Delivering the promise of data mining and predictive analytics requires an operational platform that is agile, business-friendly and decision-centric - decision modeling with DMN and business rules.
One of the most important steps in a predictive analytic effort is correctly framing the problem a way that creates a shared understanding of the business problem across business, IT and analytics teams. A decision requirements model makes it clear how to best leverage analytics. Watch the webinar recording at http://decisionmanagement.omnovia.com/archives/223762
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.
Requirements for a Master Data Management (MDM) Solution - PresentationVicki McCracken
Working on Requirements for a Master Data Management solution and looking for thoughts on how to approach the requirements? This is an overview presentation that complements my guide on how to approach requirements for a Master Data Management solution (Requirements for an MDM Solution). You may be able to leverage all or some of the approach described in this guide to formulate your approach.
A Data Management Maturity Model Case StudyDATAVERSITY
How Ally Financial Achieved Regulatory Compliance with the Data Management Maturity (DMM) Model
Ally Financial Inc., previously known as GMAC Inc., is a bank holding company headquartered in Detroit, Michigan. Ally has more than 15 million customers worldwide, serving over 16,000 auto dealers in the US. In 2009 Ally Bank was launched – at present it has over 784,000 customers, a satisfaction score of over 90%, and has been named the “Best Online Bank” by Money magazine for the last four years.
Ally was an early adopter of the DMM, conducting a broad-based evaluation of its data management practices, and creating a strategy and sequence plan for improvements based on the results. Ally’s implementation of an integrated, organization-wide data management program including data governance, a robust data quality program, and managed data standards, resulted in a “Satisfactory” rating on its latest regulatory audit.
In this webinar, you will learn:
How Ally employed the DMM to evaluate its data management practices
Who was involved / lessons learned
How Ally prioritized and sequenced data management improvement initiatives
How the data management program has been enhanced and expanded
Business impacts and benefits realized
Major initiatives completed and underway
How Ally is leveraging DMM 1.0 to proactively prepare for BCBS 239 compliance.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
One of the most important steps in a predictive analytic effort is correctly framing the problem a way that creates a shared understanding of the business problem across business, IT and analytics teams. A decision requirements model makes it clear how to best leverage analytics. Watch the webinar recording at http://decisionmanagement.omnovia.com/archives/223762
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.
Requirements for a Master Data Management (MDM) Solution - PresentationVicki McCracken
Working on Requirements for a Master Data Management solution and looking for thoughts on how to approach the requirements? This is an overview presentation that complements my guide on how to approach requirements for a Master Data Management solution (Requirements for an MDM Solution). You may be able to leverage all or some of the approach described in this guide to formulate your approach.
A Data Management Maturity Model Case StudyDATAVERSITY
How Ally Financial Achieved Regulatory Compliance with the Data Management Maturity (DMM) Model
Ally Financial Inc., previously known as GMAC Inc., is a bank holding company headquartered in Detroit, Michigan. Ally has more than 15 million customers worldwide, serving over 16,000 auto dealers in the US. In 2009 Ally Bank was launched – at present it has over 784,000 customers, a satisfaction score of over 90%, and has been named the “Best Online Bank” by Money magazine for the last four years.
Ally was an early adopter of the DMM, conducting a broad-based evaluation of its data management practices, and creating a strategy and sequence plan for improvements based on the results. Ally’s implementation of an integrated, organization-wide data management program including data governance, a robust data quality program, and managed data standards, resulted in a “Satisfactory” rating on its latest regulatory audit.
In this webinar, you will learn:
How Ally employed the DMM to evaluate its data management practices
Who was involved / lessons learned
How Ally prioritized and sequenced data management improvement initiatives
How the data management program has been enhanced and expanded
Business impacts and benefits realized
Major initiatives completed and underway
How Ally is leveraging DMM 1.0 to proactively prepare for BCBS 239 compliance.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
What has changed in DMBok V2?
We have been working with DMBoK V1 for may years and it is great to finally get to read and study the changes. Did a quikc comparison between the 2 versions.
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.
Data Warehousing in the Cloud: Practical Migration Strategies SnapLogic
Dave Wells of Eckerson Group discusses why cloud data warehousing has become popular, the many benefits, and the corresponding challenges. Migrating an existing data warehouse to the cloud is a complex process of moving schema, data, and ETL. The complexity increases when architectural modernization, restructuring of database schema, or rebuilding of data pipelines is needed.
Adopting a Process-Driven Approach to Master Data ManagementSoftware AG
What is a lasting solution to the sea of errors, headaches, and losses caused by inconsistent and inaccurate master data such as customer and product records? This is the data that your business counts on to operate business processes and make decisions. But this data is often incomplete or in conflict because it resides in multiple IT systems. Master Data Management (MDM)'s programs are the solution to this problem, but these programs can fail without the investment and involvement of business managers.
