you can maximize straight through “Jet” processing while minimizing risk and fraud using a decision-centric, continuous improvement business architecture. Our proven decisions-first approach delivers the 5 elements of a powerful claims handling platform: decision model, business rules, risk and fraud analytics, impact analysis and continuous improvement.
One of the prime causes of complex business processes is the inclusion of decision-making in process designs. Organizations that identify the decisions in their processes and manage them as peers – not part of the process but supporting it – find they can simplify process designs, increase agility and bring business users and IT into better alignment.
This webinar will build on real case studies to show you how keeping decisioning and process entangled creates complexity, how to find decisions in your complex processes and how Decision Management delivers simpler, more manageable processes.
Successful digital programs extend their Digital Business Platforms with 3 critical elements: decision modeling, predictive analytics and business rules technology. Coordinating these technologies into a virtual decision hub. Decision Management automates and improves every digital interaction and delivers agile, data-driven, real-time outcomes.
Organizations are increasingly investing in data analytics to improve decision-making. Dashboards, self-service BI, data mining, predictive analytics, machine learning and cognitive technologies are being evaluated, deployed and used as organizations push to adopt data-driven decision-making. Effectively using these analytic technologies requires a disciplined focus on better decisions. Some organizations are using decision modeling, and the DMN standard, to achieve analytic excellence.
DMN is a great standard and we’ve both achieve considerable successes with it: its help to improve the transparency, accuracy and agility of many business decisions and helped us to deliver better decisions and decision services to our clients. However, like any released product, DMN 1.1 can benefit from usage suggested refinements.
To succeed, an analytics or data science team must effectively engage with business experts who are often inexperienced with advanced analytics, machine learning and data science. They need a framework for connecting business problems to possible analytics solutions and operationalizing results. Decision modeling brings clarity to analytics projects, linking analytics solutions to business problems to deliver value.
Get deployed! Many Analytics Teams have experience with building what seems like a great model–valid, predictive, powerful–only to see disappointing or even no business impact. Some models are not deployed, or take so long to deploy their accuracy is lost. Even deployed models are often not used effectively.
What can you do? Learn the 5 questions to ask before deploying your model.
A decision modeling approach using DMN is the best practice for for scaling BRMS. Decision modeling address three key challenges of a existing BRMS program, improving traceability, sustaining business engagement and maximizing re-use while minimizing duplication.
Get the business understanding right! Analytics Teams know that one of their biggest challenges is effective communication and collaboration with their business partners. Projects are plagued with too many iterations to get to a solution, too many detours responding to unfocused requests, and too often the final model results in a positive analytic result that can’t demonstrate business value.
What can you do? Analytics and decision modeling expert James Taylor of Decision Management Solutions outlines six questions to ask your business partner before you start modeling and shows you why decision modeling is the best approach to building this shared understanding.
If you are kicking off your first BRMS project, don’t start by gathering the rules! Often teams will be advised to begin their project by gathering all the relevant rules, in a natural language or rulebook approach.
But these rules-first approaches address issues that don’t exist with modern BRMS technology, resulting in redundant and counter-productive efforts.
A decisions-first, decision modeling approach using the Decision Model Notation (DMN) standard is the best practice for business rules projects when implementing a modern BRMS.
In this recording of our live webinar, you will learn why building a decision model that is linked to the business context (metrics, processes, logical data structures) and then implementing this directly in a linked BRMS is faster and cheaper while resulting in more accurate rules, more business engagement and better value realized.
Learn how decision models based on the Decision Model and Notation (DMN) standard can be more easily integrated with business rules being managed and deployed using JBoss BRMS, improving traceability and business ownership.
Decisions First Modeler Enterprise Edition Integration with JBoss BRMSDecisionsFirst Modeler is a collaborative decision modeling solution using the new Decision Model and Notation (DMN) standard. DecisionsFirst Modeler provides a diagram-based, business user friendly front-end to the business rules environment.
DecisionsFirst Modeler enables organizations to accurately specify their business using decision requirements models; structure and manage the supporting business rules; and streamline business process design.
The Enterprise Edition integration with IBM ODM delivers traceability from business objectives through decision requirements to the business rules running in production. This ensures that DecisionsFirst Modeler users have full access to all the rule editing, validation, simulation, deployment and management capabilities of IBM ODM.
DecisionsFirst Modeler is a collaborative decision modeling solution using the new Decision Model and Notation (DMN) standard. DecisionsFirst Modeler provides a diagram-based, business user friendly front-end to the business rules environment.