Listen to Rob Karel, Forrester analyst, and Jignesh Shah from Software AG to learn about a new, process-driven approach to MDM and why it is a win-win for both business and IT managers.
Visit us at http://www.softwareag.com Become part of our growing community: Facebook: http://www.facebook.com/softwareag Twitter: http://www.twitter.com/softwareag LinkedIn: http://www.linkedin.com/company/software-ag YouTube: http://www.youtube.com/softwareag
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
Enterprise resource planning (ERP) is business management software that allows an organization to use a system of integrated applications to manage the business.
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Implementing a Successful, Scalable, Governed BI ProgramPyramid Analytics
Explore elements, challenges, and tips in orchestrating a successful BI program. See related highlights from the BARC BI Survey 14 and from Gartner research. This slide presentation accompanies a webinar given in March 2015. For more contextual information related to these slides, see the list of content on the “Additional resources” slide of this presentation.
Presentation given at the IIR Business Process Management Conference, San Diego, CA, November 13th, 2007. It focuses on the difference between rules and processes, the integration points of BPMS and BRMS, and ways to get started.
What has changed in DMBok V2?
We have been working with DMBoK V1 for may years and it is great to finally get to read and study the changes. Did a quikc comparison between the 2 versions.
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.
Data Warehousing in the Cloud: Practical Migration Strategies SnapLogic
Dave Wells of Eckerson Group discusses why cloud data warehousing has become popular, the many benefits, and the corresponding challenges. Migrating an existing data warehouse to the cloud is a complex process of moving schema, data, and ETL. The complexity increases when architectural modernization, restructuring of database schema, or rebuilding of data pipelines is needed.
Adopting a Process-Driven Approach to Master Data ManagementSoftware AG
What is a lasting solution to the sea of errors, headaches, and losses caused by inconsistent and inaccurate master data such as customer and product records? This is the data that your business counts on to operate business processes and make decisions. But this data is often incomplete or in conflict because it resides in multiple IT systems. Master Data Management (MDM)'s programs are the solution to this problem, but these programs can fail without the investment and involvement of business managers.
Listen to Rob Karel, Forrester analyst, and Jignesh Shah from Software AG to learn about a new, process-driven approach to MDM and why it is a win-win for both business and IT managers.
Visit us at http://www.softwareag.com Become part of our growing community: Facebook: http://www.facebook.com/softwareag Twitter: http://www.twitter.com/softwareag LinkedIn: http://www.linkedin.com/company/software-ag YouTube: http://www.youtube.com/softwareag
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
Enterprise resource planning (ERP) is business management software that allows an organization to use a system of integrated applications to manage the business.
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Implementing a Successful, Scalable, Governed BI ProgramPyramid Analytics
Explore elements, challenges, and tips in orchestrating a successful BI program. See related highlights from the BARC BI Survey 14 and from Gartner research. This slide presentation accompanies a webinar given in March 2015. For more contextual information related to these slides, see the list of content on the “Additional resources” slide of this presentation.
Presentation given at the IIR Business Process Management Conference, San Diego, CA, November 13th, 2007. It focuses on the difference between rules and processes, the integration points of BPMS and BRMS, and ways to get started.
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.
Predictive analytics are increasingly a must-have competitive tool. A well-defined workflow and effective decision modeling approach ensures that the right predictive analytic models get built and deployed.
Transforming Business with Smarter AnalyticsCTI Group
Transforming Business with Smarter Analytics by Deb Mukherji @ BPT IBM Innovative Indonesia with Smarter Analytics, 12 June 2013, Shangri-La Hotel Jakarta
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.
Personalizing the web or mobile experience for your audience can seem like a daunting task. In this webinar, Whitney Littlewood (Director of Strategic Optimization) and Jon Noronha (Audiences Product Manager) walk you through how you can leverage Optimizely to create more relevant experiences for your target customers through a tour of practical use cases for a range of business goals.
The Decision Table Template For Geospatial Business RulesJacob Feldman
We explore a new system that allows business users to natively define and maintain complex spatial rules without becoming experts in specific Java APIs. We applied OpenRules BDMS to create a new Spatial Decision Table template that allows stakeholders with no GIS training to use plain English in familiar Decision Model spreadsheets to define spatially aware business rules without any additional software.
Practical Techniques for Resolving Conflicts among Business RulesJacob Feldman
Modern rules and decisions management systems provide effective mechanisms for modeling, managing and execution of business decision models. However, building real-world decision models, business analysts frequently face complex issues related to diagnostic and resolution of business rule conflicts. Some systems can effectively verify decision model consistency and diagnose rule conflicts. However, contradictory rules occur in normal business situations, and maintaining rules with exceptions is a very typical example. Today it mainly remains a responsibility of users to represent rules in such a way that allows them to avoid conflicts. As a result, the number of rules grows exponentially making their maintenance a real problem. Is it possible to automatically resolve rule conflicts?
In this presentation we discuss different techniques for automatic resolution of conflicts among business rules. We will consider classical “strict” rules and “defeasible” rules that actually can be defeated by other rules. We will consider different representations of superiority relations among rules when one rule may override the conclusion of another rule. We will describe practical examples of contradictory rules from financial and other business domains. And finally we will demonstrate how a well-known theory of the “defeasible reasoning” can be incorporated into the modern Business Rules Management systems delivering practical solutions for this important problem
Impact 2012 1640 - BPM Design considerations when optimizing business process...Brian Petrini
Whilst it is not always possible to remove and automate human tasks in a process, if it can be done, it often leads to the most dramatic optimization, leading to fully straight through processing. The challenge is that if straight through processing is the goal, we may need to design the process differently from the beginning, with automation in mind. This lecture uses tried and tested techniques for assessing processes to establish whether they are likely to be able to evolve to full automation, and recommends design patterns to be used to simplify the progression from manual to decision supported to completely automated.
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.
Research into how people find and share expertise can be traced back to the 1960s, with early studies focusing on knowledge workers such as engineers and scientists and the information sources they consult. However, in recent years there has been a growing recognition that the effectiveness of expertise retrieval systems is highly dependent on a number of contextual factors, where the emphasis is on how people search for expertise in the context of a specific task. These studies have typically been performed in an enterprise context, where the aim is to utilize human knowledge within an organization as efficiently as possible. This talk presents results of an Innovate-UK funded project investigating the use of complex search strategies in the workplace, with the aim of producing requirements for the design of next generation search tools.
Next Steps In Your Digital TransformationVMware Tanzu
This session brings together all the lessons learnt throughout the day and shares with you practical advice on how to get started with, or accelerate, your journey to become a digital business.
Speaker: Fadi Yousuf, Sales Manager - Gulf & KSA, Pivotal
Role of Data in Digital TransformationVMware Tanzu
Data plays a big role in building the kinds of experiences demanded by the market today. In this session, we’ll unpack what goes into building a data-driven app, case studies of how organizations have successfully overcome siloed data and analytics to bring new predictive features into their applications, and what your next steps for data should be on your digital transformation journey.
Speaker: Les Klein, EMEA CTO Data, Pivotal
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
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.
Creating a Business Case for Global Payroll - APA Fall ForumCatriona Keevans
Mark Graham, Executive Director at Immedis, spoke at the 2017 Fall Forum. His presentation was focused around Creating a Business Case for Global Payroll
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.
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
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
Your success with 0365 and SharePoint 2016 is not assured: A successful Digital Workplace transformation goes way beyond getting the software installed and configured successfully. Fortunately your chances have greatly improved recently with the advances made by Microsoft. By integrating new capabilities and social tools into everyday work processes we are able to reimagine how work gets done and have measureable impact to the bottom line.
In this session we will discuss the importance of creating a Digital Workplace Transformation Strategy to ensure a successful Digital Workplace Transformation. In this highly interactive session, we’ll share key aspects of a Digital Workplace Strategy and discuss how to engage business stakeholders, drive user adoption, and realize a true return on your organization’s investment in SharePoint and 0365.
Highlights include:
•Defining your Vision
•Determining the potential Business Impact
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
Identifying and managing the decisions within a business process are critical next steps for greater efficiency and effectiveness in organizations today.
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.
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
5 tips als je nu wilt starten met digital marketing analyticsAvanade Nederland
Uit onderzoek van de DDMA blijkt dat 47 procent van de Nederlandse ondernemingen het onderbuikgevoel en ervaring als belangrijke factoren zien in het besluitvormingsproces. Maar liefst 90 procent geeft daarnaast aan dat marketeers meer en meer kennis in huis moeten hebben op het gebied van data, dataverzameling en data analyse. Hoe ga jij als digital marketeer hiermee aan de slag? Wij geven jou 5 tips om vandaag nog aan de slag te gaan met digital marketing analytics. Daarnaast gebruiken we praktijkvoorbeelden om je te laten zien hoe je met analytics nieuwe afzetmarkten en doelgroepen kunt ontdekken.
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.
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.
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.