As businesses have an increasing obligation to demonstrate compliance with regulations there is a need for a business architecture view that not only tracks regulations impact but also connects seamlessly to diverse, distributed implementations in automated systems and manual procedures. The Decision Model Notation (DMN) has been used to create a decision architecture for regulatory compliance at a leading global financial organization. This Regulatory Architecture includes business decisions impacted by a variety of global financial regulations – the Dodd Frank Act, in particular. This business architecture has been modeled in the form of decision requirement models and aligned with business process and business organization architectures. Presented by Gagan Saxena of Decision Management Solutions at the Building Business Capability Conference (BBCCon) 2015
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
3. Decisions and smarter systems Different kinds of decisions Introducing Decision Management Business Rules and Decision Management Analytics and Decision Management Wrap and next steps
20. Consequences of Decision Management Business Control of Decisions Simpler, more agileBusiness Processes Integration of Business Analytics Externalization from Legacy Applications Separation of Decisions
21. Decision Management, Decision Support 100% Decision Management OperationalDecisions TacticalDecisions StrategicDecisions Decision Support 0% Decision Volume Increases Smart (Enough) Systems, Prentice Hall June 2007. Fig 2.3
Large companies rely on their Enterprise Resource Planning (ERP) and other supply chain systems to manufacture, distribute and manage the products their customers need. The behavior of these operational systems is critical to how a company treats, and is perceived by, its customers, its partners and its suppliers. Yet these systems are often plagued by manual interventions that delay processes, by hard to change constraints and thresholds and by problems with local exceptions to global processes. This session will show how using Decision Management to apply business rules and analytic technology can upgrade your ERP to be smarter and more agile. Illustrated with case studies, one attendee will receive a free signed copy "Applying Real-World BPM in an SAP Environment".
At its heart a decision is a choice, a selection of a course of action. A decision is arrived at after consideration and it ends uncertainty or dispute about something.Decisions are made only after considering various facts or pieces of information about the situation and participants.Decisions select from alternatives, typically to find the one most profitable or appropriate for an organization.Decisions result in an action being taken, not just knowledge being added to what’s knownThe basic decision making process is simple. Data is gathered on which to base the decision. Some analysis of this data is performed and rules derived from company policy, regulations, best practices and experience is applied. A course of action, a selection from the possible options, is then made so that it can be acted on. When considering decisions in operational business processes, the way the decision is made is often constrained such that it can be described and automated effectively in many, even most, cases.
As we are talking about decisions it is worth remembering that all decisions matter, as Peter Drucker noted. Not just the big, strategic decisions of your executives but the day to day decisions that drive your business.
Volume—Perhaps the most common characteristic of operational decision problems is that the number of decisions of a particular type you must make is high—so high you must automate it or high enough that many front-line workers must make it on your behalf. Volume alone can cause problems or exacerbate another decision problem, such as compliance or risk assessment. Latency—Many managers now have more timely information about their business. If you can use this information to see trouble coming but can’t change how you make decisions in time, you might have an operational decision problem. The latency between knowing something must change and being able to change it probably comes from having systems or people processes that are hard to change quickly. This is often caused by the way operational decisions are handled.Variability—Try imagining nightmare scenarios and thinking about what approach you might take. Think about the systems and people interacting with associates. Decisions those systems and people affect that must change to reflect your new approach could well be operational decisions that, although not a problem now, would cause problems if the business climate changed suddenly.Compliance—Ensuring that decisions are made consistently by using the same set of guidelines and policies and being able to prove to regulators that the correct rules are in place and used for a given decision can be difficult, especially if the decision must be made in any sort of volume. Demonstrating compliance in every operational decision can be particularly time-consuming if the decision isn’t automated correctly.Straight-through processing—“Straight-through processing” or “once and done” processing involves performing every step in a transaction or process without human intervention. A manual review that drags down response time in a process might be hiding a problem-prone operational decision. If you have a mostly automated process that hangs up on manual reviews, you might have a good candidate for an operational decision.Managing risk—A prime reason for having a person involved in a process is to manage risk, which is often all about making decisions that manage trade-offs or risks and rewards. A risk-centered decision that must be made quickly or in volume might be a good candidate for an operational decision.Unattended—With some transactions, there’s no choice but to automate a decision. Without automation, there’s no way to inject expertise or learn what works better and improve the decision; for example, there’s no person who can make a decision in transactions on your Web site or at your ATM. These kinds of decisions are often good candidates for operational decisions.Self-service—Complex decisions are more common in self-service. No longer is it enough for a self-service portal to deliver a document or ask someone to call an 800 number when things get complex. Now you need to automate this decision so that customers can self-serve, even when the decisions involved are complex.Personalized—Any time you want to personalize interactions with associates, you’re making a decision. For most organizations, these operational decisions can create problems because of the need to balance timeliness with personalization. (Taylor and Raden 2007)
much of a typical mainframe system is static, works fine and needs no maintenance. Often only a small portion of the system is responsible for much of the maintenance work. My suggestion would be to find the COBOL that represents business decisions such as a pricing engine (what price is this product for this customer), eligibility logic (is this customer eligible for this offer or service), approval rules (can this claim be auto-approved) and replace those parts of the application with Decision Services.