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.
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.
Learn how to innovate risk management and customer processes with decision and process management, from leading experts Roger Burlton and James Taylor.
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
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
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.
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
2. 1 2 3
4 5 6
AGENDA
The power of
analytics
Challenges in
analytics
Introducing
business rules
Integrating
business rules
and analytics
Decision
Management
Wrap Up
48. Thank you!
James Taylor, CEO
james@decisionmanagementsolutions.com
www.decisionmangementsolutions.com
Editor's Notes
Putting business analytics to work is top of mind for organizations like yours. Business agility and operational responsiveness are more important than ever. There is a real opportunity to use analytics – especially predictive analytics – to seek out increasingly small margins and understand your customers, products, channels, partners and more. But predictive analytics is only part of the solution – you must put these analytic insights to work making better decisions every day. Business rules offer the agile, business-centric platform you need to manage decisions and effectively deploy predictive analytics. Putting them together requires a new conceptual framework – Decision Management.
Applying analytics to acquire, retain and grow 100M customersBusiness challenge:100M customers and 3Bn calls / day200TB of customer information1.3M Retail partnersRural and urban consumers, large and small companiesSolution:Integrated data warehouse across all channels, all productsReal-time analytics for micro-segmentation, offer targetingWeb, retail, call-center and mobile channelsBenefits:Rapid growth with 2-3M new customers/monthGrowing and accelerating Revenue Market Share
Models make predictions but predictions alone will not help much – you must ACT based on those predictions.When you are thinking about smarter systems, taking action means having the system take action in a way that uses the predictions you made. You need to make a decision based on those predictions and this means combining the models with rules about how and when to act.Let’s take our retention example from earlier. Knowing that a customer is a retention risk is interesting, acting appropriately and in time to prevent them leaving is usefulGrovel index story
Remember – decisions are where the business, analytics and IT all come together
Once deployed analytics cannot be a “black box”, we must understand analytic performanceObviously you need a 'hold out sample' or business as usual random group to compare to.You need to understand what's working and what's the next challenge – which segments are being retained, for instanceYou must understand operational negation.You need to track input variables, scores, decisions or actions taken (classic example is in collections where a strategy may dictate a 'do nothing' strategy, but the collections manager overrides the decision and puts the accounts into a calling queue) and operational data that fed the decisionBoth analysts and business users must think about what they can do to improve decision making, which is the foundation of adaptive controlIn our retention example I need to have some customers I don’t attempt to retain or that I don’t spend any money retaining. I have to capture what the call center representative ACTUALLY offered and what was actually accepted (if anything), not just what SHOULD have been offered and I have to be able to show the results to my business users in terms they understand.
Actions not predictions - Business rules add actions to analytic insightTime to impact - Externalized decisions, rapid deploymentBusiness results - Decisions impact KPIs, implement strategyEngage IT, Business - Rules for the business, Decision services for ITMonitoring , compliance - Rules and explicit models expose decision making
Sometimes the ROI is discussed in terms of keeping a company in business, eliminating those company killing risks.This company offered trade credit insurance and a decision service provides trade credit calculations, combining business rules and algorithms developed by using predictive analytic techniques. Business experts interact directly with trade credit rules by using rule templates to ensure that rules match the underlying object model, without business users having to understand the object model’s technicalities.They got some classic BRE ROI:A country can be added in a few weeks rather than months, so the organization went from 2 to 16 covered countries in just 3 months.Ongoing changes can be made in hours rather than weeks.Most importantly though the system allows immediate changes to rules in a crisis, preventing the possibility of liability or other legal exposure for the organization.
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
The most basic representation is a list of rules or a rule set. These are simple atomic rules grouped into a logical set for execution and storage. Rule sets are often shared between decisions.
A big part of the benefit companies get from managing rules comes from putting the business in charge more directly. Having business users manage business rules reduces costs by eliminating a step – that of having the business tell IT what they want so that IT can do code it – and improves accuracy by eliminating the impedance of this step. It also increases business agility by making it easier for a company to respond to changes – after all the business folks notice the changes firstIn my experience, the use of business rules and a BRMS to manage high-volume, operational decisions have a proven track record in reducing application development costs and application maintenance. It takes fewer developers and less time to specify how a system or service should behave using a BRMS thanks to the increased expressive power of business rules and the improved verification and testing offered by BRMS. Maintenance of these rules is easier, often dramatically easier, than the maintenance of the equivalent code. Not only are can the business rules be changed independently and safely; business users can participate directly in the maintenance process for the first time. Domain expertise is applied more directly and less time and money are spent making changes.