Remember – decisions are where the business, analytics and IT all come together
The consequences of this are 5 foldFirst we isolate decisions so that they can be managed and controlledThis allows the high-change, complex logic elements of legacy applications to be externalizedIt gives us points of control and agility in processesIt allows for the easy integration of analyticsMost of all, it puts the business in control of decisions even when those decisions are being automated and delivered into our applications.One of the interesting facts about Decision Management is that it was created by studying history and observing what worked – I know as I was there. This was not an attempt to describe a new thing but to give a label to an old thing – something that worked and worked well in a particular environment because it seemed that the things that had limited it to this niche – hardware cost, performance, software techniques – were a thing of the past.
People make decisions based on prior experience and expertise.People make decisions based on pre-conceptions and biases.People make decisions based on policies and regulations and their understanding of them.People make decisions based on historical information and their analysis of itPeople make decisions based on context
Here’s the stack again just to be clear.But #39 is important here too – managing readiness and organizational change.
So making decisions correctly will be hard unless we can pull all these rules together.Given this is how rules often look to start with, this is clearly going to be hard.But rules also change…Because your business policies doBecause your competitors doBecause the law doesBecause stock levels doBecause your services and products doBecause your customers doBecause your customers’ needs doSo we need something that will let us collect, manage and update the business rules that drive our decisions
Customer ChurnCustomer Service CallsLoss to CompetitorsRetention Budget
Let’s take a process like completing the sale of a subscription service, a location-dependent one like a cell phone, and see what decisions are part of that process. The process involves a customer specifying the service they want, answer questions about themselves and then either getting accepted or rejected.In this process there is clearly a decision – can this customer buy this service. We can drill into this a little. To determine if a customer is eligible for a service we might do several things. First we might check to see if the service they want is available in their area, we might check to see if we still have capacity on the service and then we will see if the information provided by the customer makes them eligible for the service. So now we have a decision with three rulesets or sub-decisions:Can this customer buy this service?Is the service available where the customer livesIs there capacity on this service?Is the customer eligible for the service?Interestingly we can immediately see that the first of these might be one we want to expose as an independent decision so that a customer can check to see if a service in which they are interested is available in their area. Similarly we might combine the first two for a customer service representative to answer a customer question. The difference here is that we might not want to expose problems with capacity too casually.Returning to our process we might decide that we don’t just want a yes/no we want what I call a “yes and/no but” decision. In other words we want to say yes when we can but also see if there is a cross-sell/up-sell that makes more sense. Similarly if we would have to say no we want to be able to say no but you can get this product (presumably something similar).Now we have a second decision – what is the best upsell/cross-sell for this service for this customer. This would take customer information and a service (one already approved for them) and return either a replacement service (an upsell) or an additional service (a cross sell). This decision probably has two sub-decisions:What is the best upsell/cross-sell for this customer when buying this service?Is there a replacement service that is a compelling upsell for this customer for this service?Is there a cross-sell/additional service for this customer when buying this service?And if the first one returns a new, upsell service then the cross-sell would need to be executed against the upsell service.And we have a third decision – what is a similar decision for this customer when rejected for this service. This too has two sub-decisions:what is a similar decision for this customer when rejected for this servicewhat services are similar to this service?which services (from a list) is this customer eligible for?Interesting the second sub-decision uses the same rules as the eligibility check mentioned earlier but takes a set of services to check not a single one. Also we might choose to expose the what services are similar decision as a decision so that a customer looking at a particular service would see a list of “other services you might want to consider).Finally we might decide that pricing is not static for these services and so add a decision what is the price for this service for this customer at this time? This could use things like promotions, customer profile and existing products/services owned to calculate a discount etc.