Faster, easier, independent changes to decision logic Coordination of decisions across channels and products Higher employee productivity and resource utilization a leading French retailer of cosmetics, faced the challenge of multiple channels and overlapping marketing and loyalty offers. A customer might be eligible for a loyalty offer, have downloaded a web coupon and heard a “discount word” on the radio. This made it hard for retail staff to ensure the price was handled correctly at the point of sale. In addition, they needed a better way to get loyalty offers to the customer. Yves Rocher replaced their POS devices with Linux-based terminals and developed a rules-based system that allowed all the pricing rules to be defined by the marketing department and then downloaded into the terminals. All relevant offers are correctly combined at the point of sale. This system also takes the customer’s loyalty card and applies loyalty offers. Using purchases and loyalty history, it prints an incentive offer designed to bring the customer back to the store on the card itself—the cards are re-printable so the customer sees the offer that will be made when they return.
the classic sources of rules – policies, regulations, best practices, expertise. Many, most, of your rules will come from these sources. But your data is also rich source of rulesYou can analyze the data you have to find exactly which thresholds you should use in your rules – is it really customers above 21 years old or would 20 or 19 be a more meaningful cut off?You can use data mining techniques to actually find the rules – association rules such as if someone is buying this product try and sell them that product or segmentation rules – using your historical data to find out what were the most successful rules in the pastYou can use this historical data to create new insights into customers – predicting things about them that extend the data you can work with and against which you can write rules.
Descriptive analytics can be used to categorize customers into different categories – to find the relationships between customers - which can be useful in setting strategies and targeting treatment. But this analysis must be delivered not just to your analysts, also to your systems. Analysis is generally done offline, but the results can be used in automated decisions – such as offering a given product to a specific customer – often by developing rules that embody the analytics.For instance a decision tree can be created where each branch, each end node, identifies the segment for a particular member.Data mining can also create rules with less effort and with a quicker time to market in certain circumstances
Predictive analytics often rank-order individuals. For example, rank-order members by their likelihood of renewing – the higher the score, the more “completers” for every “non-completer”. The risk or opportunity is assessed in the context of a single customer or transaction and these models are not an overall pattern, even if they are predictive. Models are called by a business rules engine to “score” an individual or transaction, often in real time, though the analysis is done offline.These models are often represented by a scorecard where each characteristic of a member adds to the score and where the total score can then be returned.
All these pieces contribute to ever-more sophisticated decision services that support your business processes.Decision Services externalize and manage the decisions production processes and systems needBusiness rules allow business users to collaborate in the declarative definition of decisionsAnalytics can create better more data-driven business rulesAnd ultimately additional predictive analyticsAdaptive control allows test and learn to become part of a continuous improvement loop
Here’s another example, this time of an insurance company with about 750,000 policies that implemented a risk-based underwriting decision service for use across its systems. In the first year an eight-point reduction in combined ratio – a big deal for an insurance companyThey got this improvement from all the areas I see when clients apply decision managementThey reduced costs by eliminating many manual reviews and by putting underwriters and actuaries in charge of the rules behind the decision – they eliminated or reduced many of their IT costs.They boosted revenue, the second major area, by improving risk management (far more tiers and more fine grained decisioning) and by focusing their staff on the book of business and helping agents improve it rather than on transactional approvalsThe third area does not show up in the specifics but when I talked to them it was clearly the most powerful aspect of the whole thing. They gained true strategic control over their underwriting decisions.
Actions not predictions - Business rules add actions to analytic insightTime to impact - Externalized decisions, rapid deploymentBusiness results - Decisions impact KPIs, implement strategyEngage IT, Business - Rules for the business, Decision services for ITMonitoring , compliance - Rules and explicit models expose decision making
Little decisions add up so focus on operational or front-line decision makingThe purpose of information is to decide so put your data and analytics to workYou cannot afford to lock up your logic so externalize it as business rulesNo answer, no matter how good, is static so experiment, challenge, simulate, learnDecision Making is a process to be managed
Begin!Identify your decisionsHidden decisions, transactional decisions, customer decisionsDecisions buried in complex processesDecisions that are the difference between two processesConsiderWho takes them nowWhat drives changes in themAssess Change ReadinessConsider Organizational changeAdopt decisioning technologyAdopt business rules approach and technologyInvestigate data mining and predictive analyticsThink about adaptive control
Decision Management Solutions can help youFind the right decisions to apply business rules, analyticsImplement a decision management blueprintDefine a strategy for business rule or analytic adoptionYou are welcome to email me directly, james at decision management solutions.com or you can go to decision management solutions.com / learn more. There you’ll find links to contact me, check out the blog and find more resources for learning about Decision Management.